Success rate in visualizing distal coronary arteries by TTE
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",isbn:"978-1-83768-165-5",printIsbn:"978-1-83768-164-8",pdfIsbn:"978-1-83768-166-2",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"681a60ff84a29b9f72de9b662bab9c38",bookSignature:"Prof. Shailendra K. Saxena",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/12104.jpg",keywords:"Viral Outbreak, Viral Epidemic, Viral Pandemic, Disease Outbreak Detection, COVID-19, Nipah, Ebola, MERS, Pathogenesis, Host-Pathogen Interaction, Immunity, Antiviral",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 25th 2022",dateEndSecondStepPublish:"June 22nd 2022",dateEndThirdStepPublish:"August 21st 2022",dateEndFourthStepPublish:"November 9th 2022",dateEndFifthStepPublish:"January 8th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"5 days",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Prof. Dr. Shailendra K. has received many awards and honors in India and abroad, including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various prestigious international societies/academies, including the Royal College of Pathologists, United Kingdom; Royal Society of MedProf. He is the vice dean and Professor at King George\\'s Medical University, Lucknow.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"14",totalChapterViews:"0",totalEditedBooks:"9",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"16",title:"Medicine",slug:"medicine"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"441704",firstName:"Ana",lastName:"Javor",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/441704/images/20009_n.jpg",email:"ana.j@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Thus, treatment of coronary artery disease (CAD) is performed primarily on the basis of anatomic measurements of stenosis severity, although the disease severity correlates better with physiologic disturbances which can be revealed by the analysis of coronary artery flow and coronary flow reserve (CFR). Direct invasive measurements of coronary flow signal using Doppler flow wires and catheters provide a lot of information on the pathophysiology of coronary flow dynamics (Chamuleau et al, 2001; Bax et al, 2006; Braden, 2006; Werner et al., 2006; Kaul & Jayaweera, 2008; Courtis et al., 2009). But in clinical practice, these invasive techniques are rarely applied because of the time and expense required. Alternative methodology in detecting coronary flow and CFR is positron emission tomography which is feasible but expensive and scarcely available (West & Kramer, 2009). In fact, a large-scale assessment of such important functional parameters is hampered by the lack of a reliable, low-cost, noninvasive method that might be used for this purpose (Pellikka, 2004). Some years ago transesophageal echocardiography was proposed for evaluation of coronary flow and CFR in man. However, this method demonstrates some important limitations: it is semiinvasive, and has optimal feasibility in visualizing the flow in only very proximal part of the left anterior descending coronary artery (LAD) (ranging from 69% to 97%) and right coronary artery (RCA) (ranging from 66% to 83%) which allowes the assessment of transstenotic or prestenotic CFR but not poststenotic CFR (Vrublevsky et al., 2001, 2004). Until recently, transthoracic echocardiography (TTE) evaluation of the CAD was aimed at the assessment of regional and global left ventricular function (Youn & Foster, 2004). Direct transthoracic visualization of the coronary arteries was attempted in children and occasionally in adults with coronary artery anomalies, arteriovenous fistulas, and aneurysms (Harada et al., 1999; Hiraishi et al, 2000; P.C. Frommelt & M.A. Frommelt, 2004). However, with the advent of harmonic imaging, contrast agents and high-frequency transducers, direct transthoracic Doppler visualization of non-dilated arteries and measurement of coronary artery flow is now relevant in the majority of patients. The aims of this review are to outline the technical aspects of coronary artery visualization and flow measurements both at rest and with pharmacological stress, to demonstrate pathologic coronary artery flow patterns by TTE and to discuss clinical implications of TTE for patients with suspected or confirmed CAD.
One of the first reports on TTE visualization of distal LAD as a vessel with a most superficial location (3-7 cm from skin) was presented by Fusejima et al., 1987. However, clinical application of the method was limited by a low success rate of the LAD assessment because adequate signals were available in only 35% of control subjects and 50% of patients with cardiac disease. The introduction of high-frequency (7.5-MHz) transducers allowed a more frequent visualization of distal LAD (Ross et al., 1990; Kenny & Shapiro, 1992). But a major limitation of Doppler evaluation of blood flow in distal LAD associated with a low-intensity Doppler signal caused by ultrasound attenuation was overcome with echocontrast agents alone. Several reports on echocardiographic contrast enhancement of coronary artery images have been published and shown considerable improvement of visualization rate of distal LAD. Caiati et al., 1999a, 1999b, during TTE gave a peripheral injection of Levovist, a contrast agent consisting of a suspension of galactose microbubbles, and demonstrated enhanced coronary color flow Doppler signals. Lambertz et al., 1999, reported the increase of visualization rate of mid-distal LAD during high-frequency TTE from 40% without a contrast agent to 88% with Levovist. In addition, contrast administration facilitated the positioning of the pulsed sample Doppler volume. Okayama et al, 2002, demonstrated a success rate of CFR assessment in the LAD in 70% of cases without an echocontrast agent and in 97% after a Levovist injection with particular improvement of systolic pattern quality. With the routine use of contrast, coronary flow and CFR measurements in the distal LAD become feasible in the majority of patients. Several reports gave little information on transthoracic visualization of the posterior descending coronary artery (PDA) (Voci et al., 2002; Tokai et al., 2003). Voci et al., 2002, could estimate coronary blood flow in the PDA in 76% of patients at rest, but CFR assessment was performed in 54% of patients only because of hyperventilation caused by adenosine. Tokai et al., 2003, demonstrated beneficial effect of Levovist on coronary blood flow signals in the PDA, with increase of visualization rate from 30% without a contrast agent to 86% with it.
High frequency transducers can be most successfully used for scanning the apical area, that is for examination of distal LAD or PDA. Unlike distal LAD and PDA, non-distal LAD, circumflex artery (Cx) and right coronary artery (RCA) are located too deep for TTE, and high-frequency transducers preferred by many investigators can not be used (Boshchenko et al., 2008). Standard low-frequency transducers provide a good penetration and seem to be the optimal choice for scanning the RCA, Cx and proximal and mid LAD. Unfortunately, as standard cardiac low-frequency transducers have lower resolution and lower sensitivity of Doppler exam, low success rate of visualization of non-distal coronary arteries was reported in earlier studies (Voci & Pizzuto, 2001). In recent years, the advantage of using a multifrequency (1.7- to 3.5-MHz) transducer with second tissue harmonics lies in the fact that coronary flow imaging and standard TTE can be readily alternated (Pellikka, 2004), and it is true for estimating both distal LAD and PDA, and proximal-mid segments of coronary vessels. Wideband of low ultrasound frequencies of multifrequency transducers at the exit (1.7-3.5 MHz) provides a good scanning depth which is particularly important for visualizing non-distal LAD and PDA, and second tissue harmonics enables to receive reflected ultrasonic waves of high-frequency range (3,5-7 МГц) at the entrance improving the image quality for both near and far setting zones. According to our data the feasibility of LAD and PDA visualization with second harmonics has progressively improved, and harmonic imaging facilitated the examination considerably (Table 1).
Fusejima et al., 1987 | high-frequency transducer | 35%healthy volunteers 50% CAD patients | |
Hozumi et al., 1998a | 23 | high-frequency transducer | 78 |
Lambertz et al., 1999 | 45 | high-frequency transducer, contrast agent | 80 |
Caiati et al., 1999a | 56 | harmonic, contrast agent | 88 |
Lethen et al., 2003 | 33 | high-frequency transducer | 91 |
Boshchenko et al., 2008 | 150 | harmonic | 93 |
Sicari et al., 2008 | 1779 | harmonic, contrast agent | 96 |
Krzanowski et al., 2000 | 50 | harmonic | 33 |
Tokai et al., 2003 | 50 | harmonic, contrast agent | 86 |
Takeuchi et al., 2004 | 151 | harmonic, contrast agent | 83 |
Otsuka et al., 2005 | 129 | harmonic, contrast agent | 97 |
Boshchenko et al., 2008 | 150 | harmonic | 91 |
Krzanowski et al., 2000 | 50 | harmonic | 0 |
Boshchenko et al., 2008 | 150 | harmonic | 33 |
Success rate in visualizing distal coronary arteries by TTE
Modern, high quality ultrasound systems are required for success scanning. In most cases TTE is performed with the help of Acuson Sequoia 512 (Acuson) or HDI 5000, HDI 5000 SonoCT and iE33 (Philips). We used Vivid 7 (GE HealthCare) with 1.7-3.5 MHz narrow-band transducers with second harmonic mode (Boshchenko et al., 2008, 2009).
After obtaining optimal quality B-mode image, the search for coronary arteries is started with color Doppler mapping with or without the use of harmonics. To achieve the best image quality the sample size of color Doppler should be kept at minimum. As the Doppler velocities of coronary blood flow are low, the velocity range should be set with a low Nyquist limit (15-20 cm/s), and filters should be decreased. Too low Nyquist limit can be a cause of more color Doppler artifacts obscuring the images (<10-13 cm/s), too high Nyquist limit is not able to detect low blood flow velocity within coronary arteries (Pellikka, 2004; Korsarz & Stein, 2004; Boshchenko et al., 2008, 2009). Some ultrasound systems offer special color maps for coronary artery examination including second or third harmonics of B-mode and color Doppler mapping, low Nyquist limit, special gain for B-mode and Doppler mode, etc.
There are several windows by which coronary arteries can be visualized with the patients in the supine or left decubitus positions (Krzanowski et al., 2000, 2003; Saraste et al., 2005; Boshchenko et al., 2008). Standard parasternal short- and long-axis views from second- or third intercostal space or low parasternal short- or long-axis views from fourth- or fifth intercostal space should be used. Alternatively, a modified apical 2, 3 or 5-chamber view or subcostal scanning can be performed. TTE has a very high time resolution, while spatial resolution is low due to a small size of scanning windows. So, coronary arteries appear as linear intramyocardial color fragmental structures of approximately 0.5-2.5 cm in length and 2 to 4 mm in diameter. Initially, a short part of arteries can be visualized. Then, by step-by-step movement of the transducer according to the course of the vessel, a longer fragment of arteries can be assessed.
The scanning depth for the search of proximal and mid coronary artery segments should be set at 10-15 cm. The transducer should be placed at the left parasternal position from second or third intercostal space and a modified short-axis B-view of great vessels should be obtained. The search of the left main coronary artery (LMCA) and proximal LAD can be started in B-mode (figure 1A, B) by consecutive clockwise and cranial rotation of the transducer, but color Doppler mapping which makes images clearer can also be recommended for initial search. The LMCA has approximately 1-3 cm in length, and the vessel should be visualized along its entire extension.
Images of the LMCA and proximal LAD (pLAD). The left parasternal position, a modified parasternal short axis view of great vessels, Nyquist limit is 20-67 cm/s. A – LMCA, B-mode; B – pLAD, B-mode; C – LMCA, Color Doppler mapping; D - bifurcation of the LMCA; Color Doppler mapping.
The normal anterograde blood flow in the LMCA is identified on color Doppler map as a linear structure dawning from left coronary sinus of Valsalva and has a red or blue color depending on the placement of the transducer, anatomic features of chest and LMCA origin (figure 1C). Bifurcation of the vessel into the LAD and Cx is a marker of LMCA distal board (figure 1D). If the origin of the Cx can not be found, the LMCA and proximal LAD should be assessed as a common segment. Proximal LAD should be assessed after the LMCA by a slight change of the imaging plane in a parasternal or low parasternal short-axis B-view or by change of the position in a modified parasternal long-axis view. The origin of the first diagonal branch can be used as a distal mark of proximal LAD (fig. 2A). Mid LAD should be searched in the low left parasternal position from third- to fifth intercostal spaces and a modified short- or long-axis view of the left ventricle in the anterior interventricular groove (fig 2B, C). Distal LAD should be assessed from the low left parasternal position to a modified apical five-chamber position at varying levels using different short- and long-axis views in the anterior interventricular groove before, at or after the apex of the left ventricle (fig 2D,E). The setting depth should be reduced approximately to 6-10 cm, and the transducer may be substituted for a high-frequency one, because the location of distal LAD is superficial. The LAD is the best vessel for TTE assessment as there are clear anatomic marks for its search and segmentation, such as: anterior interventricular groove, origin of the first diagonal branch and papillary muscles. The segment of the LAD from the origin of diagonal branch to papillary muscles in the short-axis view should be assessed as its mid segment, and the segment of the LAD apical to papillary muscles should be marked as distal LAD. Apical window is usually the best one to obtain low Doppler angles for velocity measurements in the LAD. The normal anterograde blood flow in the entire LAD before the apex is identified as a red linear color signal on color Doppler map, which reflects the direction of the flow from base to apex of the left ventricle.
Unlike the LAD, the scanning depth for the RCA and Cx should be set at 12-15 cm. Proximal Cx should be visualized in the left parasternal position and a modified short-axis B-view of great vessels with the slight caudal tip of the transducer. The normal anterograde blood flow in proximal Cx is identified as a blue linear color signal on color Doppler map, reflecting the direction of the flow from the transducer (fig. 3A). There are no clear anatomic marks for the distal border of proximal Cx. Visualization of mid and distal segments of the Cx is very difficult and possible in a few patients only. Mid and distal Cx should be examined with the same position of the transducer as proximal Cx. As the mid and distal Cx are located in the coronary sulcus at the border between the left atrium and left ventricle, the angulation from heart basis to apex at the level of papillary muscles is usually required (fig 3B). The posterior papillary muscle can be used as a symbolic border between mid and distal Cx. The first or second obtuse marginal branches (OMB) presenting distal parts of the Cx can be assessed from fourth- and fifth intercostal spaces in the apical long-axis position in a modified four- or five-chamber view at either lateral or inferior wall of the left ventricle (fig. 3C).
Proximal RCA should be examined in the left parasternal position from second- or third intercostal spaces in modified short- or long-axis B-views as a structure dawning from right coronary sinus of Valsalva and lying along the anterior wall of the aorta (fig. 4A, B). It may be relatively easy to visualize proximal RCA in B-mode and Color Doppler mapping but pulse-wave Doppler examination is rarely correct because the angle between the direction of coronary blood flow and Doppler beam exceeds 60 degrees. The mid and distal RCA should be searched using Color Doppler mapping only. The subcostal position, a short-axis B-view or a modified apical two-chamber position with cranial angulation of the transducer should be used for the search of mid RCA (fig. 4C). Good quality images of the PDA – usually distal
Doppler Color images of the LAD. A – distal board of proximal LAD with origin of the first diagonal branch (I DB); B – mid LAD (mLAD), the left parasternal position, a modified parasternal short axis view of great vessels; C – mLAD, the left parasternal position, a modified parasternal long axis view; D – distal LAD (dLAD) before circumflexing the cardiac apex, a modified apical five chamber position; E - dLAD after circumflexing the apex of the left ventricle.
RCA – can be obtained from fourth- and fifth intercostal spaces in the apical long-axis position in a modified two- or three-chamber view with caudal tip of the transducer in the posterior interventricular groove (fig. 4D). There are no anatomic marks for segmentation of the entire RCA. The direction of the normal mid RCA and PDA flow is the same as that of the normal LAD flow.
Color Doppler images of the Cx, Nyquist limit is 20-33 cm/s. A – proximal Cx (pCx); the left parasternal position, a modified parasternal short-axis view of great vessels; B - mid Cx (mCx); the left parasternal position, a modified parasternal short-axis view at the level of papillary muscles; C – the first obtuse marginal branches (OMB) presenting distal Cx, the apical long-axis position, a modified five-chamber view.
Main pitfalls of assessment of coronary arteries by TTE arise due to partial visualization of the vessels and anatomic features of coronary bed (Boshchenko et al., 2008). Certain large branches of coronary arteries – the intermediate coronary artery, diagonal and marginal branches can occasionally be visualized and confused with main coronary arteries, most frequently with the LAD (fig. 5A, B). It is more typical for the occluded main artery in which case the branches enlarge and take over its function (Krzanowski et al., 2003). To avoid this mistake, the LAD should be searched in the anterior interventricular groove along its entire extension with the end points in the LMCA and distal LAD. By moving step-by-step towards the aorta or downwards to the left ventricle apex without loosing the LAD sight, the LAD can be correctly identified. The diagonal and marginal branches have no connections with either the LMCA or distal LAD or both.
The distinction between various vessels seen at the lateral and inferior walls of the ventricle can be challenging (Krzanowski et al., 2003). As first and second OMB is lying parallel and close to the PDA, they may be taken for the PDA. If the artery is circumflexing the posterior
Color Doppler images of the RCA. Nyquist limit is 17-20 cm/s. A – proximal RCA (pRCA); the left parasternal position, a modified parasternal short-axis view of great vessels; B – pRCA; the left parasternal position, a modified parasternal long-axis view. C – mid RCA (mRCA); a modified apical two-chamber position with cranial angulation of the transducer; D - the PDA as distal RCA, the apical long-axis position, a modified two-chamber view.
surface of the apex of the left ventricle, this vessel is detected by coronary angiography as the PDA in the majority of cases. On the other hand, if the artery is sending a branch to the posterior papillary muscle or lying next to the lateral wall of the left ventricle, this vessel is identified by coronary angiography as the OMB. The PDA which is usually a distal RCA may arise from the Cx if the left coronary artery is strongly dominant, and this fact may result in diagnostic mistakes too.
In scanning mid or distal LAD, certain extracardiac arteries visualized on color Doppler mapping may be confused with the LAD, for example, the left internal thoracic artery (LIMA). However, the pulse-wave Doppler assessment allows an accurate distinction between them: unlike coronary arterial flow which is biphasic systole-diastolic with predominant diastolic phase, the extracardiac arteries show a typical peripheral arterial flow with high velocity predominantly systolic flow and very low anterograde or retrograde diastolic flow.
As there are no clear anatomic marks for segmentation of the Cx and RCA, the pitfalls in assessing the place of coronary stenoses can be observed.
Large branches of coronary arteries confused with main coronary arteries: A - the intermediate coronary artery, the diameter of which is equal to those of the LAD and Cx; pLAD – proximal LAD, pCx – proximal Cx; B – the first diagonal branch (I DB), which is larger, than mother LAD; mLAD – mid LAD.
Frequently, in coronary artery occlusions and retrograde filling distal to occlusions in particular, the mistakes in distinction between coronary artery and concomitant vein may be made, i.e. mid cardiac vein may be assessed as the LAD or posterior cardiac vein – as the PDA (fig 6). As veins are larger, located closer to the right ventricle than arteries and demonstrate a three-phase predominantly systolic flow with very high respiratory variations, it is not very difficult to differentiate between the vessels. Krzanowski et al., 2003 and Youn & Foster, 2004, observed that a strong signal confusing coronary artery flow may
Distinction between the posterior descending coronary artery (PDA) and concomitant posterior cardiac vein (PCV): A – the PDA is slighter, located closer to the left ventricle and demonstrates a biphasic predominantly diastolic flow without respiratory variations; B – the PCV is larger, located closer to the right ventricle and demonstrates a three-phase predominantly systolic flow with high respiratory variations; C- simultaneous image of the PDA and PCV.
be generated by pericardial fluid, but the flow within the pericardial sac is most pronounced in systole while the coronary artery flow is predominantly diastolic. We did not have similar difficulties in our practice.
Feasibility of TTE in visualizing coronary arteries with the addition of harmonics, newer transducers, and contrast agents has been reported to be as high as 100% for distal LAD and 33-97% for the PDA (table 1). Imaging of the entire Cx and proximal and mid RCA has been possible with a low rate (table 1, Kenny & Shapiro, 1992; Krzanowski et al., 2000, Watanabe et al., 2001; Saraste et al, 2006, etc.). Our data (Boshchenko et al., 2008) of TTE feasibility in the assessment of main coronary arteries with both success Color Doppler mapping and good quality of pulse-wave Doppler recording presented in tables 2 and 3 agree with the data of other authors. TTE demonstrated adequate success rate of color Doppler mapping of the LMCA, all LAD segments and PDA, and poor feasibility in detecting other segments of main coronary arteries.
Vessel | proximal segment | mid segment | distal segment |
LMCA | 70 | ||
LAD | 82 | 83 | 93 |
Cx | 35 | 5 | 31 |
RCA | 25 | 35 | 95 |
Success rate of the detection of main coronary arteries by TTE (%) (Boshchenko et al, 2008)
Vessel | one segment (proximal or mid or distal) | two segments (proximal and mid or proximal and distal or mid and distal) | three segments (proximal and mid and distal) |
LAD | 93 | 92 | 68 |
Cx | 35 | 0 | 0 |
RCA | 95 | 51 | 6 |
Success rate of the detection of one and more segments of each coronary artery by TTE (%) (Boshchenko et al, 2008)
Thus, although this technique requires experience and practice, and only skilled operators can be expected to achieve a 90% success rate in visualizing the coronary arteries, it is possible to use current technology in a clinical setting.
With pulse-wave Doppler assessment efforts should be directed at maintaining the optimal Doppler angle, and size of the sample volume (Hozumi et al., 1998a, 1998b; Caiati et al, 1999a, 1999b). The angle of incidence between the Doppler beam and flow direction should be minimized, less than 30 degrees being optimal for coronary artery. The sample volume or gate should be reduced (1.5-3.0 mm) and positioned within the coronary artery (Pellikka, 2004). We usually use a 2-3 mm gate for pulse-wave Doppler, a 3 mm gate for proximal segments and a smaller gate (2 mm) for distal segments.
According to coronary physiology, most coronary flow occurs during diastole with a smaller systolic component (fig. 7) (Gould et al, 1974; Bax, 2006). So, coronary blood flow on pulse-wave Doppler image is presented as continuous, biphasic systole-diastolic flow with predominant diastolic phase and low velocities.
Transthoracic measurements of coronary flow velocity are proved to be highly reproducible and correlate with invasive measurements and measurements with positron emission tomography (Hozumi et al., 1998a; Caiati et al, 1999a, 1999b, Lethen et al., 2003; Ueno et al., 2002b). The measurements can include assessment of peak velocity, time velocity integral, and mean velocity in systole and diastole (fig. 8). But, in evaluating coronary flow, most investigators measure the diastolic component, and peak diastolic blood flow velocity is assessed most frequently as an easily and quickly estimated characteristic. The duration of diastolic and systolic flow is another potential measure (Crowley & Shapiro, 1998; Hozumi et al., 2000; Daimon et al., 2005; Youn et al., 2005).
Doppler examination in the PDA: A – laminar flow in the PDA is presented by red linear structure on color Doppler map; B - velocity pattern registered by pulse-wave Doppler; s – systolic phase, d – diastolic phase.
In previous works, control subjects with normal coronary angiograms and normal left ventricular systolic function showed that the peak diastolic velocity in distal LAD was 21.2±7.9 cm/s and the duration of diastolic coronary artery flow was 58.5±6.4% of the R-R interval at rest within the range of physiologic heart rates (60-100 b/m) (Youn et al, 2002). In studies including the participants without significant LAD stenosis, the peak diastolic velocity in distal LAD was ranging from 21±8 cm/s to 28±9 cm/s (Hozumi et al, 1998a, 1998b; Youn et al, 2002; Pizzuto et al, 2004). In our study (Boshchenko et al., 2008) with
Scheme of normal coronary blood flow pattern; Vps and Vpd – systolic and diastolic peak coronary flow velocities, VTIs and VTId – systolic and diastolic time velocity integrals, ATs and ATd – acceleration time in systole and diastole.
healthy volunteers the coronary flow characteristics were comparable in the conforming segments of the LAD, Cx and RCA, and coronary flow velocities showed a non-significant decrease from proximal segments to distal segments of coronary arteries (tab. 4). But the limits of normal distal LAD flow at rest have not yet been largely settled due to the multitude of variables affecting the baseline coronary flow velocity.
Characteristics | proximal LAD (n=17) | mid LAD (n=16) | distal LAD (n=17) |
Vps , cm/s | 17 (15-21) | 14 (12-16) | 14 (13-15) |
Vms , cm/s | 13 (12-16) | 11 (9-12) | 11 (9-12) |
VTIs , cm | 3.7 (3.2-4.9) | 3.3 (2.7-3.7) | 2.8 (2.2-3.6) |
ATs, ms | 118 (107-126) | 111 (89-118) | 111 (96-111) |
Vpd , cm/s | 28 (22-35) | 25 (22-30) | 25 (21-27) |
Vmd , cm/s | 22 (16-27) | 19 (16-22) | 19 (16-20) |
VTId , cm | 10.9 (7.9-13.8) | 10.6 (8.8-13.5) | 10.4 (8.6-11.9) |
ATd, ms | 204 (126-244) | 200 (155-222) | 156 (133-171) |
Coronary blood flow in the LAD (mediana (range)). Vps and Vpd – systolic and diastolic peak coronary flow velocity, Vms and Vmd – systolic and diastolic mean coronary flow velocity, VTIs and VTId – systolic and diastolic time velocity integrals, ATs and ATd – acceleration time in systole and diastole.
In adults, TTE is successfully attempted for detection of coronary artery anomalies, arteriovenous fistulas, and coronary aneurysms (Harada et al., 1999; Hiraishi et al., 2000; P.C. Frommelt & M.A. Frommelt, 2004). Thus, the overall sensitivity and specificity of TTE for accurate identification of coronary aneurysms are 95% and 99%, respectively (Hiraishi et al, 2000). Unlike aneurysms, direct visualization of atherosclerotic plaques in non-dilated or mild-dilated coronary arteries with the help of TTE is rather an exception. Accordingly, TTE can not assess correctly the structure and length of atherosclerotic plaques. Unlike computed tomography, TTE as well as coronary angiography detects coronary stenoses basing not on visualizing atherosclerotic plaque
Direct detection of atherosclerotic plaques is rarely possible. It is reliable only in case of a major proximal plaque with acoustic shadow due to calcium (fig. 9). Maxted et al, 1998, tried to search for coronary artery stents in proximal and mid LAD, using increased echogenicity, markedly thickened walls of the artery in the stent site, and a stented lumen
The cascade proximal plaques with calcium in proximal LAD. B-mode.
with relatively straight edges and a diameter approximately equal to that of the deployed stent. Stents were determined in 10 of 13 cases, but examinations were time consuming, each taking approximately 60 minutes to obtain, process, and review the images. Despite our optimism with this technology, we realize that this method for direct assessment of the plaques and stents
On the other hand, intravascular ultrasound and epicardial echocardiography studies have demonstrated that coronary atherosclerosis is a diffuse pathological process and before CAD is clinical evident, >90% of the coronary artery tree is atherosclerotic. So, coronary artery wall structure, artery lumen diameter and their qualitative or quantitative changes can be predictors of coronary artery stenosis and direct markers of coronary vasomotor function (Voci & Pizzuto, 2001). High-frequency TTE using a 7.5 or 10 MHz transducer can be used to correctly and accurately measure the wall thickness and diameter of distal LAD and to detect their changes (Kenny et al., 1990; Perry et al., 208a, 2008b). Takeuchi et al, 2006, demonstrated that wall thickness and external diameter of the LAD enlarged with the increase of the number of CAD risk factors, and wall thickness of the LAD >0.72 mm was a predictor of LAD stenosis with 74% sensitivity and 87% specificity. Perry et al, 2008a, found the wall thicknesses and external diameters of the LAD in patients with CAD to be significantly larger than those in normal volunteers, indicating atherosclerotic buildup. TTE can detect vasodilating effects of nitroglycerin and salbutamol on the LAD, correlating with peripheral vascular reactivity to these vasodilators (Perry et al, 2008b). So, TTE is a probably useful tool for noninvasive assessment of coronary vasoreactivity and provides a chance to be a surrogate marker of coronary stenosis (Perry et al, 2008а, 2008b).
The detection of coronary stenosis by TTE should be performed basing on Doppler methods – color Doppler mapping and pulse-wave Doppler recoding.
First, Color Doppler mapping should be used for stenoses search. Even at low Nyquist limits (13-18 cm/s), the color Doppler flow pattern in the normal coronary artery is uniformly consistent with laminar flow. The focal flow acceleration and turbulence may be detected as aliasing zone on color Doppler map and can assist in localizing the stenosis site (Krzanowski et al, 2000; Hozumi et al., 2000; Takeuchi et al., 2001; Saraste et al., 2005). Second, Doppler velocity patterns should be registered by pulse-wave Doppler. If Doppler color mapping shows a color laminar flow, Doppler velocity patterns should be obtained in the site with the best signal on color Doppler map. If a local increase of the velocity appears on Doppler colour flow map as a localized area of aliased and disturbed signal, Doppler velocity patterns should be obtained in the site of alising (fig. 10).
Third, coronary blood flow should be measured. Velocities of coronary blood flow in the stenosis site are increased compared with non-stenosis sites (both prestenotic and poststenotic) (Hozumi et al., 2000, Okayama et al., 2008). Some authors have shown redistribution of coronary flow in LAD stenosis with the increase of systolic wave due to stenosis and decrease of diastolic-to-systolic velocity ratio in the poststenotic site (Crowley & Shapiro, 1998; Daimon et al., 2005). There are transthoracic quantitative diagnostic markers of coronary artery stenosis >50%, offered by Krzanowski et al, 2000, and Anjaneyulu et al., 2008, based on the measurement of peak diastolic velocity in the stenosis site. The peak diastolic velocity >1.5 m/s has demonstrated 85% sensitivity and 88%
Examples of Color Doppler flow mapping of distal RCA presented by PDA: upper panel – patient C. without RCA stenosis: artery color flow map is red indicating low velocity with peak diastolic flow velocity (Vpd) equal to 25 cm/s; lower panel – patient S. with 75% stenosis of mid RCA: Changes in the color flow map for color aliasing in the stenosis site and distal to it with Vpd acceleration up to 80 cm/s.
specificity diastolic velocity >1.5 m/s has demonstrated 85% sensitivity and 88% specificity in the detection of LMCA stenosis>50% (Anjaneyulu et al., 2008). Krzanowski et al., 2000, and Saraste et al., 2005, showed that a local peak diastolic flow velocity >2.0 m/s could be used as a sign of diameter reduction>50% for all three main coronary arteries. It seems attractive and easy to detect coronary stenoses basing on the search of the aliasing zone and the measurement of peak diastolic flow velocity only, but both methods are semi-quantitative and, unfortunately, inaccurate. As previously reported, laminar peak diastolic velocity in the coronary artery is from 0.21 ± 0.08 m/s (Youn et al., 2002, Hozumi et al., 1998) to 0.28 ± 0.09 m/s (Pizzuto F., 2004), and the velocity will not exceed 1 m/s even in case of its 3-4-fold increase in the stenosis site. So, local peak diastolic flow velocity >2.0 m/s is a highly specific, but low sensitive marker of coronary artery stenosis. On the other hand, some other reasons, such as reologic factors, heart rate, etc. can cause disturbed Doppler signal, hence local aliasing may be a highly sensitive but low specific sign of coronary stenosis. So, Hozumi et al, 2000, have observed localized aliasing by color flow mapping in 100% of patients with LAD restenosis >50% after percutaneous transluminal coronary angioplasty (PTCA), and 56% of patients without restenosis. Finally, both markers are strongly dependent on different hemodynamic factors (perfusion pressure, heart rate, blood pressure, myocardial mass, etc.) and technical setting (depth of scanning, quality of pulse-wave Doppler pattern, angle of incidence between the Doppler beam and flow direction, etc). So, most authors have supposed that the ratio of stenotic-to-prestenotic diastolic velocity is more correct and allows an exclusion or minimization of hemodynamic influence.
To measure the stenotic to prestenotic velocity ratio, the localized color aliasing corresponding to local flow acceleration should be searched first to obtain coronary flow velocity in the stenosis site. When localized aliasing is detected, the sample volume of pulse-wave Doppler should be set at the aliasing and Doppler velocity pattern should be recorded. Then, the sample volume should be slightly moved from the aliasing to the prestenosis site and spectral Doppler recording should be made again (fig. 11).
stenosis in mid LAD. Left panel – prestenosis site; right panel – stenosis site; Vpd – peak diastolic blood flow velocity. The stenotic to prestenotic flow velocity ratio is 60/22 = 2.72 (>2.0).
Krzanowski et al., 2000, and Saraste et al., 2005, determined the stenotic-to-prestenotic peak blood flow velocity ratio over than 2.0 to be a sign of >50% stenosis with 62-100% sensitivity and 92-100% specificity for the LAD, 63% sensitivity and 96% specificity for the RCA, and 38% sensitivity and 99% specificity for the Cx. The same sensitivity (86%) and specificity (93%) were demonstrated by Hozumi et al., 2000, for the ratio of prestenotic-to-stenotic mean diastolic velocity <0.45 in the detection of LAD restenosis after PTCA. ТТЕ with the use of both a local peak diastolic flow velocity >2.0 m/s and stenotic-to-prestenotic peak blood flow velocity ratio >2.0 permitted to reveal 48% of all LAD stenoses, 30% of all Cx stenoses and 14% of all RCA stenoses (Krzanowski et al., 2000). Like the assessment of peak diastolic velocity this approach is easy, semi-quantitative and, though to a lesser extent, dependent on hemodynamic factors too. On the other hand, it is known that volume blood flow velocity in the prestenosis site is equal to that in the stenosis one, and, assuming the constant artery diameter and measuring diastolic time velocity integrals in both stenosis and prestenosis sites, the vessel % stenosis can be calculated according to a modified continuity equation. The feasibility of this approach for transesophageal echocardiography was demonstrated by Isaaz et al, 1998 (as cited in Vrublevsky et al., 2001). We use this concept for TTE. Diastolic time velocity integral (VTId) is measured in stenosis and prestenosis sites, and the stenosis % area is calculated as: stenosis, % = 100 × (1 - prestenotic VTId / stenotic VTId) (fig.12). The sensitivity and specificity of >50% stenosis identification by a modified continuity equation in the LAD are 72% and 96%, in the Cx - 40% and 94%, and in the RCA – 50% and 93%, respectively, for the segments which are successfully visualized (Boshchenko et al., 2008). The data on all segments, successfully visualized and unvisualized, are shown in table 5.
Coronary artery | Coronary angiography | Transthoracic echocardiography | ||||||
stenosis | stenosis | false positive | false negative | sensitivity | specificity | positive predictive value | negative predictive value | |
LMCA (n=100) | 1 | 0 | 0 | 1 | - | 100 | - | 97 |
LAD (n=300) | 55 | 39 | 8 | 24 | 56 | 96 | 79 | 89 |
Cx (n=300) | 28 | 6 | 4 | 26 | 7 | 94 | 33 | 70 |
RCA (n=300) | 47 | 21 | 9 | 35 | 26 | 93 | 57 | 78 |
Diagnostic accuracy of Doppler TTE in the detection of >50% stenosis in main coronary arteries (Boshchenko et al., 2008).
Thus, TTE is highly specific for identification of coronary stenosis >50%, but, being low sensitive for Cx and RCA stenosis, may be helpful as a screening tool for LMCA and LAD stenosis >50%, limiting the use of groundless catheterization.
TTE permits visualizing separate segments of coronary arteries only, and the detection of coronary occlusion as well as stenoses by TTE should be performed basing on Doppler color-coding of the flow velocity and direction. The first offered TTE sign of coronary artery occlusion was the absence of coronary blood flow on color Doppler map, and it demonstrated very low feasibility of the method (Krzanowski et al., 2000) because it was difficult to differentiate between real absence of coronary flow due to occlusion and absence of visualization of coronary artery due to TTE limitations. So, at present, TTE does not seem to be a suitable method for the assessment of acute coronary occlusions. But transthoracic color-Doppler ultrasound can be useful after acute myocardial infarction for the detection of an open LAD, reflecting adequate myocardial reperfusion basing on anterograde flow in the LAD alone or together with perforators (Voci et al, 2002).
Calculation of stenosis % area of proximal LAD according a modified continuity equation by TTE. A - scheme of calculation by TTE; B - example of Doppler flow patterns in patient with 35% stenosis according to coronary angiography data; C - Doppler flow patterns in patient with 60% stenosis; D - Doppler flow patterns in patient with 80% stenosis; VTId – diastolic time velocity integral
Unlike acute occlusion, chronic total coronary occlusion (CTO) of over 1-month duration leads to the formation of stable collateral coronary pathways (Werner & Figulla, 2002; Braden, 2006; Werner et al., 2006). Recently, feasibility of TTE for the CTO identification of the LAD and RCA has been established. Watanabe et al., 2001, proposed the inversion of the coronary blood flow in the epicardial collateral vessels on color Doppler map to be a main ultrasound sign of CTO. It has been established that retrograde flow in distal LAD is a good marker of LAD occlusion with 88% sensitivity and 100% specificity (Hirata et al., 2004) and retrograde flow in the PDA is a good marker of RCA occlusion with 67% sensitivity and 100% specificity (Otsuka et al., 2005). But Pizzuto et al., 2006, doubted such a high sensitivity of TTE in the detection of LAD occlusion having revealed a retrograde flow in distal LAD in only 43% of patients with CTO and normal anterograde flow in more than half patients (55%). Angiography data demonstrate that in LAD and RCA occlusions, besides collateral flow distal to the occluded region through the connections on the epicardial surface, 63-86% of patients have intramyocardial collateral channels lying usually in the interventricular septum. According to these findings an additional examination of the retrograde flow in the septal branches of the LAD and RCA has demonstrated the increase of TTE sensitivity in the CTO detection from 88 to 96% for the LAD (Hirata et al., 2004) and from 67 to 80% for the RCA (Otsuka et al., 2005, Saraste et al., 2005).
According to our data (Boshchenko et al., 2009), the sensitivity and specificity of retrograde flow for identification of the occluded LAD by TTE in distal LAD alone were 77% and 97%, and those in both distal LAD and septal branches of the LAD - 85% and 97%, respectively. The sensitivity and specificity of retrograde flow for identification of the occluded RCA by TTE in the PDA alone were 77% and 98%, and those in both the PDA and septal branches of the RCA - 88% and 98%, respectively. Basing on these data the following order of TTE detection of LAD and RCA occlusion could be offered. First, potential epicardial collateral vessels should be examined. The retrograde flow in distal LAD will be a highly specific marker of LAD occlusion, and the retrograde flow in the PDA will be a sign of RCA occlusion, respectively. In this case, the examination can be stopped. Second, if the flow in distal LAD and RCA is anterograde, the septal (intramyocardial) collateral pathways of the LAD and RCA should be examined additionally, because 8% of patients with LAD CTO and 11% of patients with RCA CTO demonstrate an inversion of the flow direction in the septal branches only (Boshchenko et al, 2009) (fig. 13). Unlike the LAD and RCA, low success rate of visualization of the Cx does not allow the use of TTE for CTO detection.
TTE detection of CTO is based on the identification of coronary blood flow direction alone without the assessment of the rest Doppler coronary flow velocities and, thus, it does not depend on the hemodynamic conditions of the patients and does not require discontinuation of the therapy including antianginal, hypotensive, and antiarrhythmic drugs. So, TTE can be used in unstable patients, patients with life-threatening rhythm and conductance disturbances. TTE can be rather an attractive non-invasive method with little time consumption and good specificity in standardized approach, answering the principal question – whether the LAD or RCA is chronically opened or closed. The length and accurate site of CTO can not be assessed by TTE.
Over the last two decades it has been demonstrated that measurements of coronary flow reserve (CFR) are a diagnostic approach providing a lot of additional information on the
Patient B. Proximal occlusion of the right coronary artery (RCA). Examples of the retrograde coronary blood flow in septal branch of the RCA and in the PDA (intramyocardial and epicardial collateral flow, respectively).
function of coronary artery and assisting in the decision-making process of cardiac interventions. Reserve of coronary blood flow is defined as the ability of coronary flow volume to increase under maximal coronary hyperemia when compared with coronary flow volume at rest. Coronary flow velocity correlates well with flow volume, and measurements of the ratio of hyperemic-to-rest coronary flow velocity can substitute direct measurements of the ratio of hyperemic-to-rest flow volume. At present, intracoronary Doppler with adenosine or papaverine infusion remains to be the reference standard for the assessment of coronary flow velocity reserve (CFVR) in vivo. In normal coronary bed, microvascular flow at rest is low-optimal for the maintenance of wall perfusion, and it increases at stress due to maximal peripheral vasodilatation according to myocardial demand; normal epicardial coronary artery with a high degree of elasticity under these conditions demonstrates a high CFVR. In agreement with experimental and intracoronary wire studies (Gould et al., 1974; Gould & Lipscomb, 1974), three main mechanisms, alone or in combination, may explain why coronary flow does not increase or even decreases during adenosine infusion in stenosis. First, in mild, moderate or tight severe stenoses, CFVR reflects the state of microcirculation to a greater degree. Epicardial stenoses induce increased resistance to flow, and microvascular resistant vessels already are dilated maximally at rest to maintain the basal flow. Therefore, a hyperemic stimulus results in a smaller increment of poststenotic flow, and the change of flow or the ratio of hyperemic-to-rest flow are less, and CFVR distal to the stenosis site is reduced. Second, in incompletely calcified severe coronary stenosis, the coronary artery preserves some degree of elasticity and may collapse during adenosine infusion allowing a decrease in intraluminal tense pressure, which is induced by flow acceleration in the stenosis site. This collapse may translate distally into a damped flow producing at times a coronary steal effect. Third, prestenotic collaterals may be opened at stress, causing coronary redistribution from the critically hypoperfused bed to less stenotic regions. So, CFVR should be measured in the most distal part of the epicardial artery for assessing its function along the entire length.
TTE is a good method for detection of distal flow in the LAD and PDA (usually distal RCA), and it has the main advantage among other noninvasive technologies being valid for easy, fast, direct assessment of distal CFVR. That is particularly important in cases of repeated monitoring of stenosis progressive changes. Hozumi et al, 1998a, 1998b, performed the first validation of TTE comparing CFVR in the LAD with simultaneous intracoronary Doppler guide wire assessment. TTE reflected invasive measurement of coronary flow velocity and CFVR accurately, and the agreement between the two methods was 0.97 for averaged diastolic and systolic peak velocities, 0.98 for diastolic peak velocity and 0.97 for CFVR. A very good correlation was observed between TTE and intracoronary Doppler guide wire not only for the LAD (Caiati et al., 1999a, 1998b; Lethen et al., 2003) but for the PDA as well (Ueno et al., 2002b). The correlation ranging from 0.79 to 0.97 has been reported for noninvasive techniques compared with invasive ones in cases of decision-making process (Hozumi et al., 1998a, 1998b; Caiati et al., 1999a, 1998b) and intracoronary intervention (Lethen et al., 2003). Thus, TTE can be used as a possible substitute of the invasive method for correct clinical measurement of CFVR, particularly in the LAD.
A variety of agents can be used as vasodilators to examine CFVR by TTE including adenosine, dipyridamole and dobutamine with or without additional atropine (Pellikka, 2004; Korsarz & Stein, 2004). All drugs have potent endothelium-independent vasodilating properties, but act by different mechanisms. Dobutamine increases metabolic myocardial demand inducing the rise of rate-pressure product, and accordingly contributes to the increase of coronary flow. Both adenosine and dipyridamole induce coronary arteriolar vasodilatation associated with hyperemic coronary flow as a result of stimulation of adenosine A2-receptors on arteriolar smooth-muscle cells causing vasorelaxation.
As dobutamine stress echocardiography is widely available, it is appropriate to consider a combination of CFVR examinations and these tests (Pellikka, 2004). But dobutamine infused with the traditional rate of 5-10-20 mcg/kg/min induces a smaller acceleration of the flow and lower CFVR than adenosine as a reference standard (Meimoun et al., 2006). Similar CFVR values can be obtained with two drugs at peak dobutamine infusion only (with the infusion rate of 40 mcg/kg/min). But it is not always possible in patients with positive dobutamine stress echocardiography and chest pain. Furthermore, CFVR assessment with recording of the LAD or RCA flow velocity at each step is time-consuming and requires an average of 25-30 minutes. A number of technical difficulties during TTE with dobutamine also must be stressed because a high heart rate and consequently a reduced diastolic filling time and increased myocardial contractility can impair good-quality recording of the coronary flow pattern. This is particularly true for very high heart rates at peak stress test.
Like intracoronary Doppler wire assessment of CFVR, adenosine, a direct coronary vasodilator, seems to be a drug of the first choice for TTE. Intravenous adenosine has a short half-life (8-10 seconds) inducing rapid onset of vasodilatation and resulting in short examination periods. CFVR assessment may be performed at bedside within a few minutes. Adenosine should be infused intravenously at the rate of 140 mcg/kg/min for 2 minutes. Coronary flow velocities are measured before and immediately after the cessation of adenosine infusion. But if simultaneous evaluation of regional function is necessary, repeated infusion of adenosine is required, and the effect of ischemic preconditioning can be observed. Adenosine may be a cause of adverse effects, attributed to nonselective stimulation of the A1-, A2B-, and A3-receptors, because of its lack of specificity for the A2-receptors. Among these effects, arterial hypotension, dyspnea and chest discomfort are frequent and tend to impair LAD flow velocity recording during hyperemia.
Dipyridamole is an indirect vasodilator, decreasing the cellular uptake of adenosine and increasing its endogenous level. Compared with adenosine, the duration of the infusion is longer (0.56 mg/kg for 4 minutes or 0.84 mg/kg for 6 minutes) and, depending on the dose administered and infusion rate, its effects can last up to 30 minutes allowing a combined CFVR and wall motion evaluation. Peak vasodilating activity is obtained 2 to 4 minutes after the cessation of dipyridamole infusion. In agreement with the comparative TTE study of Lim et al, 2000, dipyridamole with the infusion rate of 0.56 mg/kg may induce lower CFVR than adenosine, and CFVR value, achieved with adenosine, can be obtained with dipyridamole infusion rate of 0.84 mg/kg only. Adverse effects after dipyridamole infusion appear slowly and have a less intensity than those after adenosine, without marked dispnea and arterial hypotension. Both adenosine and dipyridamole are contraindicated in patients with active asthma or severe chronic obstructive pulmonary disease with wheezing. The vasodilative effect of both drugs is reversed by antagonists, such as methylxanthines, which compete for the A2 receptor, and therefore, foods and drinks containing xantines (chocolate, coffee, tea, colas, etc.) should be avoided for at least 12 hours before testing.
In summary, adenosine should be a drug of choice for TTE, if CFVR assessment is required in one artery only. If combined evaluation of regional function and CFVR assessment in the LAD or both the LAD and PDA are planned, the choice should be made in favor of dipyridamole with the infusion rate of 0.84 mg/kg. Dobutamine could be a good alternative to adenosine and dipyridamole for CFVR assessment in patients with contraindications to both drugs or scheduled dobutamine stress echocardiography. If echocontrast infusion is necessary, a separate intravenous line should be made.
For CFVR assessment, the correction of angle incidence between the Doppler beam and flow direction may be used; however, as evaluation is performed on the basis of ratio values, the absolute velocity is of less importance. However, the angle should not change between the baseline and hyperemic phases of the test, so the differences in blood flow velocity can still be compared. After obtaining the baseline and hyperemic coronary flow velocities, CFVR should be expressed as the ratio of coronary flow velocity under maximal vasodilatation to coronary flow velocity at rest (fig.14) (Picano et al., 1999; Korcarz & Stein, 2004).
Various investigators consider that the peak diastolic flow velocity (Vpd), mean diastolic flow velocity (Vmd), and average peak diastolic flow velocity (AVpd) can be used as a reference parameter for CFVR assessment. Vpd, being a most easily and quickly measured
Example of CFVR evaluation in the PDA. Vpd – peak diastolic coronary flow velocity.
index, demonstrates a higher inter- and intra-observed variability of assessment than Vpm and AVpd. But CFVR evaluation is based on the ratio values of the same parameters, and similar values of CFVR were reported for Vpd and Vmd (Hozumi et al., 1998; Caiati et al., 1999b). The time required to complete a CFVR test in one artery is around 5–8 minutes depending on the investigators’ experience.
Pizzuto et al, 2001, 2003 revealed CFVR value for the LAD ranging from 2.90±0.58 to 3.05±0.81 in control group of patients with angiographically normal coronary arteries, and similar values for CFVR were found in <50% LAD in-stent restenosis (Lambertz et al., 1999; Pizzuto et al, 2003). Later, CFVR in angiographically normal LAD patients with remote CAD (presence of previous remote myocardial infarction and wall motion abnormalities) was determined also as preserved (Pizzuto et al, 2004). According to numerous studies using TTE the cut-off value of CFVR is generally accepted to be 2.0 for predicting significant LAD stenosis in patients under decision-making process, after intracoronary intervention, and with in-stent restenosis (table 6). The sensitivity and specificity of Doppler TTE measurement of CFVR for detecting significant angiographic disease were satisfactory, ranging from 77% to 94% and 65% to 100%, respectively, slightly depending on the study population, dose of stress medications and cut-off value of diameter % stenosis. In one study, CFVR with a cut-off value <2.0 was a significantly better predictor (90%sensitivity, 96%specificity) of LAD stenosis than multidetector computed tomography (80%sensitivity, 93%specificity) and improved the diagnostic accuracy of the latter from 90 to 96% (Pizzuto et al., 2009). A cut-off value <2.0 was appropriate even for the diagnosis of significant stenosis of donor LAD giving collaterals to other arteries (Pizzuto et al., 2004; Iwata et al, 2006).
Several investigators studied the accuracy of Doppler TTE measurement of CFVR in the PDA to detect stenosis in the RCA, and the same cut-off value of CFVR (<2.0), demonstrating sensitivity 84-89% and specificity 83-96%, was accepted for predicting significant RCA stenosis (Voci et al., 2002; Takeuchi et al., 2004).
Authors | Diameter stenosis, % | CFVR, cut-off value | Reference parameter | Stress agent | Sens | Specif | Population |
Hozumi et al., 1998b | "/>70% | <2.0 | Vpd, Vmd | adenosine | 92% | 82% | unselected |
Caiati et al., 1999a | "/>70% | <2.0 | Vpd, Vmd | dipyridamole | 86% | 90% | unselected |
Voci et al., 2002 | "/>70% | <2.0 | Vpd | adenosine | 89% | 100% | unselected |
Voci P et al., 2003 | "/>90% | <1.0 | Vpd | adenosine | 92% | 98% | unselected |
Nohtomi Y. et al., 2003 | "/>50% | <2.0 | Vpd | dipyridamole | 94% | 65% | unselected |
Lethen et al., 2003 | "/>70% | <2.0 | S/D mean velocity | adenosine | 89% | 90% | after PTCA |
Takeuchi et al., 2004 | "/>50% | <2.0 | AVpd | adenosine | 91% | 75% | unselected |
Matsumura et al., 2003 | "/>70% | <2.0 | Vmd | adenosine | 90% | 93% | unselected |
Rigo et al., 2003 | "/>50% | <1.9 | Vpd | dipyridamole | 81% | 84% | unselected |
Okayama et al., 2002 | "/>70% | <2.0 | AVpd | adenosine | 94% | 88% | unselected |
Pizzuto et al., 2003 | "/>70% | <2.0 | Vpd, Vmd | adenosine | 91% | 95% | after stenting |
Lowenstein et al., 2003 | "/>70% | <2.0 | Vpd | dipyridamole | 87% | 73% | unselected |
Hirata et al., 2006 | "/>50% | <2.0 | Vmd | adenosine | 77% | 100% | after PTCA |
Pizzuto et al., 2009 | "/>70% | <2.0 | Vpd | adenosine | 90% | 96% | unselected |
Sensitivity and specificity of Doppler TTE measurement of CFVR for detecting significant LAD stenosis. Vpd – and Vmd – peak and mean diastolic coronary flow velocities, AVpd – average peak diastolic velocity of coronary blood flow, S/D mean velocity – systole-diastolic mean velocity of coronary blood flow, Sens – sensitivity, Specif – specificity.
CFVR can be a marker of chronic occluded LAD or RCA function. CFVR is always depressed in the collateral dependent vascular area, and the value<2.0 is registered in the LAD or PDA distal to the occlusion in all cases (Takeuchi et al., 2005, Pizzuto et al., 2006). But TTE is able to reveal patients with CFVR <1.0 reflecting coronary steal effect which develops in 33% to 47% of occluded vessel territories (Takeuchi et al., 2005, Pizzuto et al., 2006). Coronary steal effect occurs when collateral circulation is poor and the donor artery is significant stenotic (Pizzuto et al, 2006; Braden, 2006).
Transthoracic CFVR measurement may have incremental predictive value in addition to stress echocardiography for detecting CAD in LAD and RCA distribution. In the study by Rigo et al., 2003, CFVR<1.9 in the LAD correlated well with stenosis severity and wall-motion abnormalities. The inverse correlation between CFVR and peak wall motion score index in the overall study population was significant (r=0.46: p<0.001), and the concordance between the 2 techniques was good (80%) (Rigo et al, 2003). CFVR had excellent sensitivity (81-94%) but moderate or good specificity (65-84%) in detecting significant LAD stenosis whereas wall motion score index showed lower sensitivity (69-74%) and higher specificity (82-95%), and both techniques demonstrated a similar diagnostic accuracy ranging from 82 to 86% for CFVR and from 81 to 84% for wall motion score index (Rigo et al, 2003; Lowenstein et al., 2003; Nohtomi et al., 2003). So, the data for flow and function may be complementary in predicting the underlying angiographic findings and increase the diagnostic accuracy up to 94%(Nohtomi et al., 2003), because abnormal wall motion may confirm and negative CFVR may exclude CAD more accurately. So, CVFR measurement is more important in patients with negative stress echocardiography by wall motion criteria.
Similarly, transthoracic CFVR by Doppler is associated with perfusion abnormalities, as it has been shown with exercise single photon emission computed tomography thallium imaging. Most patients with abnormal perfusion in the LAD territory had abnormal CFVR in the LAD; those with perfusion defect in the RCA territory had abnormal CFVR in the PDA; vise versa, patients with normal exercise perfusion had CFVR greater than 2.0. A transthoracic CFVR in the LAD <2.0 provided data consistent with those obtained by single photon emission computed tomography for physiologic estimation of stenosis severity with 94% sensitivity and 100% specificity (Hirata et al., 2006). Tokai et al., 2003, showed the equivalent potential of transthoracic CFVR in the PDA for detecting myocardial ischemia in the left ventricular inferior region and RCA stenosis. CFVR in the Cx could be obtained in 72% of patients and CFVR<2.0 had 92% sensitivity and 96% specificity for predicting the perfusion defect in the Cx territory.
In one comparative study (Osorio et al., 2007) with simultaneous CFVR assessment and quantitative analysis of myocardial contrast perfusion, CFVR was a much better index for detecting LAD stenosis than myocardial blood flow reserve (sensitivity 92% and 84%, specificity 94% and 87%, and accuracy 93% and 86% for CFVR and myocardial reserve, respectively).
In summary, CFVR measurement may be a useful tool for detecting myocardial ischemia in the LAD distribution and, probably, in the RCA and Cx territory.
Evaluation of patients with angiographic moderate coronary artery stenosis is challenging. Neither visual assessment of an angiogram nor quantitative coronary angiography can accurately predict the significance of most moderate stenoses (50–70%). Rest coronary flow is preserved until severe narrowing occurs (>80%), but according to the experimental study in mice (Wikstrom et al., 2005), there is a close correlation between CFVR in the left coronary artery and coronary minimal lumen diameter of this vessel (r=0.87, p<0.005), and CFVR depends on the diameter % stenosis. In clinical studies, the degree of angiographic stenosis also is related to CFVR in both the LAD and RCA (Lambertz et al.,1999; Pizzuto et al., 2001; Voci et al., 2002, 2003; Sicari et al., 2009). With insignificant LAD stenosis (<50%), CFVR in the LAD is normal (Lambertz et al., 1999; Voci et al., 2002), equal to 2.6±0.6 in subjects with totally normal coronary arteries, 2.6±0.6 in subjects with LAD stenosis of 0-20% and 2.2±0.5 in subjects with LAD stenosis of 20-40% (Sicari et al., 2009). In cases with moderate stenosis, overall group CFVR is intermediate (from 2.23± 0.20 to 2.33±0.32); and only in high-grade stenosis CFVR is low (from 1.12±0.49 to 1.64 ± 0.30). But according to individual analysis data, CFVR reduction is found upstream in the classical ischemic cascade, and can well detect stenosis unable to induce regional wall motion abnormalities during stress echo (see 4.3). CFVR is often <2.0 when stenosis is still moderate (50%-60%) (fig. 15) mirroring the decrease of subendocardial blood flow without total wall perfusion deficit and wall motion disturbance. So, demonstrating a higher negative predictive value in the detection of ischemia, compared with wall motion score index or nuclear cardiac imaging, CFVR is very useful in moderate stenosis to assess its functional significance and to help consider the necessity of revascularization (when CFVR<2.0).
In severe stenosis, CFVR is more preserved in subjects with stenosis of 70-90% than in subjects with stenosis greater than 90% (Voci et al., 2003). Pizzuto et al., 2001 and Voci et al., 2003, found the cut-off value of CFVR <1.0 to be a marker of coronary flow steal effect in patients with severe LAD stenosis (>90%) with 92%sensitivity, 98%specificity, and 97%diagnostic accuracy. This finding is in agreement with the experimental work of Gould et al., 1974, who showed that CFVR in over 90% stenosis of the lumen diameter is blunted mainly due to either stenosis site collapse or development of coronary steal through collateral vessels.
So, CFVR by Doppler TTE may be a useful tool for: 1) selection of patients with moderate stenosis and CFVR<2.0 for revascularization and 2) detection of patients with >90%stenosis basing on coronary steal effect (CFVR<1.0).
Another important application of TTE is assessment of early efficacy and remote coronary restenosis after intracoronary interventions. In the study of Pizzuto et al., 2001, CFVR measurement was performed before and within 1 day after LAD stenting. Prestent impaired CFVR increased after success stent implantation from 1.45±0.5 to 2.58±0.7 in groups with 70-90% and >90% stenosis, and an absence of CFVR change was revealed only in 3 patients with >90%stenosis due to reactive hyperemia, microvascular stunning or post-procedure vasoconstriction. Unlike intracoronary Doppler studies with the guide wire or guiding catheter, the influence of which on the vascular endothelium and coronary flow dynamics is unpredictable and may be a cause of high rate of impaired CFVR after balloon angioplasty or stenting (50% and 30%, respectively) even in the absence of any residual angiographic stenosis, TTE, being a non-invasive technique, is deprived of this effect, and can more accurately reflect changes of coronary flow.
In the study including 53 patients, coronary angiography and CFVR detection were performed 6 months after PTCA of the LAD (Lethen et al., 2003). The investigators observed CFVR to significantly differ in the groups with and without restenosis, and CFVR with the cut-off value <2.0 demonstrated 89% sensitivity and 90% specificity for predicting
Examples of CFVR in distal LAD in patients with LAD stenosis are presented. A - case with mild proximal LAD stenosis, CFVR is 2.3; B - case with moderate LAD stenosis; the basal peak diastolic flow velocity is normal, but it increases less than 2 times after dipyridamole, and CFVR is decreased (1.6); C - case with proximal severe LAD stenosis and basal poststenotic acceleration of coronary flow with high peak diastolic flow velocity in distal LAD at rest; after dipyridamole the increase of peak diastolic flow velocity is slight, CFVR is equal to 1.3.
significant LAD restenosis. Similar studies were carried out after LAD stent, and CFVR with the cut-off value <2.0 also demonstrated sensitivity ranging from 77% to 93% and specificity ranging from 78% to 100% for predicting LAD restenosis (Ruscazio et al., 2002; Pizzuto et al, 2003a; Hirata et al., 2006). One of the criticisms of TTE is that assessment has been limited to the LAD, but progress is being made in examining other vessels. High success rate of CFVR measurements in the PDA permits to hope for the forthcoming appearance of CFVR studies before and after RCA intracoronary interventions.
Thus, noninvasive CFVR assessment by TTE is a very promising tool in monitoring early efficacy of LAD angioplasty or stenting and detecting remote restenosis after LAD intracoronary interventions.
Besides stenosis, several factors can influence the baseline or hyperemic coronary flow and cause decreased CFVR. Elevation of the basal flow can occur with hypertension, tachycardia, anemia, thyrotoxicosis, or valvular disease, or after caffeine intake (coffee, tea, cola, etc.). The conditions which can decrease the maximum hyperemic flow include not only epicardial coronary stenosis but also microvascular disease with impaired structure, function, rheology, and lower density of capillaries, polycythemia and elevated left ventricle end-diastolic pressure (Baumgart et al., 1998; Hirata et al., 2001; Neishi et al., 2005; de Grigorio et al., 2005; Sherrid et al., 2006; Kaul & Jayaweera, 2008).
According to the data of studies in patients with acute anterior myocardial infarction, CFVR is able to reflect an absence of microvascular reperfusion in the presence of a patent epicardial coronary artery, and is a negative determinant for myocardial viability (Ueno et al., 2002a; Rigo et al., 2004; Meimoun et al., 2009). Ueno et al., 2002a, reported that CFVR measured in open infarct-related LAD on day 1 after success primary angioplasty was a good predictor of the recovery of regional left ventricle function at discharge, whereas Rigo et al., 2004, found CFVR in the LAD <2.0 to be useful also in predicting an unfavorable long-term (6-month) outcome. In the study of Meimoun et al., 2009, a cut-off CFVR value of 1.7 was an independent predictor of both the left ventricle recovery at a 3-month follow-up, and in-hospital adverse cardiac events including death, recurrent myocardial infarction, and acute heart failure.
CFVR<2.0 was associated with an unfavorable outcome in an unselected cohort of patients with positive and negative stress echocardiograms by wall motion criteria (Rigo et al., 2008), in patients with intermediate LAD stenosis (Rigo et al., 2007), and in patients with chest pain and normal or near-normal coronary arteries (Sicari et al., 2009). CFVR<1.8 provided independent information for prognostic stratification in patients with inducible ischemia during stress echocardiography, and it was associated with an increase of event rate (death and myocardial infarction) by 46% during 19-month follow-up (Cortigiani et al., 2010). But LAD CFVR demonstrated an extremely high additional prognostic value (up to 160%) in patients with negative stress echocardiography by wall motion criteria, and a reduced CFVR was associated with a less benign long-term outcome (Rigo et al., 2006; Cortigiani et al., 2010). In the study of Rigo et al., 2006, CFVR<1.92 was the best predictor of future events (sensitivity = 77%, specificity = 85%), and the 3-year event-free survival was higher in patients with normal CFVR (>1.92) compared with patients with reduced CVFR (98% versus 64%, P<0.0001). The main reasons for CFVR importance in the prognosis in patients with negative stress echocardiography are the following: (1) CFVR can detect moderate coronary stenoses inducing no wall motion abnormalities during stress test (see 4.3, 4.4); (2) CFVR can be useful for the detection of severe stenosis in patients on antiischemic therapy. When ischemia-dependent wall motion abnormality is the diagnostic end point, concomitant antiischemic therapy modifies the prognostic value of stress echocardiography, markedly reducing TTE sensitivity; in fact, a positive test result in on therapy patients is more prognostically malignant, and a negative test result is less prognostically benign. The flow information in patients with known or suspected coronary artery disease is relatively unaffected by concomitant antiischemic therapy, and does not influence CFVR significantly. In the study with 1779 patients performed by Sicari et al., 2008, the symptoms-free survival was higher in patients with normal CFVR (>2.0) and lower in patients with abnormal CFVR (87% versus 34%, P =0.0001), and it was comparable to that in patients with normal CFVR on and off therapy and in patients with abnormal CFVR on and off therapy; so, antiischemic therapy at the time of testing did not modify the prognostic value of Doppler CFVR. (3) CFVR can identify severe microvascular disease (Rigo et al., 2006; Cortigiani et al., 2007; Sicari et al., 2009). Coronary microvascular dysfunction does not normally induce wall motion abnormalities but has been linked to an adverse outcome, which can be accurately detected by abnormal CFVR. So, in a prospective study in 394 patients with angiographically normal or near-normal coronary arteries and preserved regional and global left ventricular function at baseline and during stress, CFVR <2.0 adds incremental value to the prognostic stratification achieved with clinical and angiographic data (Sicari et al., 2009), and selects a subgroup of patients with a less benign prognosis. During a median follow-up of 51 months, long-term survival estimated for adverse events (death and myocardial infarction) showed an extremely better outcome for the patients with a normal CFVR compared with those with an abnormal CFVR (96% versus 55%).
In summary, CFVR provides independent information for prognostic stratification, and a reduced CFVR is associated with a less benign long-term outcome in patients with acute anterior myocardial infarction, known or suspected CAD with positive and particularly negative stress echocardiography by wall motion criteria. CFVR measurement is offered to be added to routine stress echocardiography.
We do not have our own sufficient experience of coronary graft assessment. But in published studies TTE visualization of the left internal mammary artery (IMA) graft has varied from 70% to 100%, the venous grafts to the LAD could be assessed in 91%, to the RCA – in 96%, to the Cx – in 90% (Chirillo et al., 2001, 2004; Chong et al., 2004). The Nyquist limits should be set at 20 cm/s for the IMA grafts and 10-12 cm/s for the venous grafts (Youn & Foster, 2004). In the proximal part next to the subclavian artery, patent IMA grafts demonstrate a flow pattern with predominant systolic velocity, and next to distal anastomosis site the flow pattern has predominant diastolic velocity similar to that of the coronary artery. Some researchers made an effort to detect dipyridamole-induced CFVR in the IMA and venous grafts. Meyer et al., 2004, compared CFVR in the proximal left IMA graft with the help of simultaneous TTE and intracoronary Doppler guide wire assessment. TTE reflected invasive measurement of CFVR accurately, and the agreement between the two methods was 0.97, and patients with CFVR>2.1 showed patent IMA graft. According to the data of Chirillo et al., 2001, 2004, CFVR<1.9 in proximal IMA grafts and CFVR <1.6 in venous grafts demonstrated a higher sensitivity in the detection of 50-100%graft stenoses in comparison with wall motion score index. But recently, Pizzuto et al., 2005 have determined distal CFVR in the IMA grafts to depend on flow interrelation in the graft and native LAD, and to be a better predictor of LAD function than IMA graft patency in the presence of flow competition. So, TTE value for identification of graft patency is not yet established, and further studies are required.
In summary, with the advent of harmonic imaging, contrast agents and high-frequency transducers, TTE can be used for the diagnosis of coronary narrowing as a noninvasive, inexpensive, non-X-ray, high time resolution and widely used in clinical practice method. After a period of investigators’ training, detection and measurement of distal LAD and RCA flow and CFVR by TTE is feasible in more than 90% of patients and correlates well with invasive measurements. Clinical applications of TTE for direct assessment of coronary stenoses and occlusions are limited due to partial artery visualization, and TTE can not be accepted as an alternative to coronary angiography. But Doppler TTE in CAD patients can be a helpful method providing additional information on the coronary artery function for:
noninvasive clinical repeated or serial measurements of coronary flow velocity at rest after stress which are necessary for understanding the physiology and pathophysiology of coronary flow; in this case the LAD can be used as a reference vessel;
preliminary identification of coronary stenosis in the LMCA, LAD and PDA;
detection of restenosis after percutaneous intracoronary interventions in the LMCA, LAD and PDA;
diagnosis of reperfusion in the acute phase of myocardial infarction in the LAD territory with evaluation of no-reflow after recanalization;
identification of chronic occluded LAD and RCA;
assessment of endothelial function;
measurement of CFVR in the following groups of patients: (1) with suspected or confirmed CAD in those who undergo stress echocardiography (dobutamine or dipyridamole) for reflecting perfusion, function, prognosis-risk stratification, and selection of significant coronary stenosis (CFR<2.0) of the LAD and RCA; (2) with intermediate-grade coronary obstruction where the functional assessment of the lesion is doubtful, and CFVR can be used in considering
We would like to thank Tatyana Taushkanova for her assistance in the preparation of this chapter.
Snake venoms are the secretion of venomous snakes, which are synthesized and stored in special glands. The venom were synthesized and stored into the base of channeled or tubular fangs through which it is ejected. Most of the venoms are complex mixture of a number of proteins, peptides, enzymes, toxins and non-protein inclusions [1]. Some of snake venom possess biological effects on various functions, such as blood coagulation and pressure, regulation, and transmission of nerve impulses. These venoms have been studied and developed by researchers for use as pharmacological or diagnostic tools, and even drugs. Snake venom is a therapeutic agent for various diseases due to its physiologically active components [2]. More specifically, cobra venom has been used historically in Ayurveda in the treatment of arthritis and other chronic diseases [3].
Chinese physicians are implementing the use of snake venom products to treat stroke patients, and research has been conducted surrounding its analgesic, anti- cancerous and anti-inflammatory effects [2]. Cytotoxic effects of snake venom have potential to degrade and destroy tumor cells [4]. There are basically three types of snake venom according to its effects [5, 6]. (a) Hemotoxic venoms, which affects cardiovascular system and blood functions, (b) cytotoxic venoms targets specific cellular sites or muscles and (c) neurotoxic venoms harms nervous system of human body. The families, Elapidae and Viperidae, are large majority of the research done surrounding the medical application of snake venom involves species within these groups. Both elapids and vipers are front fanged snakes that belong to the superfamily Colubroidea. Notable species of the elapid family are cobras of the genus
Snake venom components caused retardation of growth of cancerous cells due to its therapeutic activity, potency for many diseases and disorders [7]. Many excellent publications characterized use of venoms for the treatment of various therapeutic conditions such as human diseases, cancer and inflammation [8, 9].
Snake venoms are complex mixtures; mainly it has proteins, which have enzymatic activities, inorganic cations, calcium, potassium, magnesium, zinc, nickel, cobalt, iron, and manganese. Zinc is necessary for anti-cholinesterase activity; calcium is required for activation of enzyme like phospholipase. Some snake venoms also contain carbohydrate, lipid, biogenic amines, and free amino acids [10].
Proteins found in snake venom include toxins, neurotoxins, nontoxic proteins, and many enzymes, especially hydrolytic ones. Enzymes are protein in nature including digestive hydrolases, L-amino-acid oxidase, phospholipases, thrombin-like pro-coagulant, and kallikrein-like serine proteases and metalloproteinases (hemorrhagins), which damage vascular endothelium.
Phosphodiesterases enzyme interfere with the prey’s cardiac system, mainly to lower the blood pressure. Phospholipase A2 causes hemolysis by lysing the phospholipid cell membranes of red blood cells [2]. Amino acid oxidases and proteases are used for digestion. Also amino acid oxidase triggers some other enzymes and is responsible for the yellow color of the venom. Hyaluronidase enzymes increases tissue permeability to accelerate the absorption of other enzymes into tissues Table 1.
Type | Name | Origin species |
---|---|---|
Oxidoreductases | Dehydrogenase Lactate | Elapidae |
L-amino-acid oxidase | All species | |
Catalase | All species | |
Transferases | Alanine amino transferase | |
Hydrolases | Phospholipase A2 | All species |
Lysophospholipase | Elapidae, Viperidae | |
Acetylcholinesterase | Elapidae | |
Alkaline phosphatase | ||
Acid phosphatase | ||
5′-nucleotidase | All species | |
Phosphodiesterase | All species | |
Deoxyribonuclease | All species | |
Ribonuclease 1 | All species | |
Adenosine triphosphatase | All species | |
Amylase | All species | |
Hyaluronidase | All species | |
NAD-nucleotidase | All species | |
Kininogenase | Viperidae | |
Factor X activator | Viperidae, Crotalinae | |
Heparinase | Crotalinae | |
α-Fibrinogenase | Viperidae, Crotalinae | |
β-Fibrinogenase | Viperidae, Crotalinae | |
α-β-Fibrinogenase | ||
Fibrinolytic enzyme | Crotalinae | |
Prothrombin activator | Crotalinae | |
Collagenase | Viperidae | |
Elastase | Viperidae | |
Lyases | Glucosaminate ammonia-lyase |
Main enzymes of snake venom [1].
Pllypeptides include cytotoxins, cardiotoxins, and postsynaptic neurotoxins (such as α-bungarotoxin and α-Cobratoxin), which bind to acetylcholine receptors at neuromuscular junctions. Also polypeptides contains metals, peptides, lipids, nucleosides, carbohydrates, amines, and oligopeptides. Chemical composition variations of snake venom due to geographical and Ontogenic of the different species [3].
These enzymes catalyze the breakdown of tissue proteins and peptides. They are also known as peptide hydrolases, protease, endopeptidases and proteinases. Some metal ions of the proteolytic enzymes help in catalysis involved in the activity of certain venom proteases and phospholipases [10].
Non-cholinesterase enzymes, it causes hydrolysis of the ester or peptide linkage, to which an arginine residue contributes the carboxyl group. This activity was found in snake, crotalid, viperid and some sea snake venoms [10]. Several arginine ester hydrolases have been isolated from the venoms of different snake species. These enzymes eventually showed fibrinogenolytic, caseinolytic, bradykinin releasing or edema-inducing activities. Most of them are serine proteases [11].
Snake venom thrombin-like enzymes (SVTLEs) constitute the major portion (10–24%) of snake venom and these are the second most abundant enzymes present in the crude venom. These enzymes are glycoprotein in nature, and act as defibrinating anticoagulants in vivo, whereas in vitro they clot plasma, heparinised plasma and purified fibrinogen. It used as therapeutic agent for the treatment of various diseases such as congestive heart failure, ischemic stroke, thrombotic disorders. Thrombin like enzymes such as crotalase, agkistrodon, ancrod and batroxobin can be purified from different snake venoms [12].
Collagenase enzymes are proteinase in nature that digests collagen and mesenteric collagen fibers [13]. Collagenase are also compounds of snake venoms, may induce disruption of retinal veins that, in turn, result in retinal hemorrhage. Collagenase could as drug leading to the development of new treatments due to its proteolytic properties in their pathophysiology.
hyaluronidase beyond its role as a spreading factor venom it deserves to be explored as a therapeutic target for inhibiting the systemic distribution of venom bite. It acts upon connective tissues and decreases their viscosity, catalyzes the cleavage of internal glycoside bonds. Hyaluronidase enzyme has been found to be ubiquitously distributed in snake venoms. Hyaluronidase enzyme by itself is non-toxic and has long been known as ‘spreading factor’. The breakdown in the hyaluronic barrier allows some other fractions of venom to penetrate the organ tissues [2].
Phospholipases are enzymes that hydrolyse glycerophospholipids. It catalyzes the calcium dependent hydrolysis of the 2-acyl ester bond thereby producing free fatty acids and lysophospho lipid. Neurotoxic phospholipases A2 (PLA2s) very large superfamily of enzymes composed of 16 groups within six major types. PLA2s can bind to and hydrolyse membrane phospholipids of the motor nerve terminal to cause degeneration of the nerve terminal and skeletal muscle. PLA2 can also cause hydrolysis of membrane phospholipids, and liberation of some bioactive products [14]. The biotechnological effectively of PLA2 inhibitors may support the therapeutic potential with antiophidian activity.
Snake poisonous venom phosphodiesterase is a zinc metalloenzyme that share a number of mechanistic features with the nucleotidyl transferases. Zinc of this enzyme is activated by magnesium, and catalyze α-β phosphoryl bond cleavage. Phosphodiesterase releases 5-mononucleotide chain act as an exonucleotidase, thereby affecting DNA and RNA functions [15].
Snake acetylcholinesterase in general is found in cobra and sea snake but absent in viperid and crotalid venoms. It plays a role in cholinergic transmission which located at the neuro-muscular junction of vertebrates.
Some of snake venom components which have spurred the development of novel pharmaceutical compounds. Snake venom are investigated for the treatment of many diseases as cancer, hypertension, and thrombosis. Venoms of rattlesnakes and other crotalids produce alterations in resistance of blood vessels, changes in blood cells and coagulation and changes in cardiac and pulmonary dynamics. Also it may cause alterations in nervous system and respiratory system [16, 17, 18, 19, 20]. The potency of venom and its effect on human depend on the type and amount of venom injected and the site where it is deposited. Different other parameters and therapeutic derived such as hypotension and nerve shock and fall in blood pressure and varying degree of shock followed by a decrease in heamatocrit values are associated with snake venom [21, 22, 23].
Snake venoms are a cocktail of potent compounds which specifically and avidly target numerous essential molecules with high efficacy. The individual effects of all venom toxins integrate into lethal dysfunctions of almost any organ system. Such toxin mimetic may help in influencing a specific body function pharmaceutically for the sake of man’s health. Such snake toxin-derived mimetic are in clinical use, trials, or consideration for further pharmaceutical exploitation, especially in the fields of hemostasis, thrombosis, coagulation, and metastasis. Snake venom has great potential use as a medicine, because of all the compounds it contains, and their specific actions. Two analgesics derive from cobra venom; Cobroxin is used like morphine to block nerve transmission, and Nyloxin reduces severe arthritis pain [24]. Arvin compound from
Given that snake venom contains many biologically active ingredients, some may be useful to treat disease [25].
Phospholipases type A2 (PLA2s) from the Tunisian vipers
Serotherapy using antivenom is a common current treatment, both adaptive immunity and serotherapy are specific to the type of snake; venom with identical physiological action do not cross-neutralize [31, 32].
Hepatocellular carcinoma (HCC) represents up to 90% of all liver malignancies. Recently, the World Health Organization (WHO) reported that HCC is the fifth most common tumor worldwide, and the second most common cause of cancer-associated deaths. For the majority of advanced HCC cases, curative treatments are not possible, and the prognosis is dismal because of underlying cirrhosis as well as poor tumor response to standard chemotherapy. For patients with advanced HCC, the only approved molecular targeted therapy is sorafenib (SOR), the first orally active multi-kinase inhibitor. It provides only temporary therapeutic efficacy by increasing the survival rate by approximately 3 months [33]. Besides, a great inter-individual variation in the pharmacokinetics of SOR, due to systemic overexposure, has contributed to its toxicity [34, 35]. Therapeutic approaches to identify and develop novel compounds such as snake venom components are urgent to have potential ability for cancer treatment [36]. Moreover, better finding alternative natural safe, and better ways to treat cancer with less toxicity and deteriorated effect on normal cells is highly desirable [37].
The combining snake venoms (SVs) could synergistically enhance the antiproliferative effects at low doses on liver cancer cells (HepG2). In such Research the gene expression for apoptotic, inflammatory, antioxidant and cell cycle regulator was determined [38].
Varies compounds from venomous animals such as spiders, scorpions, snakes, caterpillars, centipedes, wasp, bees, toads, ants, and frogs have largely shown biotechnological and pharmacological applications against many diseases including cancer [39, 40, 41, 42]. Venoms obtained from snakes were reported to exhibit a cytotoxic effect against tumor cells [26]. This potency is due to inhibiting cell proliferation, promoting cell death through activating the apoptotic mechanisms [43, 44]. Meanwhile snake venom increased cytochrome-c production, modulating the expression levels of proteins that controlling the cell cycle, and treat triggering damages in the cell membranes [45, 46, 47].
The complex mixtures of snake venom, L-amino acid oxidase (LAAO) are a effect as anticancer therapeutic activity and through the induction of oxidative stress in cancer cells [48]. L-amino acid oxidase (LAAO) has been reported to exhibit a potent anti-tumor activity to different cancer cell lines including [49]. LAAO can selectively bind to the cancer cell surface at specific phospholipid compositions to deliver the hydrogen peroxide [47, 48, 49, 50]. LAAO mediates its cytotoxicity to the cell surface and produces H2O2 [49, 51, 52]. Moreover studies are confirmed this safer effect on animal models [38]. In terms of cytotoxicity, combined administration of LAAO with SOR has reduced the cell death on normal liver cells THLE-2 as compared to a single administration [38]. On the other hand the administration of LAAO and SV alone or in combination with SOR has significantly induced cell death and apoptosis in HepG2 cells as compared to control untreated cells [53]. Additionally, [54] showed that the LAAO isolated from
Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease in which the immune system primarily attacks healthy tissue of synovial joints (NIH). The disease affects between 0.5–1.0% of the developed world population, and is a significant cause of disability [56]. The primary characteristic of RA is the progressive destruction and inflammation of synovial joints, most commonly in metacarpophalangeal, proximal interphalangeal, metatarsophalangeal, wrist, and knee joints. Articular manifestations include symmetric joint swelling, tenderness, stiffness, and motion impairment, and general symptoms such as fevers, fatigue, weight loss, and discomfort are also common [57].
Snake venom has been used for treatment of rheumatoid arthritis and pain management. Venom from the families
A study found that while the general health status of RA patients in Norway improved between the years of 1994 and 2001, alleviation of pain remained the highest priority in both cohorts [59]. In another study, 88% of participants selected pain as their top priority for improvement during a year of treatment [60]. Pain scores are also disproportionately greater in women, minorities, and those with lesser levels of education, and pain is a top contributor to emotional health in RA patients [61, 62].
One of the main treatments for pain in RA patients is the administration of disease modifying antirheumatic drugs (DMARDs), which act peripherally to reduce the inflammatory response and the pain associated with it. Additionally, non-steroidal anti-inflammatory drugs (NSAIDs) such as ibuprofen and naproxen are often suggested to patients to manage their pain. These medications can be coupled with over the counter medications such as acetaminophen to further alleviate pain. When the combination of NSAID and acetaminophen administration has failed to provide relief, weak opioids are considered [63]. Therapies for RA have generally shifted focus from symptom management to the treatment of underlying inflammation that causes the symptoms [64]. Biologic disease modifying drugs are act to reduce immune responses in the body such as TNF inhibitors are used to block tumor necrosis factor (a proinflammatory cytokine) activity. Similarly, Abatacept prevents the overactivity of T cells, and Tocilluzumab inhibits the activity of another proinflammatory protein, IL-6 [65, 66].
Mechanical and thermal hyperalgesia have been found to be suppressed in several murine models with the administration of snake venom. Inflammation can also affect central pain processing, so a decrease in inflammation with snake venom could positively affect central pain and sensitization as well. The effects of snake venom from elapids and vipers on cholinergic and opioidergic mechanisms of pain are arguably the most promising relevant to treating rheumatoid arthritis. In one study, snake venom acting on cholinergic receptors to produce analgesia was found to be just as effective as morphine, with a longer lasting effect [67]. A handful of studies have utilized venom from elapids, particularly the species
Produced similar results using cobratoxin, a neurotoxin from a
Compared the effects of cobratoxin from
The use of tumor necrosis factor (TNF) blockers, a more recent therapeutic option for RA, provides a correlation between the cytokine TNF-α and bone erosion. Several studies have found that the five TNF blockers that are currently in use have all been correlated with continued inhibition of bone erosion [71]. The positive effect of TNF inhibitors provides evidence that a decrease in the cytokine TNF-α could have beneficial effects on reducing not only initial inflammatory pain but also pain induced by bone erosion and other structural changes. Additionally, the anti arthritic and anti inflammatory activity of NN-32, a cytotoxic protein from Indian spectacle cobra snake
The anti-cancer potential of snake venom depend on its protein peptides and enzymes which bind to cancer cell membranes, affecting the migration and proliferation of these cells [78].
Cancer is characterized by uncontrolled cell division, cell transformation, and escape of apoptosis, invasion, angiogenesis and metastasis. Induction of apoptosis is the most important mechanism of many anticancer agents. Snake integrins are important in cell adhesion, cell migration, tissue organization, cell growth, hemostasis and inflammatory responses, so they are in the study for the development of drugs for the treatment of cancer [53]. The induction of the apoptosis manifests the control on the tumor size and number of tumor cells hence establishing the application of apoptosis inducers as vital components in the treatment of cancer [55].
Isolation and purification of L-amino acid oxidases (LAAOs) from
The extraction of specific protein Okinawa Habu apoxin protein-1 (OHAP-1) from Okinawa Habu venom studied for its toxic effects [83]. In this study, OHAP-1 could induce apoptosis in some glioma cell. Also the apoptotic effect of OHAP-1 on malignant glioma cells could be through the generation of intracellular ROS and p53 protein expression. Antitumor activity using snake venom (
Snakes venoms were assayed in order to investigate their antimicrobial activities giving promising results [88]. Since 1930s, cobra venom has been used to treat various diseases like asthma, polio, multiple sclerosis, rheumatism, severe pain and trigeminal neuralgia. Among antimicrobial components that have been isolated from snake venom are (i) L-amino acid oxidase (LAAO), and (ii) phospholipase A2 (PLA2) [89]. The LAAO antibacterial action appears to result from hydrogen peroxide generated by the oxidative action of the enzymes, as the effect is abolished in the presence of hydrogen peroxide scavengers such as catalase [10, 90, 91, 92, 93]. Also antimicrobial peptides including cathelicidins, nerve growth factor and omwaprin have been isolated from various venomous snake species [94, 95, 96]. The antibacterial effects of cobra venom LAAO were affected against strains including
Electron microscopic assessments of both Gram-positive and Gram-negative bacterial strains suggested that the H2O2 produced by LAO induced bacterial membrane rupture and consequently loss of cytoplasmatic content [100, 101]. Akbu-LAAO an L-amino acid oxidase isolated from the venom of
The most mode of action involved in the bactericidal activity of LAAOs is that H2O2 causes oxidative stress in the target cell, triggering disorganization of the plasma membrane and cytoplasm and consequent cell death Table 2 [103, 104].
Snake species | Antibacterial component | Effective against |
---|---|---|
BmLAAO | Gram positive and negative bacteria | |
King cobra L-amino acid oxidase (Oh-LAAO) | Gram positive and negative bacteria | |
Balt-LAAO-I | ||
DRS-LAAO | ||
King cobra venom | LAAO | |
Bp-LAAO | Not specific | |
BsLAAO | ||
LAAO | ||
Casca LAAO | ( | |
CdcLAAO | ||
LAAO | Gram-negative and Gram-positive bacteria | |
Akbu-LAAO | ||
TM-LAO | ||
TJ-LAO | ||
BmarLAAO | ||
LAAO | ||
LAAO | ||
B. leucurus | BleuLAAO | S. aureus |
Anti-bacterial profile of various snake venom LAAOs [88].
Phospholipase has antimicrobial activity against
Snake species | Antibacterial component | Effective against |
---|---|---|
BFPA | ||
Agkistrodon spp | AgkTx-II | |
EcTx-I | ||
VBBPLA2 | ||
PLA2 myotoxins | ||
PnPLA2 |
Antibacterial profile of various snake venom Phospholipae A2s [88].
Peptides are have a critical defense against all kinds of microorganisms, bacteria, fungi, and viruses. Peptides play an important role in the bactericidal effect. Antimicrobial peptides can be divided into four structural groups known as α-helical, β-sheet, α-hairpin, and extended peptides [107].
Cathelicidin-BF found in the venom of the snake
Cathelicidin-BF is active against Salmonella infected-mice and it showed strong antibacterial activity against various bacteria [110]. Cathelicidin from the venom of
Snake venoms are the complex mixtures of several biologically active proteins, peptides, enzymes, and organic and inorganic compounds.
Snake venoms are very important agents for many types of diseases as well as antimicrobial, anti-inflammation, anti-rheumatoid and cancer therapy. Snake venoms acts by inhibiting cell proliferation and promoting cell death by different means: induction of apoptosis in cancer cell, increasing Ca2+ influx; inducing cytochrome C release; decreasing or increasing the expression of proteins that control cell cycle; leading to damage of cell membranes. Snake venoms contain many components that act on the peripheral nervous system for killing or immobilizing prey. All the above mentioned attracted our attention to develop of a new drugs from snake venoms will be useful as therapeutic agents of many diseases.
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\n\nOver the years we have learned what is important. What makes a difference to the researchers that work with us, what they value. Something that is very high not only on their lists, but our own, is the quality of the published content.
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\n\nYOUR WORK, YOUR COPYRIGHT
\n\nThe utilization of CC licenses allow researchers to retain copyright to their work. Researchers are free to use, adapt and share all content they publish with us. You will never have to pay permission fees to reuse a part of an experiment that you worked so hard to complete and are free to build upon your own research and the research of others. The Edited Volume helps bring together research from all over the world and compiles that research into one book - accessible for all. The research presented in chapter one can inspire the author of chapter three to take his or her research to the next level. It is about sharing ideas, insights and knowledge.
\n\nCan collaboration be inspired by a publishing format? At IntechOpen, the answer is yes. The way the research is published, the way it is accessed, it’s all part of our mission to help academics make a greater impact by giving readers free access to all published work.
\n\nOur Open Access book collection includes:
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\n\n107,564 INTERNATIONAL AUTHORS AND ACADEMIC EDITORS
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\n\nPUBLISHING PROCESS STEPS
\n\nSee a complete overview of all publishing process steps and descriptions here.
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\n\nTo view current Open Access book projects that are Open for Submissions visit us here.
\n\nNot sure if this is the right publishing option for you? Feel free to contact us at book.department@intechopen.com.
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. He has contributed in stochastic estimation of control area especially, in the Multiple Target Tracking and Interactive Multiple Model (IMM) research, Ball & Beam Control Problem, Robotics, Levitation Control. He has contributed in developing Algorithms for Fingerprint Matching, Computer Vision and Face Recognition. He has been supervising Pattern Recognition, Formal Languages and Distributed Processing projects for several years. He has reviewed many books on Management, Computer Science. Currently, he is an active and permanent reviewer for many international conferences and symposia and the program committee member for many international conferences.\nIn teaching he has taught the core computer science subjects like, Digital Design, Real Time Embedded System Programming, Operating Systems, Software Engineering, Data Structures, Databases, Compiler Construction. 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Finally, these organizations continuously review and implement effective quality systems following the rigorous ISO 9000/TS16949 series of standards and most automobile companies have developed in-house procedures and software for the supplier selection process.",book:{id:"7454",slug:"industrial-engineering",title:"Industrial Engineering",fullTitle:"Industrial Engineering"},signatures:"Lokpriya Gaikwad and Vivek Sunnapwar",authors:[{id:"246830",title:"Prof.",name:"Lokpriya Mohanrao",middleName:null,surname:"Gaikwad",slug:"lokpriya-mohanrao-gaikwad",fullName:"Lokpriya Mohanrao Gaikwad"},{id:"251857",title:"Dr.",name:"Vivek K.",middleName:null,surname:"Sunnapwar",slug:"vivek-k.-sunnapwar",fullName:"Vivek K. 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It provides a novel ALIZA Canvas and ALIZA Process supported by a comprehensive ALIZA Toolset. This output is derived from observed, tangible deficiencies in contemporary functional communications in manufacturing. This study proposes an innovative approach with robust methodologies for strategic alignment of the technical and business components in manufacturing. The requirement for a supplementary educational infrastructure, to address the pronounced educational shortcomings and knowledge gaps in the transition to Industry 4.0 is outlined. An explanation is provided of how E-Cubers (our own educational organization) will design, develop, and deliver educational programmes on Topics relevant to achieving Industry 4.0 Equipment Engineering Excellence. It defines and tests the novel concept of the E-Cubers Eight Ps; encompassing prioritized problem solving, via portfolios and projects, through peer collaboration within a defined technology playground with emphasis on learning and playing with passion. The E-Cubers Eight Ps is combined with The E-Cubers Library to deliver a truly comprehensive specialist, national learning framework. This holistic approach will ultimately enable Ireland to lead the way in Industry 4.0 by doing what we do best “ag spraoi agus ag imirt” (Gaelic – playing by having fun and competing).",book:{id:"7436",slug:"new-trends-in-industrial-automation",title:"New Trends in Industrial Automation",fullTitle:"New Trends in Industrial Automation"},signatures:"Shane Loughlin",authors:null}],onlineFirstChaptersFilter:{topicId:"119",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:31,numberOfPublishedChapters:314,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:11,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:105,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:18,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:14,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:23,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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Among them are those associated with pollution, resource extraction and overexploitation, loss of biodiversity, soil degradation, disorderly land occupation and planning, and many others. These anthropic effects could potentially be caused by any inadequate management of the environment. However, ecosystems have a resilience that makes them react to disturbances which mitigate the negative effects. It is critical to understand how ecosystems, natural and anthropized, including urban environments, respond to actions that have a negative influence and how they are managed. It is also important to establish when the limits marked by the resilience and the breaking point are achieved and when no return is possible. The main focus for the chapters is to cover the subjects such as understanding how the environment resilience works, the mechanisms involved, and how to manage them in order to improve our interactions with the environment and promote the use of adequate management practices such as those outlined in the United Nations’ Sustainable Development Goals.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/39.jpg",keywords:"Anthropic effects, Overexploitation, Biodiversity loss, Degradation, Inadequate Management, SDGs adequate practices"},{id:"38",title:"Pollution",scope:"\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",keywords:"Human activity, Pollutants, Reduced risks, Population growth, Waste disposal, Remediation, Clean environment"},{id:"41",title:"Water Science",scope:"