Dr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
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Seeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\\n\\n
Over these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\\n\\n
We are excited about the present, and we look forward to sharing many more successes in the future.
\\n\\n
Thank you all for being part of the journey. 5,000 times thank you!
\\n\\n
Now with 5,000 titles available Open Access, which one will you read next?
Preparation of Space Experiments edited by international leading expert Dr. Vladimir Pletser, Director of Space Training Operations at Blue Abyss is the 5,000th Open Access book published by IntechOpen and our milestone publication!
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"This book presents some of the current trends in space microgravity research. The eleven chapters introduce various facets of space research in physical sciences, human physiology and technology developed using the microgravity environment not only to improve our fundamental understanding in these domains but also to adapt this new knowledge for application on earth." says the editor. Listen what else Dr. Pletser has to say...
\n\n\n\n
Dr. Pletser’s experience includes 30 years of working with the European Space Agency as a Senior Physicist/Engineer and coordinating their parabolic flight campaigns, and he is the Guinness World Record holder for the most number of aircraft flown (12) in parabolas, personally logging more than 7,300 parabolas.
\n\n
Seeing the 5,000th book published makes us at the same time proud, happy, humble, and grateful. This is a great opportunity to stop and celebrate what we have done so far, but is also an opportunity to engage even more, grow, and succeed. It wouldn't be possible to get here without the synergy of team members’ hard work and authors and editors who devote time and their expertise into Open Access book publishing with us.
\n\n
Over these years, we have gone from pioneering the scientific Open Access book publishing field to being the world’s largest Open Access book publisher. Nonetheless, our vision has remained the same: to meet the challenges of making relevant knowledge available to the worldwide community under the Open Access model.
\n\n
We are excited about the present, and we look forward to sharing many more successes in the future.
\n\n
Thank you all for being part of the journey. 5,000 times thank you!
\n\n
Now with 5,000 titles available Open Access, which one will you read next?
\n'}],latestNews:[{slug:"webinar-introduction-to-open-science-wednesday-18-may-1-pm-cest-20220518",title:"Webinar: Introduction to Open Science | Wednesday 18 May, 1 PM CEST"},{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"}]},book:{item:{type:"book",id:"1861",leadTitle:null,fullTitle:"Wavelet Transforms and Their Recent Applications in Biology and Geoscience",title:"Wavelet Transforms and Their Recent Applications in Biology and Geoscience",subtitle:null,reviewType:"peer-reviewed",abstract:"This book reports on recent applications in biology and geoscience. Among them we mention the application of wavelet transforms in the treatment of EEG signals, the dimensionality reduction of the gait recognition framework, the biometric identification and verification. The book also contains applications of the wavelet transforms in the analysis of data collected from sport and breast cancer. The denoting procedure is analyzed within wavelet transform and applied on data coming from real world applications. The book ends with two important applications of the wavelet transforms in geoscience.",isbn:null,printIsbn:"978-953-51-0212-0",pdfIsbn:"978-953-51-4970-5",doi:"10.5772/2286",price:139,priceEur:155,priceUsd:179,slug:"wavelet-transforms-and-their-recent-applications-in-biology-and-geoscience",numberOfPages:312,isOpenForSubmission:!1,isInWos:1,isInBkci:!1,hash:"17f3d0e20293bdad1d8f4c760e6826b3",bookSignature:"Dumitru Baleanu",publishedDate:"March 2nd 2012",coverURL:"https://cdn.intechopen.com/books/images_new/1861.jpg",numberOfDownloads:40155,numberOfWosCitations:13,numberOfCrossrefCitations:36,numberOfCrossrefCitationsByBook:6,numberOfDimensionsCitations:50,numberOfDimensionsCitationsByBook:9,hasAltmetrics:0,numberOfTotalCitations:99,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"May 10th 2011",dateEndSecondStepPublish:"June 7th 2011",dateEndThirdStepPublish:"October 12th 2011",dateEndFourthStepPublish:"November 11th 2011",dateEndFifthStepPublish:"March 10th 2012",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7,10",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"105623",title:"Dr.",name:"Dumitru",middleName:null,surname:"Baleanu",slug:"dumitru-baleanu",fullName:"Dumitru Baleanu",profilePictureURL:"https://mts.intechopen.com/storage/users/105623/images/system/105623.jpg",biography:"Dumitru Baleanu received a B.Sc. degree in Physics from the University of Craiova, Romania, in 1988, an M.Sc. degree from the University of Bucharest, Romania, in 1989, and a Ph.D. degree from the Institute of Atomic Physics, Romania, in 1996. He is Professor at the Institute of Space Sciences, Romania, and since 2000 he is visiting staff member at Cankaya University, Turkey. He published 500 papers in journals indexed in SCI. He is a co-editor of five books published by Springer. He is coauthor of three books published by Elsevier and World Scientific. He is an editorial board member of six ISI journals and is on the 2015 Highly Cited Researcher list in mathematics. His Hirsch index is 33.",institutionString:"Cankaya University",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"4",institution:{name:"Çankaya University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1237",title:"Theoretical Physics",slug:"theoretical-physics"}],chapters:[{id:"30721",title:"Wavelet Transform for the Analysis of EEG Signals in Patients with Oral Communications Problems",doi:"10.5772/37358",slug:"analysis-of-eeg-signals-in-patients-with-oral-communication-problems-using-wavelet-transform",totalDownloads:2411,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:null,signatures:"Maria Viqueira, Begona García Zapirain, Amaia Mendez Zorrilla and Ibon 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\r\n\tThe book will aim to examine the Kalman Filter (KF), also known as the Kalman Bucy Filter (KBF), from the standpoint of its engineering implementation. The intended purpose of the book will be to extend the circle of users of the Kalman filter by considering it not as a means of theoretical analysis, but rather as a powerful tool for the design of a technical system. The editor accumulated experience of using suboptimal KF in various aerospace applications and would wish to share it with the pool of potential users and like-minded specialists. Instead of the formal programming of the recursive KF equations some simple and robust sub-optimal forms are proposed. For example, developed by the editor, suboptimal (KBF), with bounded grows of memory (FBGM) and its steady-state form- the time-invariant filter with constant coefficients is aimed to be considered. This allows the developer to use the KBF not only for system state estimation but for control as well. Proceeding in this way developer can be guaranteed the filter stability and robustness in many practically uncertain situations when the statistic characteristics of system disturbances and measured errors are not entirely known. A guaranteed approach with using an equivalent white noise is also aimed to be considered. Some representative examples from typical aerospace systems (the editor’s main professional field) are intended to be presented. Summarizing the above, it can be emphasized that when implementing the KF it is always useful to replace the art of programming with the experience of designing conventional robust systems having an idealistic estimate of maximum (best) of achievable performance. This would prevent the system's real-time computer from many possible situations with “empty “computations and even to the divergence of the computational process. It can also show that the filter is not a magic mill and cannot achieve the desired performance if it cannot be achieved in principle, better that it can be “promised” by the KF quadratic criterion minimum, or if some state vector components are not observable and controllable.
",isbn:"978-1-80356-576-7",printIsbn:"978-1-80356-575-0",pdfIsbn:"978-1-80356-577-4",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,hash:"4c3e68adcaeaa44f9fbfe9bb19bdd55b",bookSignature:"Dr. Yuri Kim",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11504.jpg",keywords:"Separation Theorem, Extended Kalman Filter, Covariance Matrix, Riccati Equation, FBGM, Analytical Implementation Forms, Physical Implementation Forms, Steady State Filter, Inertial Navigation System, Global Positioning System, Controllability, Multisensory Navigation",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 15th 2022",dateEndSecondStepPublish:"April 12th 2022",dateEndThirdStepPublish:"June 11th 2022",dateEndFourthStepPublish:"August 30th 2022",dateEndFifthStepPublish:"October 29th 2022",remainingDaysToSecondStep:"a month",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Prof. Y.V. Kim is a Doctor of Technical Science, having a broad and wealthy international scientific, engineering, and teaching experience, obtained in the former USSR, Israel, and Canada. He has many scientific publications and implemented inventions dedicated to Aerospace GN&C.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"316140",title:"Dr.",name:"Yuri",middleName:null,surname:"Kim",slug:"yuri-kim",fullName:"Yuri Kim",profilePictureURL:"https://mts.intechopen.com/storage/users/316140/images/system/316140.jpg",biography:"Yuri Kim\n24 Buttenut, Gatineau, QC, Canada\nTel : 1-(514)- 466-1033, e-mail: yurikim@hotmail.ca\n\nHIGHLIGHTS OF QUALIFICATIONS:\n\nExperienced scientist, engineer and manager with internationally recognized achievements in area of Aerospace Avionics, (GN&C); Analysis, design (HW&SW), integration, testing and operation for various aerospace platforms and missions. \n\nGained a broad experience in preparation of technical documents for Joint (Industry-Customer) State Commissions for the acceptance (commissioning) of Aerospace Avionics, Navigation and Special application experimental equipment for further serial production, and operational support. Last works have been dedicated to R&D projects developing new Satellite Navigation Control Technology and customer support of Canadian satellites Control system design.\n\n\nACADEMIC DEGREES:\n\n 1991 *Doctor of Technical Science Diploma in Aerospace Vehicles Guidance \n Navigation and Control \n Scientific Council of State Institute of Automatic Systems, Ministry of Aviation\n Industry of USSR, Moscow\n (Recognized by Canadian Professional Counsel of Engineers) \n1982 * Senior Scientific Fellow Diploma in Gyroscopes and Navigation systems \n Capital Certification Commission of Scientists, Ministry of High Education of\n USSR, Moscow.\n (Recognized by Canadian Professional Counsel of Engineers)\n1974 * Candidate of Technical Science Diploma in Aerospace Navigation\n and Control Systems (Accredited as Ph.D by York University, Toronto.)\n Scientific Council of Moscow Aviation Institute, Moscow.\n1970 * Engineer Electromechanic Diploma in Gyro and Navigation systems,\n Faculty of Flight Apparatuses Control Systems, Moscow Aviation Institute, \n Moscow (Accredited as between Masters Degree and Bachelor Degree by\n York University, Toronto).\n1965 * Radio and TV Systems Technician Certificate, Dnepropetrovsk Technical School \n of preparation of technical specialists for Soviet Army, Military Aviation and \n Navy.\n\nMILITARY EDUCATION:\n\n1970 * Engineer in ballistic rocket control system, Military Faculty of MAI, last rank senior engineer-lieutenant (in reserve)\n\n\n\nEMPLOYMENT HISTORY:\nA. GOVERNMENT\n\nAt present - Canadian Space Agency, Space Science and Technology Division, David Florida Laboratory\n\n Senior Aerospace System engineer \n\n° Performing, developing and supporting phases of design, testing, commissioning and \n operation for space vehicle orbit and attitude control systems, in particular: Tecsas, Scope, \n J2Sat, Small satellite, M3Msat, Cassiopea, Neossat, RCM, PCW\n\n° Reviewing and commenting on Attitude Control systems design documentations, related to \n all phases of system development commissioning and operation\n \n° Supporting Aerospace Industry R&D projects funding by CSA (STDP) as Scientific\n Authority, in particular: Microwheel (Dynacon), LOCOOS (NGC), PCW (Bristol)\n\n° Providing expertise on new initiatives for Space Exploration and Utilization regarding \n Attitude and Orbital Control and possible development of Canadian space launcher\n\n° Developing basic mathematical (Simulink/Matlab) simulator for developing the \n requirements and expected performance of AODCS for new space vehicles\n\n° Developing new basic technology (based on Kalman Filter) for satellite attitude\n determination and sensor calibration, developing of FF test-bed equipment and GPS \n navigation in environment of CSA laboratory, developing of methods of ACS sensors\n calibration, measuring and compensation of satellite residual magnetic moment, experimental determination of satellite inertia matrix during ACS integration tests\n\n° Interacting with Space Industry and Universities in the problems, related to development of \n new methods and systems for space vehicle attitude and orbit determination and control\n \n° Sharing with International Aerospace community CSA achievements and experience in\n development of new technologies and methods for space vehicle attitude and orbit \n determination and control through publications, presentations and participation in scientific\n conferences, meetings and symposiums as well as maintaining an awareness about new \n technological advancements\n \n° Providing professional training for students and post. Graduates in the area of Orbital and\n Attitude Dynamic and Control\n\nB. INDUSTRIAL\n\nSept. 1998 – Feb. 1999 – Olympia Engineering Ltd. (Toronto)\n\nResearch and Development Engineer\n\n•\tDevelopment of measuring instrument for measuring remote measuring of micro- deformations of machinery (milling machine) equipment\n•\tResearch and testing of differential GPS survey equipment and antennas in environment of industrial facility for developing a new remote method for the measuring of machinery micro-deformations\n\n\n\n\nFeb.1999 – Jun.2002 – Saskatoon Engineering Division of Calian Company, \n Radarsat-1 Operation Team (CSA, Montreal)\n\nAttitude Control System Analyst\n\n•\tWorking as RADARSAT-1 Attitude Control System Analyst performing day-to-day operation TLM data analysis; reporting, monitoring and solving ACS flight anomaly problems, maintaining ACS software and performance \n•\tAuthor of many reports (see attached list of publications), devoted to solving of Radarsat-1 non-benign Safe Hold Mode problem, Momentum Wheel failure problems and improvement of the performance of attitude determination method with Magnetometer and Sun Sensor (back up, ADM3 mode for the case of potential failure of Horizon Scanner).\n•\tPreparation and implementation of the solution for RADARSAT-1 operation without failed Momentum Wheels, that saved the satellite mission after the wheel failures\n(This work was prolonged after in CSA and awarded by the Canadian Government Award for the invention used by the Government)\n•\tDesign and implementation of new dynamic simulators (based on Simulink\ntoolbox) for Radarsat-1 ACS for operation support\n•\tPreparation for operation of new Canadian satellites Scisat and RADARSAT-2 \n\n\n\nJan. 1994 – Sep. 1997 – Israel Aviation Industry (IAI factories: TASHAN, LAHAV)\n\nAvionics system engineer\n\n•\tResearch and preliminary design of the Special Data Fusion System for a fighter-interceptor\n•\tIntegration of Inertial Navigation System with Global Position System into Upgraded Avionics Suit and installation in aircraft cockpit for A/C – trainer T-38\n\nNov. 1977 – Apr. 1993 – Moscow Research and Design Institute of Electromechanic and Automatic (formerly P/B: M5537, presently “Aviapribor” Corporation)\n\n \nHead of Division (R&D in Pilot-Navigation Systems)\n\n•\tLeadership of the Division, performing planning, financial and methodological duties, related to this position, reporting to the R&D deputy director of the Institute\n•\tResponsibility for Pilot-Navigation System integration, interaction, tests and transferring for serial production and operational support\n•\tInitiation and methodical leadership of innovative research and development projects\n•\tReviewing, commenting and implementation of Technical standards and Navigation norms\nas well as sharing progressive methods and results within Aerospace organizations within former USSR\n \n Head of Department (INS and Flight Management System SW Development)\n\n•\tLeadership and performing of duties of Head of Department \n•\tResponsibility for the prospective research and preliminary design of the Inertial Navigation Systems (INS) and Flight Management Systems (FMS)\n•\tDesign of the INS and FMS algorithms and simulation of expected performance\n•\tDevelopment of INS/FMS flight code\n•\tDevelopment of test procedures and simulators for FMS, and pilot nav.complexis for aircrafts \n•\tResponsibility for system performance analysis in the ground and flight tests\n\n Head of Sector (System Flight Test data analysis) \n\n•\tLeadership of the Sector\n•\tDevelopment of ground and flight test simulation procedures and requirements for test equipment and simulators, for flight test aircraft measuring equipment, installation and recorded data processing\n•\tDesign of Estimation and Identification algorithms for ground and flight data processing\n•\tTest data analysis, preparation of test results analysis reports and conclusions\n\n Senior Scientific Fellow\n\n•\tResearch, development and principal design of the special Suboptimal Kalman Filter for the fusion of data of various navigation sensors for aviation and space platforms\n•\tDevelopment of new Guidance and Navigation methods for aviation and space platforms\n•\tAnalysis of INS and FMS performance in ground and flight tests\n\nC. ACADEMIC \n\n1977–1993 – Moscow Aviation Institute, Moscow Institute of Instrument -\n Making, Aviation Industry Ministry Upgrade Qualification Institute\n(Part Time) Professor, Associate professor, Chairmen of State Diploma Commission,\n Member of Scientific Council\n•\tLecturer of the disciplines: Applied Oscillation, Theory (MIIM), Design of Instruments (MIIM), Integrated Navigation Systems (MUQI)\n•\tChairman of the State Diploma Commission -Gyro Instruments and Systems (MAI)\n•\tLeadership of postgraduates, participation in sessions of Scientific Council (MAI)\n•\tMethodical management of cathedra of Orientation and Navigation in MAI \n\n2009 McGill University, Montreal\n\nPart time lecturer for course (in English): Aircraft Performance, Stability and Control\n\n1970–1977 – Moscow Aviation Institute \n(Full Time) Associate Professor, Senior Researcher, Assistant Lecturer \n•\tLecturer of the courses: Spacecraft orbital mechanics and attitude determination and control, Inertial Navigation Systems, Gyro Instruments and Systems\n•\tResearch and development of suboptimal robust estimation methods for navigation data processing\n•\tResponsibility for the navigation systems laboratory\n•\tDeputy head of cathedra of Orientation and Navigation\n\nFIELDS OF THEORETICAL AND METHODOLOGIC EXPERTISE:\n \n•\tSpace vehicle Orbit and Attitude determination and control\n•\tGyro instruments and systems\n•\tRadio navigation systems\n•\tInertial Navigation systems\n•\tAirplane Navigation and Control\n•\tAnalytical mechanics \n•\tApplied oscillation theory\n•\tAutomatic control theory\n•\tStochastic estimation theory\n\nENGINEERING EXPERIENCE:\n\n•\tFlight and laboratory tests of Aerospace Avionics Equipment\n•\tDistribution of mission requirements between Aerospace vehicle subsystems, definition of functions and ICD \n•\tSpacecraft operation and performance maintenance\n•\tAvionics system (hardware and software) development and testing (autonomously and integration)\n•\tInertial navigation systems\n•\t Development of Avionics for Soviet Military aircrafts: Tu-142, Tu-95MC, An-124, An-70, A-40, Soviet Space shuttle “Buran” (responsibility for preliminary design of radio-navigation automatic landing system), \n•\tIsrael (IAI) upgrade of Avionics system for T-38 (USA Air force trainer) \n•\tOperation and modification in space Canadian Satellite RADARSAT-1 Attitude Control system\n•\tParticipation in commissioning of ACS of Canadian Satellite Scisat\n•\tDevelopment of a generic mathematical simulator for satellite AODCS analysis and simulation of expected performance for a family of Canadian new generation small satellites\n\nSCIENTIFIC EXPERIENCE:\n\n•\tTheoretical and experimental investigation in the fields of S/C Orbital and Attitude Control\n•\tKalman Filter suboptimization and robust guarantee estimation theory development: authorship of new Suboptimal Kalman Filter modification, methods of INS correction and calibration, Geomagnetic Inertial Navigation System\n•\tResearch in areas of ACS and INS sensors development, their performance improvement\n•\tVarious Avionics Systems Mathematical models development and mathematical and semi-natural simulation\n•\tCoordination of research and development projects related to Aerospace equipment performed by Universities and Industries\n•\tScientific reports and articles reviewing and editorship \n•\tMembership in Scientific Counsels and Commissions\n•\tTutorship of under-graduate, graduated and post -graduate students \n\n•\tScientific reports and inventions in the field of GN&C for aircraft and spacecraft methods development \n•\tSeveral articles dedicated to the development of new methods in estimation theory: new suboptimal Kalman Filter with limited growth of the memory, observability and factor of state vector components estimation, guaranteed ellipsoidal estimation and stochastic estimation comparison \n\nLANGUAGES:\n \n•\tEnglish, Russian, Ukrainian, 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1. Introduction
As a treatment modality driven by technology, radiation therapy (RT) has made significant advances in recent years. These advances have mostly been in areas of treatment delivery, imaging, and image fusion which has required sophisticated algorithms for calculation of dose in patients and complex machines to deliver the dose. There is always some level of discrepancies between the calculated dose and delivered dose which can arise from different sources such as: the dose calculation algorithm, beam modeling in TPS, physics data entry, beam delivery, detector resolution, and planned grid size. The purpose of this chapter is to present a review of algorithms for photon dose calculation, beam modeling in different TPSs, detector resolution and planned grid size (GS) and analyze the effect of each of them on gamma passing rate (GPR) in pre-treatment quality assurance (QA).
2. Treatment planning system (TPS) algorithms
For understanding TPS algorithms, it is required to know [1]:
The production of Megavoltage X-rays
The interaction and scattering of photons by the Compton effect
The effects of transport of charged particles near boundaries and tissue heterogeneities
By far, medical linear accelerators (linac) are the main devices used in the treatment of cancer patients producing X-rays and electrons in the clinical energy range. In the head of a linac, high energy electrons are accelerated to the near speed of light and are directed to strike a high Z target typically made of Tungsten which has also a high melting point to produce photon. The bremsstrahlung photons produced by a linac have an energy distribution from 0 to maximum energy of the electrons in the beam impinging upon the target. These photons pass through the primary collimator and other parts of the linac head such as jaws, Multi Leaf Collimator (MLC) system, etc. before reaching the patient. All these photons (primary and scattered) will contribute to photon fluence. For example, for a typical Varian linac with a flattening filter, 80–90% of primary photons are directly from the target, 3–5% from the primary collimator, 8–12% originated from the flattening filter [1, 2]. However, in modern linacs which are equipped with flattening filter free (FFF) technology, scatter photon produced in the treatment head has significantly decreased [3, 4]. Therefore, the contribution of primary and scatter photon in photon fluence for FFF is different from the flattened beam [5]. For example for a 40 × 40 cm2 field size and a 6 MV FFF beam, the calculated contribution was 84.6% for the primary source, 11.3% for the first scattered source, and 4.1% for the second scattered source [5].
In general, ionizing radiation such as photon, electron, and heavy charged particles interact with matter which depends on the energy of ionizing radiation, type of ionizing radiation, the atomic number, and density of the medium through which they travel. Photons are indirect ionizing radiation and energy deposition of the photon to the material is dominated by three interactions: Photoelectric, Compton scatter, and pair production. In the energy range from 100 Kev to 10 MeV, which is a mostly therapeutic range, the Compton process is dominant for energy absorption in soft tissues. The energy deposition of photons involves two stages: First, partial transfer of their kinetic energy to charged particles (electron, positron) when they interact with material, and second, energy deposition from these charged particles to material through excitation or ionization. The range of charged particles in the therapeutic energy range can be several centimeters so they can travel and pass-through various layers with different densities and atomic numbers in a human body. When charged particle equilibrium (CPE) is achieved, then there is a linear relationship between TERMA1 (Total energy released per unit mass) and dose, and the two steps can be included in a single calculation. However, this condition does not occur near the edge of the field or in inhomogeneity regions like at tissue interfaces, therefore, this simplification cannot be valid, and the two steps of energy deposition of the photon to medium must be more clearly distinguished [6].
The human body consists of a variety of tissues and cavities that are radiologically different from water, such as lungs, oral cavities, teeth, nasal passages, sinuses, and bones. A treatment planning system uses the electron density derived from CT images of patients to calculate dose in the patient body. Therefore, the dose distribution inside the patient body is affected by these heterogeneities. In this area, the ability of treatment planning systems to calculate dose at the interferences such as lung vs. tissue, bone vs. air cavity, etc. is crucial. Also, using CT images with 3D TPS allows us to design a plan with complex beam arrangements which require more advanced dose computation algorithms. In this section, we will present a summary review of the past and current dose calculation algorithms used in the TPS for radiotherapy.
According to the American Association of Physicists in Medicine (AAPM) Task Group 65 (TG-65, Report No.85) [6], there are four types of inhomogeneity correction algorithms:
Category.1: Linear attenuation, Ratio of tissue air ratio (RTAR), Power law (Batho).
Category.2: Equivalent TAR, Differential scatter air ratio (dSAR), Delta volume, Differential TAR, and 3D Beam subtraction method.
Category.3: Convolution (pencil beam) and Fast Fourier transformation (FFT) techniques.
Category.4: Superposition/Convolution, Monte Carlo.
2.1 Category.1
2.1.1 Linear attenuation
This is the simplest technique for computation of inhomogeneity correction factor (ICF), which does not include any information regarding electron density and the geometric treatment beam parameters such as field size [6].
ICF=%percm×inhomogeneity thicknesscmE1
2.1.2 Ratio of tissue air ratio (RTAR)
Only heterogeneity correction applied on the beam path from source to the calculation point.
ICFdr=TARd′rTARdrE2
where d and d’ are physical depth and water equivalent depth to the calculation point and r is the field size at depth d. The main weakness of this method is overcorrection when the density of the medium is less than the density of the water and under correction when the density is greater than the density of water due to compromised modeling of lateral component of the scattered photon [7].
2.1.3 Power law (Batho)
This is an empirical correction factor method for points lying within water and distal to an inhomogeneity by raising tissue-air ratios to a power that depends on density. This was first proposed by Batho in 1964 [8] and then modified by Sontag and Cunningham in 1977 [9].
ICF=TARd1rρ1−ρ2TARd2r1−ρ2E3
where d1 is depth to first slab boundary and d2 is depth to second slab boundary from the point of calculation at depth d. r is field size at depth d and ρ1 and ρ2 are densities of the medium in which the calculation point is located and relative electron density of the overlying material respectively.
The power law method underestimates the dose when density is less than one and overestimates when density is greater than one [6]. Several studies showed improvement if Tissue Maximum Ratio (TMR) is used instead of TAR [10, 11].
2.2 Category.2
2.2.1 Equivalent TAR (ETAR)
It can be considered as the first practical dose calculation method using the full CT data set for computerized treatment planning and was used in early treatment planning systems [6].
ICFdr=TARd′r∼TARdrE4
where d′ and r∼ represent the “scaled” or “effective” values of depth at interesting point (d) and field radius (r) respectively for the energy of the radiation being used. This method required excessive computer memory and calculation times; therefore, some adjustments such as the coalescing of adjacent CT slices were applied to reduce 3D calculations to appropriate 2D calculations to make it more practical for use in clinics in the 1980s.
2.2.2 Differential scatter air ratio (dSAR)
This was a 3D dose calculation in a heterogeneous media that used scatter-air ratios (SAR) to calculate the dose to a point in an inhomogeneous medium. For this purpose, a SAR table was used to determine the scatter contribution that arises from voxels within the irradiation volume [12].
2.2.3 Delta volume (DVOL)
The primary dose, an analytical first-scatter dose component, and an approximate residual multiple-scatter component were summed to calculate dose at a point in a heterogeneous medium. This method has been examined and justified for Co-60 and succeeds incorrectly calculating the dose to (a) water with a small void and, (b) homogeneous non-water medium.
dSAR and DVOL have never been implemented in clinics due to the long CPU time required to run them with no significant improvement in dose calculation accuracy compared to previously used algorithms [7].
2.2.4 Differential TAR
Kappas and Rosenwald [13] showed that applying K(θ,μ) on dSAR method results in more accurate results.
Kθμ=eμ0cosθ−μ1θb¯−bE5
where μ0 and μ1 are the linear attenuation coefficients in the water of the primary and of the first-order scattered photons arriving at a point after a deflection. b¯ is the path length en route to point (in the waterlike medium) and b is the corresponding effective path length (in the heterogeneous medium). For very large fields and depths and when the thickness of the overlying tissue is greater than 5 cm, the difference between measurement and calculation is more than 2% and less than 6% [6].
In general, categories 1 and 2 are not applicable when photon energy is greater than 6MV where scatter contribution is less important, and the effects of secondary electrons (delta rays) set in motion can result in very high local dose changes [6].
2.3 Category.3
2.3.1 Convolution techniques
This technique is a model-based algorithm which unlike correction-based algorithms uses heterogeneity effects directly to compute the dose in tissue. Kernels are used for modeling the dose distribution in media. The kernels represent the energy spread and dose deposition of secondary particles from an interaction at a given point or line which is not usually accessible through measurements but is very simple to calculate by use of Monte Carlo particle transport codes [12]. Absorbed dose is calculated based on the following equation
Absorbed Dose=energy fluence distribution⊗KE6
This means that the energy fluence distribution is convolved2 with the scatter spread kernel (K) to obtain the dose.
Energy deposition Kernel (EDK) is the energy distribution revealed to volume elements (per unit volume) in an irradiated medium, commonly water. There are three different categories for EDKs based on the geometry of the elemental beam that delivers the incident energy: A point kernel, pencil kernel, and planar kernel [7].
Point Kernel: This kernel describes the pattern of energy deposition in an infinite media around a primary photon interaction site.
Pencil Kernel: This kernel describes the energy deposition in a semi-infinite medium from a point monodirectional beam.
Planar Kernel: A planar kernel describes the energy spread from primary interactions located in a plane of an infinite broad beam.
In 1986, Mohan et al. [14] introduced a differential Pencil beam algorithm which is a good example of this category. This is the simplest and fastest algorithm for dose calculation because it only considers inhomogeneity corrections in longitudinal direction in the central beam axis and ignores lateral scatter. Therefore, it does not accurately model the distribution of secondary electrons in heterogeneous media. This limitation causes inaccurate dose calculation in heterogeneous treatment sites such as the lung, bone, or interfaces [15, 16].
2.3.2 Fast Fourier transform (FFT) convolution
This technique reduces computation time greatly because of the invariant kernel assumption for the convolution calculation. Because of this assumption, different kernels at different regions based on the density cannot be used in FFT. Several studies were conducted to circumvent invariant kernel assumptions [17, 18, 19]. In 1996, Wong et al. [20] proposed a solution to address problems related to lateral disequilibrium and penumbra in low-density regions because a water kernel was used for entire regions even in low-density regions. The lateral disequilibrium problem was solved by lateral scaling of the field size at each depth according to local effective densities to adjust the dose along the central axis in heterogeneities. This technique is based on the ETAR method, by convolving the density at the intersection site with the primary kernel for water. The resultant dose distribution is then inverse scaled according to the effective density to correct the penumbra problem which accounts for the electron transport near the field edge inside a low-density medium with or without lateral disequilibrium.
2.4 Category.4
2.4.1 Convolution-superposition algorithms
The convolution-superposition algorithm is also a model-based algorithm and has two essential parts: 1) TERMA and 2) dose spread kernel. TERMA was first introduced by Ahnesjo et al. in 1987 [21] which is analogous to the Kerma, (the kinetic energy released in medium) and has the same unit as dose. The formula for the TERMA element (T) of the convolution method is given by the following equation
Tr′=μρr→′E.Ψr→′E7
where μ/ρ is the mass attenuation coefficient and Ψ is the primary energy fluence. Then the convolution-superposition is the integration of the TERMA distribution times EDK over the entire volume. EDK is spatially variant and is deformed based on the local density environment to consider interface effects in regions of different densities. Also, to get a more accurate model of the scattering conditions, the kernels must be adjusted according to their direction and orientation at the site of interaction [22].
This method is widely used in TPS because computers are fast enough to do 3D dose calculations by using electron density data derived from CT images in a reasonable amount of time. According to AAPM report 85 (TG-65), the dose calculation accuracy of TPS algorithms should be within 2%. This goal serves as a useful benchmark to evaluate the capabilities of treatment planning algorithms to calculate the dose.
2.4.2 Anisotropic analytical algorithm
Anisotropic Analytical Algorithm (AAA) (Varian Medical System, Inc) is a kernel-based convolution-superposition method. This algorithm was first designed by Ulmer and Kaissl (2005) [23] in cylindrical coordinate and then improved by Tillikainen in 2008 [24]. The AAA dose calculation model has two main components, the configuration algorithm, and the actual dose calculation algorithm. Its configuration is based on the Monte Carlo simulations to determine basic physical parameters and match them with measured clinical beam data. The dose calculation algorithm utilizes separate models for primary photons, scattered extra-focal photons, and contamination electrons. The lateral distribution is adjusted according to the radiological distance to the calculation point for tissue heterogeneities corrections [16, 25]. For the most part, AAA is a pencil beam convolution-superposition algorithm where the pencil beam is compiled from Monte Carlo calculations and adjusted to fit measurements. In this case, two components need to be considered that contribute to final distributions; 1) longitudinal contribution of the pencil beam which is scaled according to Equivalent Length Path (EPL), and 2) contribution from the lateral extension of the pencil beam which is scaled with the density relative to water in directions normal to the pencil beam [26]. In this way, the changes in lateral transport of energy are modeled when the density varies in the irradiated object. Therefore, unlike the pencil beam algorithms, it can consider inhomogeneity correction on both longitudinal and lateral directions. However, many studies indicate the inability of AAA to accurately calculate doses at interfaces and for high atomic number materials such as bone and have shown that the deviation between AAA and measurements exceeds the goal of TG-65 [27, 28, 29, 30].
The advantage of the AAA is its relatively short calculation time and its accuracy is better than the pencil beam convolution (PBC) model [30, 31, 32].
2.4.3 Collapsed cone convolution
In 1989 Ahnesjo [33] proposed collapsed cone convolution (CCC) method. The CCC algorithm uses the analytical kernel in polar coordinates represented by a set of cones. In this way, it is assumed that all energy is released into coaxial cones of equal solid angle and, from volume elements on the cone axis is approximated to be rectilinearly transported, attenuated, and deposited in volume elements on that axis [7]. The polyenergetic kernels can be described by
hrθ=Aθe−αθr+Bθe−bθrr2E8
where Aθ, αθ, Bθ, and bθ are fitting parameters depending on the scattering angle θ and r is radial distance. The first term mainly describes the primary dose and the second term is the scatter dose fraction.
The advantage of the CCC algorithm over standard convolution algorithms is that it can reduce the computation resources. The computation time for the CCC method in heterogenous media is proportional to MN3 where M is the number of cones and N is the number of voxels along one side of the calculation volume [16]. Different TPSs use the CCC algorithm such as Pinnacle (Philips Inc., Amsterdam, Netherlands), Oncentra MasterPlan (Nucletron, Inc., Columbia, MD, USA), CMS XiO (Elekta AB, Stockholm, Sweden), RayStation (RaySearch Laboratories AB, Stockholm, Sweden), etc.
2.4.4 Monte Carlo
Monte Carlo (MC) is a principle-based algorithm that almost includes all known physical features for photon interactions inside the patient body. Many MC codes have been developed such as BEAMnrc, GEANT4, MNCP, PENELOPE, and XVMC. All of them have two main steps, first, modeling the linac head with all precise details of the target, component dimensions, geometry, locations, and material composition. The second step uses CT data to get morphological and chemical information in terms of mass density, electron density, and atomic composition, which are all required for accurate dose calculation in the tissue.
The MC has the capability of simulating all interactions, therefore it is expected to be accurate. However, its accuracy depends on correct and detailed geometry information of the linac head and the number of particle histories. This statistical uncertainty is proportional to the inverse square root of the generated event numbers [34, 35]. MC dose calculation is slow and time-consuming, so they are not yet applicable in clinics because the dose may recompute repeatedly during planning to get an optimized plan. A few vendors offer Monte Carlo methods in TPS as calculation options for the final dose calculation once the dose optimization is completed.
2.4.5 Acuros XB
Monte-Carlo (MC) dose calculation algorithm is widely considered as the golden dose calculation technique in radiation therapy; however, the calculation time of this method is still long especially where a greater number of particle histories should be used to reduce statistical noise and/or a high spatial resolution is required. An alternative method to MC is the linear Boltzmann transport equation (LBTE) method which solves LBTE refers to grid-based Boltzmann solver (GBBS). GBBS solves the LBTE through discretizing photon and electron fluences in space, energy, and angle to allow a deterministic solution of the transport of radiation through matter. Its calculation accuracy is comparable to MC, and both are convergent methods because the MC algorithm simulates an infinite number of particles, GBBS discretizes the LBTE variables into infinitely small grids, then the two methods should converge to the real solution. However, MC and GBBS have different sources of error, there is statistical noise due to simulating a finite number of particles in Monte Carlo, while most errors in GBBS methods are systematic and their main source is discretization of the solution variables in space, angle, and energy [36, 37]. An algorithm using this technique is based on Attila (Los Alamos National Laboratory, Los Alamos, NM, and Transpire Inc., Gig Harbor, WA). Attila employs linear discontinuous finite-element spatial differencing on a computational mesh consisting of arbitrary tetrahedral elements. The primary photon fluence is analytically transported through ray tracing, and the discrete ordinates method is used for angular differencing of the scattered fluence. Based on Attila, a dose calculation algorithm for external photon beams has been developed on the same methods and implemented in the Varian Eclipse external beam treatment planning system (Varian Medical Systems, Palo Alto, CA, USA) [38]. This new deterministic radiation transport algorithm is Acuros XB (AXB), and it has been well shown by several studies that the accuracy of dose calculation of AXB is more accurate than AAA and is very similar to MC dose calculations [36, 37, 38].
3. Beam Modeling of commercial treatment planning systems
In radiotherapy, the ability of TPS to do accurate dose calculation is important. This capability depends on the algorithm of TPS as discussed before and beam modeling. For beam modeling, several dosimetric parameters (e.g., PDDs, profiles, output factors) and non-dosimetric parameters such as MLC design, flattening filter, wedges etc. must be defined precisely. Then the dose calculation algorithm applies the beam model to the patient body or phantom to calculate the dose. The challenge of the beam model is becoming more and more crucial due to advanced treatment techniques such as IMRT and VMAT. In these treatment techniques, each beam consists of multiple segments or control points that are shaped with MLC. Using multiple control points provides this opportunity to deliver conformal dose to the target, however, delivering dose through small segments arises a challenge to accurately calculate the dose due to the complexity of MLC modeling in TPS. Many studies indicate the importance of accurate MLC modeling in TPS for IMRT. In 1998, LoSasso et al. [39] showed an MLC error gap of 1 mm may result 10% error in dose calculation in the sliding window IMRT technique. Cadman et al. [40] reported 12% discrepancy between calculation and measurement due to MLC leaf gap error in step-and-shoot IMRT. Because different commercial TPS have their own features for beam modeling, many guidelines have been published regarding TPS commissioning for IMRT [41, 42]. For example, TG-119 [43] based on the IMRT QA results of five institutions for a set of test cases provides a reference baseline for the accuracy of IMRT commissioning.
In Eclipse, leaf transmission factors and dosimetric leaf gaps (DLGs) are required to model the MLC. The DLG is a beam configuration parameter used to model the effects of rounded MLC leaf ends. Many research papers indicate the effects of DLG on the accuracy of dose calculation in Eclipse TPS [44, 45, 46, 47].
In RayStation, modeling of MLC is different from other commercial TPS. The MLC model requires four parameters: leaf-tip offset, leaf-tip width, average transmission factor, and tongue and groove. The leaf-tip width is used for the MLC leaf-end transmission modeling instead of using dosimetric leaf gap (DLG) or rounded leaf-tip radius, and the MLC leaf radiation transmission is modeled using average transmission factor instead of intra-leaf and inter-leaf transmission [48, 49]. According to Chen et al. tongue-and-groove has a minimal effect on IMRT dose calculation, but transmission plays a significant role in this commercial TPS [49].
4. Measurement methods for pre-treatment verification
The process of patient-specific QA usually involves applying an optimized plan using the same beam parameters as those of the patient plan and delivered in the phantom. This process can be done in a number of different ways but according to TG-218 [50], there are three common methods for performing pre-treatment QA. 1) True Composite (TC), 2) Perpendicular field-by-field (PFF), and 3) Perpendicular composite (PC).
4.1 True composite
In this method, phantom or measurement device is placed on the treatment couch and treatment plan is delivered using actual parameters such as MUs, couch, gantry, collimator angles, MLCs, and jaws positions. The phantom or measurement device has been used to integrate dose from all beams of a plan which result in a single dose image for comparison, therefore, this method is a comparison of planned dose vs. measured dose.
4.2 Perpendicular field-by-field
The gantry is fixed at zero degree and the collimator is fixed at the nominal angle in the PFF technique. Therefore, beams are always perpendicular to the phantom surface and are comparing the dose of each beam with each measured beam dose.
4.3 Perpendicular composite
This method is similar to the PFF method, but this is not a comparison of field-by-field. This is the integration dose of all perpendicular field which result in one dose image for analysis.
5. Gamma index
For the purpose of dose comparisons between calculated and measured dose gamma index have been used. Low et al. [51] developed a gamma index (γ) for the quantitative evaluation of dose distributions. This index checks dose difference and distance-to-agreement (DTA) simultaneously in a space that also includes dose, and provides quantitative value which indicates disagreement in the regions that fail the acceptance criteria. A γ comparison is performed between two dose maps: one distribution is the ‘reference dose distribution’ and the other is the ‘evaluated dose distribution’. The reference dose distribution is referred to as true distribution so it is usually measured data using devices such as ion chamber, film, diode array detector etc., and the evaluated dose distribution is analyzed for its agreement with the reference and can be the predicted TPS dose distribution. To avoid any confusion, low replaced reference and evaluated terms by measured and calculated respectively. The gamma index calculation is based on Eq. (9):
ΓrRrE=Δr2rRrEδr2+ΔD2rRrEδD2E9
where rR and rE are reference points and evaluated point respectively, δr is distance difference criterion and δD is the dose difference criterion. ΔD is dose difference which is calculated using Eq. (10):
ΔDrRrE=DErE−DRrRE10
DE and DR are the doses at a point in evaluated dose distribution and reference dose distribution respectively.
The γ is the minimum value calculated overall evaluated points:
γrR=minΓrRrE∀rEE11
Regions where γ is less than or equal to 1 corresponds to locations where the calculation meets the acceptance criteria. According to TG-218, criteria for tolerance limit is 2 mm/3% with 95% passing rate [50].
There are two types of gamma calculation which depends on how the percent dose difference (%Diff) is normalized: 1) local normalization method which %Diff is normalized to the doses at each evaluated point, 2) global normalization method which %Diff is normalized usually to the maximum dose within the reference dose distribution. Each method has its own advantages and disadvantages. For example, local gamma will exaggerate %Diff and highlighted failures in low dose regions because in low dose regions the percent dose difference between calculated and measured may exhibit a very large value which results in more failings points. However, in the global method, the dose discrepancies in the low-dose regions could be underestimated which results in a higher passing rate than the local method [52, 53].
5.1 Effect of planned grid size on gamma passing rate
Low et al. [51] presented a powerful tool for dose distribution comparisons in a continuous environment; however, clinical comparisons are usually made between two dose distributions which are sampled at different spatial resolutions. The importance of spatial resolution was first analyzed by Depuydt et al in 2001 [54]. They indicated that the pixel size of the compared image needs to be small with respect to acceptance criteria and showed that large grid spacing in the discrete dose distribution, especially in high dose gradient regions causes overestimation of gamma values. Several investigators introduced different solutions to resolve this issue [54, 55, 56]. For example, Low and Dempsey [57] showed that by decreasing grid size to 1 × 1 mm2, the error in γ reduced to less than 0.2 even in high dose gradient areas. Furthermore, Schreiner et al. [58] reported changing the resolution of the evaluated distribution (from 2.5 mm to 0.24 mm) increase the pass rate from 80.9% to 91.3%. These results are attributed to the behavior of gamma search. When the pixel size of the evaluated distribution is large compared to the reference distribution, many reference pixels would be far away from the nearest evaluated pixel which results in more failing points. Thus, the γ value for many reference pixels reflects significant spatial misalignment purely as an artifact of the coarse evaluated resolution. When the resolution of the evaluated distribution is increased to match that of the reference distribution, this spatial artifact is eliminated because each reference point has a directly corresponding pixel in the evaluated distribution. Increasing the evaluated resolution also provides each reference point with a greater range of dose values for comparison. Based on TG-218 [50], there is a rule of thumb that the resolution of the evaluated (calculated) should be no greater than 1/3 of the DTA and the straightforward solution for reducing artifact in gamma calculation is interpolation when planned grid size is greater than 1 mm (for DTA =3 mm).
6. Dosimetry equipment for pre-treatment verification
Modern radiotherapy techniques like IMRT and VMAT are highly complex modalities due to MLCs motions, gantry rotation, dose rate variation during beam delivery. The advantages of using these techniques are delivery of conformal radiation dose to the target while sparing the surrounding normal tissues and organs-at-risk (OAR) are significantly higher compared to conventional 3D techniques. However, due to the high degree of complexity of these techniques, it is strongly recommended to do pre-treatment verification before dose delivery. For this reason, different types of 2D or 3D detectors such as diode arrays, ionization chambers, film (e.g., Gafchromic film EBT3), electronic portal imaging device (EPID), etc. have been used to ensure that the prescribed treatment dose is delivered within the clinically acceptable error tolerances. Regardless of the type of detector, all of this equipment has spatial limitations because of the discrete placement and physical separation of each detector which may affect GPR results [59, 60].
6.1 Effect of detector resolution on gamma passing rate
As it was mentioned before, phantoms or dosimeter devices used for performing patient-specific QA present spatial resolution limitations which may affect GPR results. Several research has been conducted to show the discrepancy of GPR within different phantoms with different spatial resolutions. Bruschi et al. [59] studied the effect of detector resolution on GPR. Three detectors (PTW OCTAVIUS 4D 729, 1500, and 100 SRS) used in five configurations with different resolutions were utilized in their study. This study indicates the detector resolution can significantly affect the SBRT pre-treatment verification results and a detector with high spatial resolution would be able to detect any kind of error such as those caused by MLC position, collimator, and gantry rotations, etc. In 2017 Woon et al. [61] worked on a similar subject and used three detectors with different resolutions (MapCHECK2, ArcCHECK, and EPID). They demonstrated that MLC errors of greater than 0.5 mm were not distinguishable in measured doses by the MapCheck2/ArcCHECK due to the inferior resolution caused by the large diode spacing relative to the resolution of the EPID. Bailey et al. [53] reported that detector arrays with low-spatial resolution may potentially affect the gamma index analysis by under sampling data. On the other hand, Steers et al. [62] indicated that different detectors show different error sensitivity which depends on the induced type of error and the GPR does not highly depend on detector spatial sampling. Moreover, they showed that increasing spatial sampling not only increase the GPR but also reduces error sensitivity in many cases. This is observed if the increase in the number of sampling results in a higher number of low dose points in the comparison than high dose points, an effect which is increasingly important for globally normalized gamma comparisons [62]. Salari et al. [63] also compared standard density vs. high density measurements of ArcCHECK phantom in Intensity Modulation Radiosurgery (IMRS) cases and compared the GPR values. As shown in Figure 1, the results of standard density mode had better GPR for each energy and planned dose grid which is also in good agreement with Steer et al. result. Note that 1 mm and 2 mm represent GS; 6 FFF and 10 FFF for 6 MV FFF and 10 MV FFF beam energies, respectively.
Figure 1.
Comparisons of standard density vs. high-density modes between different planned grid sizes and energy. (reprinted from Salari, et al., “evaluation of parameters affecting gamma passing rate in patient-specific QA’s for multiple brain lesions IMRS treatments using Ray-Station treatment planning system. In print: J Appl Clin med Phys. 2021).
Hussein et al. [64] also conducted research on five commercial QA devices and analyzed the effect of detector resolution on γ. They concluded that different combinations of QA devices and software exhibit varying level of agreement for the same passing rate.
7. Modulation indices
Modern treatment techniques, such as IMRT and VMAT, have enabled the escalation of target dose with fewer side effects to the surrounding OARs by modulation of the treatment plans to achieve the desired dose distribution. In IMRT, MLCs are moving during treatment, thereby delivering a radiation field with a non-uniform intensity while in VMAT technique, in addition to MLC motions, gantry speed and dose rate are also variable when the radiation beam is continuously on. For patients’ protection and safety, pretreatment dosimetric verification is done to provide sufficient data on the safety and reliability of treatment plans and delivery, even though performing pretreatment dosimetric verification is considered an additional workload. Therefore, a retrospective analysis of which parameter (leaf travel, beam aperture and shapes, control point angular separation, dose rate, and gantry variations) can affect the ability of the TPS to calculate a dose may provide important information on the limits of TPSs for IMRT/VMAT plans. The difference between calculated and measured dose distribution may be affected by the accuracy of the TPS calculation and the delivery accuracy. Discriminating between the two causes of errors is not an easy task. Furthermore, the delivery accuracy of IMRT/VMAT plans can be predicted by the score of plan modulation complexity [65]. For this purpose, many authors introduced or evaluated different Modulation Indices (MI)/parameters to find a correlation between plan complexity and GPR.
Nicolini et al. [66] studied the effect of gantry speed (deg/s) and dose rate (MU/min) on the quality of VMAT plans and showed using a higher dose rate improves plan quality and reduces delivery time. They also used dynamic log files generated by linac controllers to evaluate the delivery accuracy of plans and found out accuracy slightly improved in delivery when using a low dose rate. Wu et al. [67] analyzed the results of dose verification of 924 patients including the relationship between gamma pass rates and the location of lesions, the total number of monitor units, and the maximum area of the collective dose. They observed a correlation between the treatment site and GPR plus a strong negative correlation between total MUs and GPR that indicates increasing MU results in lower GPR. Moreover, a weak negative correlation between the largest area of the acquisition dose and GPR was reported [67]. McNiven et al. [68] proposed Modulation Complexity Score (MCS) for step-and-shoot IMRT. This score is contribution of variability in the shape of segments and variations in their area. The range of MCS is from 0 to 1. The lower value of the MCS means higher complexity. This metric provides more information about the plan quality than simple metrics such as total MUs and number of segments, but no correlation was observed between GPR and MCS which is in a good agreement with other research [69, 70]. This index was later adapted by Masi et al. [65]for VMAT plans by substituting control points for segments and called it (MCSv). Also, Masi et al. introduced Leaf Travel (LT) as the average distance that MLC is traveling over one arc in VMAT and LTMCS index which takes into account both LT and MCSv and has a range between 0 and 1. Zero shows a higher degree of modulation and leaf motion. They reported a moderate correlation between LT, MCSv, LTMCS, and GPR and a weak correlation between MU and GPR. Hernandez et al. [71] modified LT for multiple arcs or partial arc by dividing LT over arc length (LT/AL). Another index is Edge Metric (EM) which was defined by Young et al. [72] and it calculates the complexity as the ratio of MLC side length edge to aperture area. The larger EM index indicates the difference between the positions of adjacent leaves are larger which is closely related to the tongue-and-groove effect. Du et al. in 2014 [73] introduced several MIs to evaluate plan complexity such as plan averaged beam area (PA), plan averaged beam irregularity (PI), plan averaged beam modulation (PM), and plan normalized MU (PMU). PA is the average area of beam apertures; PI indicates the non-circularity of the shape of aperture and PM describes to what extent a beam is modulated with multiple smaller apertures. PMU is to compare the total MU among all plans with different prescription dose levels. According to a number of studies [70, 71, 73] MCS, EM, and PI provide similar information. In 2014, Park et al. [74] defined MIs, MIa, and MItotal which MItotal unlike previous metrics include both gantry speed and dose rate variations besides MLC motions to quantify the total delivery complexity for VMAT plans. MIs which evaluate MLC speed was originally introduced by Webb [75] to evaluate the modulation degree of IMRT and were modified by Park et al. for VMAT treatment plans and MIa evaluates both speed and acceleration of MLCs. They also studied the MCSv and LTMCS and did not see correlations as high as those found in a previous study (Masi et al) to the pre-treatment VMAT QA results.
In summary, various studies were conducted in this area and revealed different results regarding the correlation between plan complexity indices and QA metrics [65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79]. We believe, these differences may depend on the linac model and its commissioning plus TPS limitations such as beam model, dose engine, and algorithm [71, 80, 81].
8. Conclusions
As described in this chapter, there are a number of sources which may contribute and arise different levels of discrepancy between the computed dose by TPS and measurements. Much effort has been devoted to improve the accuracy of dose calculation algorithms, computing technology and measurements, and through all these developments the accuracy of dose calculation and measurements seems close to our clinical goals. Although, the accuracy of dose calculation in homogenous medium (e.g., water) does not much rely on the algorithm, in heterogeneous media such as lungs or bone, the accuracy of calculation depends strongly on the kernels of calculation algorithms and how well they can simulate the actual scattering of photon and electrons. As mentioned previously in this chapter and noted by authors in various literatures, the accuracy of dose calculation algorithms is rated as principle-based algorithms such as Monte Carlo, and the linear Boltzmann transport as the most accurate, followed by model-based algorithms such as CCC, AAA, and PBC in that order for accuracy; and correction-based algorithms. Another important item to be considered is the beam modeling which will directly affect the accuracy of dose calculation where each TPS has its own features to model beams. Therefore, following the beam data measurements, commissioning of the modeled beams becomes a necessary step typically achieved through end-to-end testing. This is to verify dose distribution and accurate computation under different clinical conditions before any clinical use. Moreover, it is important to understand the response and limitations of each equipment used along with gamma index analysis due to different combinations of QA devices and software packages, which may result in varying levels of agreement with the predicted gamma analysis for the same pass-rate criteria. Various reasons result in different correlations between GPR and complexity metrics, hence, these correlations are not generic and should be defined for each TPS.
Conflict of interest
None to report.
\n',keywords:"pre-treatment verification, gamma index, treatment planning algorithms, beam modeling, detector resolution, planned dose grid, modulation index",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80360.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80360.xml",downloadPdfUrl:"/chapter/pdf-download/80360",previewPdfUrl:"/chapter/pdf-preview/80360",totalDownloads:60,totalViews:0,totalCrossrefCites:0,dateSubmitted:"December 16th 2021",dateReviewed:"January 6th 2022",datePrePublished:"February 13th 2022",datePublished:null,dateFinished:"February 4th 2022",readingETA:"0",abstract:"To assure the accuracy and safety of radiation delivery, it is highly recommended to perform pretreatment verification for complex treatment methods such as intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) to detect any potential errors in the treatment planning process and machine deliverability. It is expected that a qualified medical physicist is aware of the underlying scientific principles of imaging and therapeutic processes to perform or supervise technical aspects of pretreatment procedures to ensure safe and effective delivery of the treatment. For this purpose, several guidelines have been published to help direct medical physicists to evaluate the accuracy of treatment planning system (TPS) in the calculation of radiation dose, and dosimetry equipment to avoid possible errors. This will require a clear understanding of abilities as well as the limitations of each TPS, the dosimetry equipment at hand, and the gamma index to perform a comprehensive pre-treatment verification.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80360",risUrl:"/chapter/ris/80360",signatures:"E. Ishmael Parsai and Elahheh Salari",book:{id:"11247",type:"book",title:"Dosimetry",subtitle:null,fullTitle:"Dosimetry",slug:null,publishedDate:null,bookSignature:"Dr. Thomas J. FitzGerald",coverURL:"https://cdn.intechopen.com/books/images_new/11247.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-460-0",printIsbn:"978-1-80355-459-4",pdfIsbn:"978-1-80355-461-7",isAvailableForWebshopOrdering:!0,editors:[{id:"241806",title:"Dr.",name:"Thomas J.",middleName:null,surname:"FitzGerald",slug:"thomas-j.-fitzgerald",fullName:"Thomas J. FitzGerald"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Treatment planning system (TPS) algorithms",level:"1"},{id:"sec_2_2",title:"2.1 Category.1",level:"2"},{id:"sec_2_3",title:"2.1.1 Linear attenuation",level:"3"},{id:"sec_3_3",title:"2.1.2 Ratio of tissue air ratio (RTAR)",level:"3"},{id:"sec_4_3",title:"2.1.3 Power law (Batho)",level:"3"},{id:"sec_6_2",title:"2.2 Category.2",level:"2"},{id:"sec_6_3",title:"2.2.1 Equivalent TAR (ETAR)",level:"3"},{id:"sec_7_3",title:"2.2.2 Differential scatter air ratio (dSAR)",level:"3"},{id:"sec_8_3",title:"2.2.3 Delta volume (DVOL)",level:"3"},{id:"sec_9_3",title:"2.2.4 Differential TAR",level:"3"},{id:"sec_11_2",title:"2.3 Category.3",level:"2"},{id:"sec_11_3",title:"2.3.1 Convolution techniques",level:"3"},{id:"sec_12_3",title:"2.3.2 Fast Fourier transform (FFT) convolution",level:"3"},{id:"sec_14_2",title:"2.4 Category.4",level:"2"},{id:"sec_14_3",title:"2.4.1 Convolution-superposition algorithms",level:"3"},{id:"sec_15_3",title:"2.4.2 Anisotropic analytical algorithm",level:"3"},{id:"sec_16_3",title:"2.4.3 Collapsed cone convolution",level:"3"},{id:"sec_17_3",title:"2.4.4 Monte Carlo",level:"3"},{id:"sec_18_3",title:"2.4.5 Acuros XB",level:"3"},{id:"sec_21",title:"3. Beam Modeling of commercial treatment planning systems",level:"1"},{id:"sec_22",title:"4. Measurement methods for pre-treatment verification",level:"1"},{id:"sec_22_2",title:"4.1 True composite",level:"2"},{id:"sec_23_2",title:"4.2 Perpendicular field-by-field",level:"2"},{id:"sec_24_2",title:"4.3 Perpendicular composite",level:"2"},{id:"sec_26",title:"5. Gamma index",level:"1"},{id:"sec_26_2",title:"5.1 Effect of planned grid size on gamma passing rate",level:"2"},{id:"sec_28",title:"6. Dosimetry equipment for pre-treatment verification",level:"1"},{id:"sec_28_2",title:"6.1 Effect of detector resolution on gamma passing rate",level:"2"},{id:"sec_30",title:"7. Modulation indices",level:"1"},{id:"sec_31",title:"8. Conclusions",level:"1"},{id:"sec_35",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Khan F, Gerbi B. Treatment planning algorithms: Model-based photon dose calculations. 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He is an expert in structural, absorptive, catalytic and photocatalytic properties, in structural organization and dynamic features of ionic liquids, in magnetic interactions between paramagnetic centers. The author or co-author of 3 books, over 200 articles and reviews in scientific journals and books. He is an actual member of the International EPR/ESR Society, European Society on Quantum Solar Energy Conversion, Moscow House of Scientists, of the Board of Moscow Physical Society.",institutionString:null,institution:{name:"Semenov Institute of Chemical Physics",country:{name:"Russia"}}},{id:"62389",title:"PhD.",name:"Ali Demir",middleName:null,surname:"Sezer",slug:"ali-demir-sezer",fullName:"Ali Demir Sezer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/62389/images/3413_n.jpg",biography:"Dr. Ali Demir Sezer has a Ph.D. from Pharmaceutical Biotechnology at the Faculty of Pharmacy, University of Marmara (Turkey). He is the member of many Pharmaceutical Associations and acts as a reviewer of scientific journals and European projects under different research areas such as: drug delivery systems, nanotechnology and pharmaceutical biotechnology. Dr. Sezer is the author of many scientific publications in peer-reviewed journals and poster communications. Focus of his research activity is drug delivery, physico-chemical characterization and biological evaluation of biopolymers micro and nanoparticles as modified drug delivery system, and colloidal drug carriers (liposomes, nanoparticles etc.).",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"61051",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:null},{id:"100762",title:"Prof.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"St David's Medical Center",country:{name:"United States of America"}}},{id:"107416",title:"Dr.",name:"Andrea",middleName:null,surname:"Natale",slug:"andrea-natale",fullName:"Andrea Natale",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Texas Cardiac Arrhythmia",country:{name:"United States of America"}}},{id:"64434",title:"Dr.",name:"Angkoon",middleName:null,surname:"Phinyomark",slug:"angkoon-phinyomark",fullName:"Angkoon Phinyomark",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/64434/images/2619_n.jpg",biography:"My name is Angkoon Phinyomark. I received a B.Eng. degree in Computer Engineering with First Class Honors in 2008 from Prince of Songkla University, Songkhla, Thailand, where I received a Ph.D. degree in Electrical Engineering. My research interests are primarily in the area of biomedical signal processing and classification notably EMG (electromyography signal), EOG (electrooculography signal), and EEG (electroencephalography signal), image analysis notably breast cancer analysis and optical coherence tomography, and rehabilitation engineering. I became a student member of IEEE in 2008. During October 2011-March 2012, I had worked at School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex, United Kingdom. In addition, during a B.Eng. I had been a visiting research student at Faculty of Computer Science, University of Murcia, Murcia, Spain for three months.\n\nI have published over 40 papers during 5 years in refereed journals, books, and conference proceedings in the areas of electro-physiological signals processing and classification, notably EMG and EOG signals, fractal analysis, wavelet analysis, texture analysis, feature extraction and machine learning algorithms, and assistive and rehabilitative devices. I have several computer programming language certificates, i.e. Sun Certified Programmer for the Java 2 Platform 1.4 (SCJP), Microsoft Certified Professional Developer, Web Developer (MCPD), Microsoft Certified Technology Specialist, .NET Framework 2.0 Web (MCTS). I am a Reviewer for several refereed journals and international conferences, such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Industrial Electronics, Optic Letters, Measurement Science Review, and also a member of the International Advisory Committee for 2012 IEEE Business Engineering and Industrial Applications and 2012 IEEE Symposium on Business, Engineering and Industrial Applications.",institutionString:null,institution:{name:"Joseph Fourier University",country:{name:"France"}}},{id:"55578",title:"Dr.",name:"Antonio",middleName:null,surname:"Jurado-Navas",slug:"antonio-jurado-navas",fullName:"Antonio Jurado-Navas",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",biography:"Antonio Jurado-Navas received the M.S. degree (2002) and the Ph.D. degree (2009) in Telecommunication Engineering, both from the University of Málaga (Spain). He first worked as a consultant at Vodafone-Spain. From 2004 to 2011, he was a Research Assistant with the Communications Engineering Department at the University of Málaga. In 2011, he became an Assistant Professor in the same department. From 2012 to 2015, he was with Ericsson Spain, where he was working on geo-location\ntools for third generation mobile networks. Since 2015, he is a Marie-Curie fellow at the Denmark Technical University. His current research interests include the areas of mobile communication systems and channel modeling in addition to atmospheric optical communications, adaptive optics and statistics",institutionString:null,institution:{name:"University of Malaga",country:{name:"Spain"}}}],filtersByRegion:[{group:"region",caption:"North America",value:1,count:6597},{group:"region",caption:"Middle and South America",value:2,count:5902},{group:"region",caption:"Africa",value:3,count:2400},{group:"region",caption:"Asia",value:4,count:12537},{group:"region",caption:"Australia and Oceania",value:5,count:1006},{group:"region",caption:"Europe",value:6,count:17560}],offset:12,limit:12,total:132761},chapterEmbeded:{data:{}},editorApplication:{success:null,errors:{}},ofsBooks:{filterParams:{hasNoEditors:"1",sort:"dateEndThirdStepPublish",topicId:"7,10,15,24,5,6,8,9,11,23,14,16,17,12,18,19,20,21,22,13,25"},books:[{type:"book",id:"11254",title:"Optical Coherence 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Rajkumar"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"712",title:"Intraepithelial Neoplasia",subtitle:null,isOpenForSubmission:!1,hash:"a1aa9858b1db54a89329fa086261dfd2",slug:"intraepithelial-neoplasia",bookSignature:"Supriya Srivastava",coverURL:"https://cdn.intechopen.com/books/images_new/712.jpg",editedByType:"Edited by",editors:[{id:"85273",title:"Dr.",name:"Supriya",middleName:null,surname:"Srivastava",slug:"supriya-srivastava",fullName:"Supriya Srivastava"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:5,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"58601",doi:"10.5772/intechopen.72705",title:"Ovarian Cancer Genetics: Subtypes and Risk Factors",slug:"ovarian-cancer-genetics-subtypes-and-risk-factors",totalDownloads:2481,totalCrossrefCites:8,totalDimensionsCites:10,abstract:"The genetics of ovarian cancer are a complex, ever evolving concept that presents hurdles in classification, diagnosis, and treatment in the clinic. Instead of common driver mutations, genomic instability is one of the hallmarks of ovarian cancer. While ovarian cancer is stratified into different clinical subtypes, there still exists extensive genetic and progressive diversity within each subtype. In high-grade serous ovarian cancer, the most common subtype, TP53 is mutated in over 90% of all patients while the next most common mutation is less than 20%. However, next-generation sequencing and biological statistics have shown that mutations within DNA repair pathways, including BRCA1 and BRCA2, are common in about 50% of all high-grade serous patients leading to the development of a breakthrough therapy of poly ADP ribose polymerase (PARP) inhibitors. This is just one example of how a better understanding of the complex genetic background of ovarian cancer can improve clinical treatment. A thorough review of ovarian cancer genetics and the effect it has on disease development, diagnosis, progression, and treatment will enhance the understanding of how to better research and treat ovarian cancer.",book:{id:"5997",slug:"ovarian-cancer-from-pathogenesis-to-treatment",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - From Pathogenesis to Treatment"},signatures:"Jeff Hirst, Jennifer Crow and Andrew Godwin",authors:[{id:"219865",title:"Dr.",name:"Jeff",middleName:null,surname:"Hirst",slug:"jeff-hirst",fullName:"Jeff Hirst"},{id:"219866",title:"Dr.",name:"Andrew",middleName:null,surname:"Godwin",slug:"andrew-godwin",fullName:"Andrew Godwin"},{id:"219867",title:"Dr.",name:"Jennifer",middleName:null,surname:"Crow",slug:"jennifer-crow",fullName:"Jennifer Crow"}]},{id:"60255",doi:"10.5772/intechopen.75484",title:"The Role of Circulating Biomarkers in the Early Diagnosis of Ovarian Cancer",slug:"the-role-of-circulating-biomarkers-in-the-early-diagnosis-of-ovarian-cancer",totalDownloads:1199,totalCrossrefCites:3,totalDimensionsCites:5,abstract:"Ovarian cancer is the leading cause of gynecologic-related cancer death and epithelial ovarian cancer (EOC) is the most lethal sub-type. EOC is usually asymptomatic, and few screening tests are available. Diagnosis of ovarian cancer can be difficult because of the nonspecific symptoms. Despite the various diagnostic methods used, there is no reliable early diagnostic test and it needs to be developed. Specific biomarkers may have potential with the least possible invasive procedure. Biomarkers with a high sensitivity to ovarian cancer should be identified. Circulating biomarkers that are significant tools for non-invasive early diagnosis can be analyzed using circulating tumor cells, exosomes, and circulating nucleic acids. Protein, gene, metabolite, and miRNA-based biomarkers can be used for ovarian cancer diagnosis. As non-coding RNAs, MiRNAs may have an important role in ovarian cancer diagnosis due to their effects on mRNA expression levels. The most recent developments regarding the potential of circulating biomarkers to detect early ovarian cancer is presented in this chapter.",book:{id:"5997",slug:"ovarian-cancer-from-pathogenesis-to-treatment",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - From Pathogenesis to Treatment"},signatures:"Ece Gumusoglu and Tuba Gunel",authors:[{id:"68399",title:"Dr.",name:"Tuba",middleName:null,surname:"Gunel",slug:"tuba-gunel",fullName:"Tuba Gunel"},{id:"202504",title:"M.Sc.",name:"Ece",middleName:null,surname:"Gumusoglu",slug:"ece-gumusoglu",fullName:"Ece Gumusoglu"}]},{id:"61944",doi:"10.5772/intechopen.78383",title:"The Landscape of Histone Modification in Cancer Metastasis",slug:"the-landscape-of-histone-modification-in-cancer-metastasis",totalDownloads:1543,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Metastasis represents one of the most devastating aspects of cancer. Epithelial to mesenchymal transition (EMT) has been shown to play a critical role in tumorigenic metastasis. During metastatic progression, both genetic and epigenetic modifications endow cancer cells with properties that modulate the capacity for metastatic success. Histone modification is profoundly altered in cancer cells and contributes to cancer metastasis by controlling different metastatic phenotypes. Here, we first review histone modifications and discuss their roles in EMT and metastasis, with a particular focus on histone methylation and acetylation. Second, we review the major histone modification enzymes that control chromatin in cancer metastasis. Third, we discuss the transcriptional regulation concerted by these enzymes with EMT transcription factors at different molecular layers. Finally, we discuss pharmacologic manipulation of histone modification enzymes for metastasis treatment. A comprehensive understanding of histone modification in metastasis will not only provide new insights into our knowledge of cancer progression and metastasis, but also offer a novel approach for the development of innovative therapeutic strategies.",book:{id:"7271",slug:"cancer-metastasis",title:"Cancer Metastasis",fullTitle:"Cancer Metastasis"},signatures:"Zhaoping Qiu, Jianlin Wang and Yadi Wu",authors:[{id:"121037",title:"Dr.",name:"Yadi",middleName:null,surname:"Wu",slug:"yadi-wu",fullName:"Yadi Wu"},{id:"256631",title:"Dr.",name:"Zhaoping",middleName:null,surname:"Qiu",slug:"zhaoping-qiu",fullName:"Zhaoping Qiu"},{id:"256632",title:"Dr.",name:"Jianlin",middleName:null,surname:"Wang",slug:"jianlin-wang",fullName:"Jianlin Wang"}]},{id:"62124",doi:"10.5772/intechopen.78717",title:"Epithelial-Mesenchymal Transition in Tumor Microenvironment Induced by Hypoxia",slug:"epithelial-mesenchymal-transition-in-tumor-microenvironment-induced-by-hypoxia",totalDownloads:1572,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"A tumor microenvironment contains various noncancerous cells including adipocytes, fibroblasts, immune and inflammatory cells, neuroendocrine cells, pericytes, vascular and lymphatic endothelial cells, and the extracellular matrix that surrounds cancerous cells. In the tumor microenvironment, cancer cells interact and cross talk with noncancerous cells and orchestrate different mechanisms of cancer such as tumorigenesis, angiogenesis, and metastasis. Moreover, the expansive nature of cancer cells and chaotic angiogenesis affect microcirculation as well as alter the oxygen concentration progressively. Hypoxia, a key player in the multistep process of cancer metastasis, is important in different regions of the tumor microenvironment. Hypoxia may transform cancer cells to become more aggressive and invasive by triggering overexpression of several hypoxia-related factors that activate epithelial-mesenchymal transition (EMT). Herein, the current knowledge of how hypoxia-driven EMT is presented in the tumor microenvironment of solid cancers is discussed.",book:{id:"7271",slug:"cancer-metastasis",title:"Cancer Metastasis",fullTitle:"Cancer Metastasis"},signatures:"Görkem Eskiizmir and Erdoğan Özgür",authors:[{id:"247860",title:"Dr.",name:"Gorkem",middleName:null,surname:"Eskiizmir",slug:"gorkem-eskiizmir",fullName:"Gorkem Eskiizmir"},{id:"247862",title:"Dr.",name:"Erdogan",middleName:null,surname:"Özgür",slug:"erdogan-ozgur",fullName:"Erdogan Özgür"}]},{id:"59258",doi:"10.5772/intechopen.73863",title:"Ovarian Cancer Overview: Molecular Biology and Its Potential Clinical Application",slug:"ovarian-cancer-overview-molecular-biology-and-its-potential-clinical-application",totalDownloads:1320,totalCrossrefCites:1,totalDimensionsCites:4,abstract:"Over the previous two decades, there has been a shift in the ovarian cancer paradigm to consider it as a multiplicity of disease types rather than a single disease, requiring specialized medical management from molecular diagnosis through to treatment. Despite the achieved improvements in diagnosis, surgery, and systemic treatment, ovarian cancer remains the leading cause of death from gynecological tumors in western countries. The study of ovarian cancer at a molecular level could reveal potential biomarkers of disease diagnosis and progression, as well as possible therapeutic targets in areas such as angiogenesis and homologous recombination deficiencies. Although this area of research is proving invaluable concerning newer therapeutic approaches, platinum-based chemotherapy continues to be the core of the first-line treatment. Genomic screening focusing on the identification of prognostic and predictive markers is considered one of the leading areas for future ovarian cancer research.",book:{id:"5997",slug:"ovarian-cancer-from-pathogenesis-to-treatment",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - From Pathogenesis to Treatment"},signatures:"Joana Assis, Deolinda Pereira, Augusto Nogueira and Rui Medeiros",authors:[{id:"50776",title:"Prof.",name:"Rui Manuel",middleName:null,surname:"de Medeiros Melo Silva",slug:"rui-manuel-de-medeiros-melo-silva",fullName:"Rui Manuel de Medeiros Melo Silva"},{id:"57116",title:"MSc.",name:"Augusto",middleName:null,surname:"Nogueira",slug:"augusto-nogueira",fullName:"Augusto Nogueira"},{id:"209193",title:"MSc.",name:"Joana",middleName:null,surname:"Assis",slug:"joana-assis",fullName:"Joana Assis"},{id:"209194",title:"MSc.",name:"Deolinda",middleName:null,surname:"Pereira",slug:"deolinda-pereira",fullName:"Deolinda Pereira"}]}],mostDownloadedChaptersLast30Days:[{id:"57832",title:"Secondary Prevention of Uterine Cervical Cancer",slug:"secondary-prevention-of-uterine-cervical-cancer",totalDownloads:1097,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Secondary prevention by cervical cytology has clearly improved the mortality rate of uterine cervical cancer (CC) by enabling early detection and treatment of high-grade squamous intraepithelial lesion (HSIL) or cervical intraepithelial neoplasia (CIN), which is a precancerous lesion. In the past two decades, HPV-DNA testing, including HPV typing, has clearly brought about positive effects on secondary prevention of CC. However, in practice, CC remains a fatal disease and is the second leading cause of cancer deaths in women aged 20–39 years. Although elucidation of the mechanisms of HPV carcinogenesis and development of a prophylactic vaccine have made CC a preventable disease, eradication of CC is expected to take several decades. Therefore, primary screening to decrease the mortality rate of CC will remain important for a while. In addition, the clinical application of simple biomarkers to stratify HPV-positive women is important for maintenance of medical economy and avoidance of overtreatment in women in the reproductive age. Therefore, the development of an inexpensive therapy or vaccine that can be used worldwide is necessary to overcome cancer deaths due to CC.",book:{id:"6421",slug:"cervical-cancer-screening-treatment-and-prevention-universal-protocols-for-ultimate-control",title:"Cervical Cancer",fullTitle:"Cervical Cancer - Screening, Treatment and Prevention - Universal Protocols for Ultimate Control"},signatures:"Seiya Sato and Hiroaki Itamochi",authors:[{id:"217868",title:"Prof.",name:"Hiroaki",middleName:null,surname:"Itamochi",slug:"hiroaki-itamochi",fullName:"Hiroaki Itamochi"},{id:"231820",title:"Dr.",name:"Seiya",middleName:null,surname:"Sato",slug:"seiya-sato",fullName:"Seiya Sato"}]},{id:"58601",title:"Ovarian Cancer Genetics: Subtypes and Risk Factors",slug:"ovarian-cancer-genetics-subtypes-and-risk-factors",totalDownloads:2481,totalCrossrefCites:8,totalDimensionsCites:10,abstract:"The genetics of ovarian cancer are a complex, ever evolving concept that presents hurdles in classification, diagnosis, and treatment in the clinic. Instead of common driver mutations, genomic instability is one of the hallmarks of ovarian cancer. While ovarian cancer is stratified into different clinical subtypes, there still exists extensive genetic and progressive diversity within each subtype. In high-grade serous ovarian cancer, the most common subtype, TP53 is mutated in over 90% of all patients while the next most common mutation is less than 20%. However, next-generation sequencing and biological statistics have shown that mutations within DNA repair pathways, including BRCA1 and BRCA2, are common in about 50% of all high-grade serous patients leading to the development of a breakthrough therapy of poly ADP ribose polymerase (PARP) inhibitors. This is just one example of how a better understanding of the complex genetic background of ovarian cancer can improve clinical treatment. A thorough review of ovarian cancer genetics and the effect it has on disease development, diagnosis, progression, and treatment will enhance the understanding of how to better research and treat ovarian cancer.",book:{id:"5997",slug:"ovarian-cancer-from-pathogenesis-to-treatment",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - From Pathogenesis to Treatment"},signatures:"Jeff Hirst, Jennifer Crow and Andrew Godwin",authors:[{id:"219865",title:"Dr.",name:"Jeff",middleName:null,surname:"Hirst",slug:"jeff-hirst",fullName:"Jeff Hirst"},{id:"219866",title:"Dr.",name:"Andrew",middleName:null,surname:"Godwin",slug:"andrew-godwin",fullName:"Andrew Godwin"},{id:"219867",title:"Dr.",name:"Jennifer",middleName:null,surname:"Crow",slug:"jennifer-crow",fullName:"Jennifer Crow"}]},{id:"63228",title:"Ovarian Clear Cell Carcinoma: Metastatic Pathways",slug:"ovarian-clear-cell-carcinoma-metastatic-pathways",totalDownloads:1352,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Ovarian carcinoma reflects the biggest challenge among the field of gynecologic oncology. It represents the most common death cause of genital carcinomas throughout years. The major classification consists of epithelial and non-epithelial types. Due to the histologic origin, epithelial types of ovarian carcinoma are endometrioid, serous-mucinous, and clear cell types. Due to intense metastatic infiltration and rapid tumor spread, clear cell ovarian carcinoma constitutes type of lesion with the most poor prognosis, decreased overall survival, decreased free survival, and poor quality of life of the patient. The metastatic infiltration is strongly accompanied with all significant prognostic factors. All biochemical pathways at the time of the infiltration are correlated with tumor size, lymphatic spread, staging of the lesion, histologic type, and grade of differentiation of the lesion.",book:{id:"7271",slug:"cancer-metastasis",title:"Cancer Metastasis",fullTitle:"Cancer Metastasis"},signatures:"Chrisostomos Sofoudis",authors:[{id:"173802",title:"Dr.",name:"Chrisostomos",middleName:null,surname:"Sofoudis",slug:"chrisostomos-sofoudis",fullName:"Chrisostomos Sofoudis"}]},{id:"27761",title:"Excess Fibroblast Growth Factor-7 (FGF-7) Activates b-Catenin and Leads to Ocular Surface Squamous Neoplasia in Mice",slug:"excess-fibroblast-growth-factor-7-fgf-7-activates-b-catenin-and-leads-to-ocular-surface-squamous-neo",totalDownloads:2528,totalCrossrefCites:0,totalDimensionsCites:0,abstract:null,book:{id:"712",slug:"intraepithelial-neoplasia",title:"Intraepithelial Neoplasia",fullTitle:"Intraepithelial Neoplasia"},signatures:"Chia-Yang Liu and Winston W.-Y. Kao",authors:[{id:"88194",title:"Dr.",name:"Chia-Yang",middleName:null,surname:"Liu",slug:"chia-yang-liu",fullName:"Chia-Yang Liu"},{id:"127513",title:"Prof.",name:"Winston W.-Y.",middleName:null,surname:"Kao",slug:"winston-w.-y.-kao",fullName:"Winston W.-Y. Kao"}]},{id:"58059",title:"Novel Systemic Treatments in High Grade Ovarian Cancer",slug:"novel-systemic-treatments-in-high-grade-ovarian-cancer",totalDownloads:1055,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Most patients with ovarian cancer present at an advanced stage and are never cured. To improve outcomes a variety of novel systemic strategies are being developed. Traditional cytotoxic chemotherapy is being optimised, anti-angiogenic strategies are already in the clinic and several PARP inhibitors have gained regulatory approval. In addition, immunotherapy is showing promise and novel targeted strategies including against folate receptor alpha are also generating excitement. As our therapeutic choice increases, a challenge will be how to best utilize the options available. Here we discuss recently established and other emerging therapies with a focus on key concepts rather than detailed synopses of trial designs and outcomes.",book:{id:"5997",slug:"ovarian-cancer-from-pathogenesis-to-treatment",title:"Ovarian Cancer",fullTitle:"Ovarian Cancer - From Pathogenesis to Treatment"},signatures:"Amit Samani, Charleen Chan and Jonathan Krell",authors:[{id:"207859",title:"Dr.",name:"Amit",middleName:null,surname:"Samani",slug:"amit-samani",fullName:"Amit Samani"}]}],onlineFirstChaptersFilter:{topicId:"1080",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,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:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{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"}}}},{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"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:49,paginationItems:[{id:"80495",title:"Iron in Cell Metabolism and Disease",doi:"10.5772/intechopen.101908",signatures:"Eeka Prabhakar",slug:"iron-in-cell-metabolism-and-disease",totalDownloads:1,totalCrossrefCites:0,totalDimensionsCites:null,authors:null,book:{title:"Iron Metabolism - Iron a Double‐Edged Sword",coverURL:"https://cdn.intechopen.com/books/images_new/10842.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"81799",title:"Cross Talk of Purinergic and Immune Signaling: Implication in Inflammatory and Pathogenic Diseases",doi:"10.5772/intechopen.104978",signatures:"Richa Rai",slug:"cross-talk-of-purinergic-and-immune-signaling-implication-in-inflammatory-and-pathogenic-diseases",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Purinergic System",coverURL:"https://cdn.intechopen.com/books/images_new/10801.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"81764",title:"Involvement of the Purinergic System in Cell Death in Models of Retinopathies",doi:"10.5772/intechopen.103935",signatures:"Douglas Penaforte Cruz, Marinna Garcia Repossi and Lucianne Fragel Madeira",slug:"involvement-of-the-purinergic-system-in-cell-death-in-models-of-retinopathies",totalDownloads:4,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Purinergic System",coverURL:"https://cdn.intechopen.com/books/images_new/10801.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"81756",title:"Alteration of Cytokines Level and Oxidative Stress Parameters in COVID-19",doi:"10.5772/intechopen.104950",signatures:"Marija Petrusevska, Emilija Atanasovska, Dragica Zendelovska, Aleksandar Eftimov and Katerina Spasovska",slug:"alteration-of-cytokines-level-and-oxidative-stress-parameters-in-covid-19",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Chemokines Updates",coverURL:"https://cdn.intechopen.com/books/images_new/11672.jpg",subseries:{id:"18",title:"Proteomics"}}}]},overviewPagePublishedBooks:{paginationCount:27,paginationItems:[{type:"book",id:"7006",title:"Biochemistry and Health Benefits of Fatty Acids",subtitle:null,coverURL:"https://cdn.intechopen.com/books/images_new/7006.jpg",slug:"biochemistry-and-health-benefits-of-fatty-acids",publishedDate:"December 19th 2018",editedByType:"Edited by",bookSignature:"Viduranga Waisundara",hash:"c93a00abd68b5eba67e5e719f67fd20b",volumeInSeries:1,fullTitle:"Biochemistry and Health Benefits of Fatty Acids",editors:[{id:"194281",title:"Dr.",name:"Viduranga Y.",middleName:null,surname:"Waisundara",slug:"viduranga-y.-waisundara",fullName:"Viduranga Y. Waisundara",profilePictureURL:"https://mts.intechopen.com/storage/users/194281/images/system/194281.jpg",biography:"Dr. Viduranga Waisundara obtained her Ph.D. in Food Science and Technology from the Department of Chemistry, National University of Singapore, in 2010. She was a lecturer at Temasek Polytechnic, Singapore from July 2009 to March 2013. She relocated to her motherland of Sri Lanka and spearheaded the Functional Food Product Development Project at the National Institute of Fundamental Studies from April 2013 to October 2016. She was a senior lecturer on a temporary basis at the Department of Food Technology, Faculty of Technology, Rajarata University of Sri Lanka. She is currently Deputy Principal of the Australian College of Business and Technology – Kandy Campus, Sri Lanka. 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