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Article Type: Review Paper
Date of acceptance: March 2022
Date of publication: March 2022
DoI: 10.5772/dmht.05
copyright: ©2022 The Author(s), Licensee IntechOpen, License: CC BY 4.0
Scientists today are pursuing the development of non-destructive and non-invasive methods for rapid and reliable diagnosis of diseases in digital form and reduction in the need for biopsies. In this paper we review the most recent studies supporting the application of Fourier Transform Infrared (FT-IR) spectroscopy and infrared thermography or medical thermography. Both are non-destructive digital techniques, which are promising to record and discriminate the local biochemical changes that are induced by the diseases, while the examined samples do not need any special preparation. The reflected infrared radiation from the affected areas of the body strongly depends on the metabolic steps of the cancer/or any other disease, which is also related to the structural changes at a molecular level of the biological molecules during enzymatic or non-enzymatic steps of the disease. The detection of the FT-IR spectral digital “marker bands” of the obtained changes of cell, liquids or tissue components are derived from the disease in the check point. Furthermore, ImageJ analysis of the thermal imaging in cancerous area showed aggregate formation upon cancer development as it was also indicated from the FT-IR spectra.
infrared spectroscopy
thermography
protein structure
digital diagnostic bands
precision medicine
Author information
Early diagnosis of diseases is important for better treatment patients and extend their life. In this regard, diagnostics is the first step of precision medicine. Point technology in medical imaging, prevention and therapy is achieved today through technical artificial intelligence, digital processing, and handling data, as well as with totally self-made procedures [1, 2]. Moreover, innovation constitutes the application of logarithms in the handling of samples in order to derive parameters to identify correctly the results better than other methods and to combine the concepts of Hippocratic messages with technologic “imperative” (power) [3]. In addition, the use of single and unique “bar code” or “diagnostic band” for detection of biological samples together with automation minimizes to zero the probability of false diagnostic results [4]. The development of computer technology gave the possibility to use the mathematical process of Fourier equations in order to digitalize the data to the actual spectrum. Based on the fact that the deviation to lower or higher of human’s body temperature from the normal one is associated with the appearance of disease, infrared thermometers and cameras digital infrared thermal imaging cameras were developed to measure the body temperature or to scan a current area [5, 6]. In the last couple of years, many airports have used thermometers or thermocameras to detect the passengers possibly infected with Covid-19.
Nearly one hundred years after the discovery by Sir William Herschel of the thermal radiation named (
Every object at a temperature above absolute zero emits thermal radiation [12]. Infrared imaging uses this thermal radiation with special infrared detectors to generate an image. Thermal radiation is located in the wavelength region from 0.75 to 1000 μm. The portion of the infrared spectrum that is used depends on the transmission in the atmosphere, the transmission of the used infrared optics and the spectral response of the detectors [13]. Modern infrared thermography uses real-time video/digital imaging through semiconductor focal plane arrays or micro-bolometer arrays [14, 15]. Given a blackbody (an object that absorbs all incident radiation and radiates in a continuous spectrum) a thermal imaging camera can capture accurate remote temperature measurements. High resolution cameras with focal plane arrays of 320 × 240 pixels, a thermal sensitivity less than 50 mK and a spatial resolution of 25–50 μm ensures useful thermal and spatial details [16, 17]. Working with infrared thermography to make images of temperature changes, physicians should consider the factors that influence either the evaluation or the interpretation of the thermal images. According to Fernández-Cuevas
Skin surface temperature is determined by the rate of heat exchange between the surroundings and the body core [14]. Hypothalamus is the control center of core body temperature through sympathetic autonomous system. Heat is generated during metabolism and muscles during systole, and then is transported to the skin by blood flow through vessels. The sympathetic nervous system is the primary regulator of blood circulation in the skin and is therefore, the primary regulator of thermal emission [18]. The benefit of thermography is that the doctors can follow up the patients many times during the period of treatment because of absence of ionizing radiation. Thus, this method is strongly suggested for pregnant women and children [19].
In contrast to thermography, where the infrared radiation is used to increase the temperature of the irradiated body, infrared spectroscopy is based on the vibration and rotation of the atoms in molecules. The infrared radiation is interacting with the matter and the absorbed energy excites the atoms from the fundamental level to higher vibrational or rotational levels [20–24]. The infrared radiation frequencies, which are used to characterize the molecular structure are found in the region between 2.5 to 25 μm (4000–400 cm−1). The development of computers and the Mickelson (Nobel 1907) interferometer led to the development of Fourier transform infrared (FT-IR) spectrometers. The use of computers and the Mickelson interferometer led to the development of Fourier transform infrared (FT-IR) spectrometers. Later, in the 1970’s Theophanides [25, 26] by using Fourier transform infrared spectroscopy studied the interaction of nucleotide bases and DNA with metal ions. Living tissues are complex systems and may contain molecules named biomolecules, such as lipids, proteins, sugars, DNA, membranes while they may contain functional groups like, NH, NH2, CH, CH2 CH3, COO−, OH, PO
In this article the authors will summarize the main benefits of the above-mentioned technologies, by showing examples of their potential applications.
Infrared spectral digital imaging is obtained through different steps, summarized in the following:
Temperature detection is done by using IR Therma CAM camera. To minimize the false diagnostic thermographic results and to compare the temperature variations received from thermal camera with the results of other disciplinary testing methods, patients are usually allowed to stay in a stable temperature and relative humidity-controlled room, by using air condition.
FT-IR spectroscopy does not require any special sample preparation, however, the technical analyst must be careful when selecting the tissue samples. It is significant to notice that in order to obtain high quality spectra the scientists must avoid receiving formalin fixed paraffin embedded tissues [30–37]. The paraffin’s absorption bands overlap the bands arising from membrane lipids and phospholipids. The spectra of the same tissue evaluated immediately after the extraction and fixation in formalin (a) or taken after paraffin incubation (b) are significantly different (figure 1). Comparison between the two spectra usually shows clearly that there are intensity changes and maximum of band shifts, while some bands have almost disappeared. Furthermore, the solute affects even the secondary structure of some remained proteins, because of solute-protein interactions (figure 1).
In FT-IR spectroscopy, when the size of the biological sample is small, the use of Attenuated Total Reflectance (ATR) apparatus gives the maximum sensitivity [36, 38]. In this case the infrared light reflects (total reflectance) many times along the sample providing an alternative of the concentration of the components (figure 2). Also, to increase the sensitivity of the FT-IR spectra the researchers can increase the number of spectra (number of scans).
Furthermore, in order to correlate the colors with the morphology and architecture of tissue sections received after surgery excision, scanning electron microscopy (SEM) has been used.
Despite the high potential, it should be noted that details of the diseased tissue are not always straightly obvious. To study extensively the thermal differences and transfer these thermal data to more sensitive distinguished digital colors, ImageJ analysis software can be used. In the example provided in figure 3 [illustrating the images of the arm of a patient, who was diagnosed with metastatic cancer using X-Rays (A) and the screen with thermal camera (B)], analysis of the square region of the thermal imaging B, shows special color changes, compared to the rest of the image. Significantly, this analysis shows two areas that are illustrated like craters. It has been observed that the crater-like form appears in cancerous tissue, but also as atherosclerotic plaques of patients [24]. It was found that the tissues are rich in lipophilic environment and amyloid proteins.
A further step of investigation, to better understand how the disease affects the tissue, the morphology and architecture of the cancerous bone can be analyzed, as mentioned, using SEM. SEM obtains high resolution analysis of the biopsies close to native state, without need of coating. In figure 4, the architecture of cancerous bone is illustrated; remarkably and similarly to what was expected in molecular pathology, the analysis was carried out on sections immediately corresponding to the ones examined for histopathological diagnosis. SEM can investigate and demonstrate the heterogeneity of a given tissue.
The combination with EDX (energy diffraction X-Rays) permits us to discriminate and characterize the element composition in very low small area, as is a biopsy section. In case of bones, for example, by determining the relative concentrations of the calcium (Ca) and phosphorous (P) atoms in the detected area of biopsy and calculate the ratios [Ca]:[P] it is easy to diagnose the osteoporotic or calcified regions due to a disease. X-Ray diffraction (XRD) can demonstrate that the hydroxyapatite loses its stoichiometric chemical composition, [(Ca10(PO4)6(OH)2)] and crystals of inorganic calcium phosphate salt (Ca3(PO4)2 are produced, enhancing further the bone resorption. Cross-linked proteins, damaged proteins, fibers and many other abnormalities are also detected.
ImageJ analysis of the outer-line square areas, where the cross-links of proteins are in SEM pictures, shows in our example that the proteins do not bind to hydroxyapatite. The formation of characteristic cross-links indicates that oxidative stress is present as cancer associated feature, and that free radicals are involved in the phenomenon [39, 40]. Upon oxidative stress the free radicals, which are mainly hydroxyl radicals (HO.) which by interacting with proteins produce proteins free radicals and finally form dimers, cross-links, fibrils, etc. [39, 40].
In the infrared spectral region between 4000–3000 cm−1 are located the characteristic stretching vibrational modes of the
In the presented example of bone cancer, in the fingerprint region 3000–2850 cm−1 the observed bands are assigned to antisymmetric
In the spectral region 1800–1500 cm−1 the intensities of all bands are very sensitive and are strongly affected by the disease [42–49]. The high intensity absorption “marker band” at 1742 cm−1 is originated from
The peptide bonds –CO-NH– of proteins give several absorption amide bands of which the most intense and sensitive are the amide I at 1655 cm−1 and amide II near 1541 cm−1 (see figure 5) the region 1700–1500 cm−1 as shown in figure 6. Amide I is resulted from the in-plane carbonyl stretching (
Comparison between the spectral amide I and amide II regions also shows considerable differences in shape and absorption intensities between normal vs. neoplastic tissue. These bands are strongly affected from the progression of cancer and can be used as distinct digital “marker bands” for the progression of cancer, the band intensities decrease, while the bands become broad. This means that upon cancer development the proteins change their secondary molecular structure. The shape and bandwidth of the amide I and amide II bands of the cancerous bone (figure 5b) indicates that an infrared spectrum has overlapping bands and leads to the suggestion to further analyze the spectra.
The application of deconvolution spectra or first derivatives’ or resolved analysis using the software of the instrument can differentiate the absorption bands and contribute to detailed studies and information on the proteins.
The deconvolution analysis allows us to appreciate that upon disease progression the proteins change their secondary structure from 𝛼-helix, while the overlapping bands are attributed to antiparallel (
The extended 𝛽-strands can interact also between each other by hydrogen bonds changing the conformation of the proteins, while, the lipophilic environment reverses the chain direction producing aggregates. Accumulation of aggregated amyloid proteins inhibits the regeneration of the bone leading to osteoporosis and osteolysis. It is known that the conformation of proteins is associated with the quality of biological hydroxyapatite of the bones [53, 57–60].
Schmidt
The band at 1028 cm−1 corresponds to stretching vibration of phosphate
The variation of the minerals and proteins in the bone can also be evaluated (figure 8).
The decrease of the concentration in hydroxyapatite is a sign of the loss of hydroxyapatite during the cancer development [65–69], which changes the bone properties and is remodeling, and usually presents in agreement with clinical data.
The region 1300–900 cm−1 is a very important spectral region and gives details on the phosphate mode about the progression of the cancer. The most important bands in this region are the stretching vibrations resulting from
The band at about 1240 cm−1 increases in the spectra of cancerous bone indicating that there is an increase in stretching of the phosphate ribose groups. The pentose phosphate is a pathway in the metabolism of cancer [68–70]. The implication of NADH in pentose phosphate generation elevates the ATP generation of cancer cells [68, 69] and leads to the suggestion that oxidative stress is involved in cancer development. This high metabolic pathway increases the temperature of the body, which could be detected with an infrared camera. The intense band at 1159 cm−1 is assigned to stretching vibration of
In this paper the non destructive methods, infrared thermography and Fourier transform infrared (FT-IR) spectroscopy are described with specific emphasis on their role in bone cancer diagnostics. They can detect the changes which affect the body’s temperature with those of the molecular structure of cells and tissues of the body. The reflected infrared radiation from the affected areas of the body strongly depends on the metabolic steps of the cancer/or any other disease, which is also related to the structural changes at a molecular level of biological molecules during enzymatic or non enzymatic steps of the disease. The detection of the FT-IR spectral digital “marker bands” of the obtained changes of cell, liquids or tissue components derived from the disease in the check point could help to correlate with the corresponding temperature transferred to surface from the influenced site growth. The development of models, sensitive software, protocols and algorithms for early diagnosis of diseases, such as cancer, sarcomas, impending pathological fractures and histological diagnosis (biopsy) is of paramount importance specifically to the high heterogeneity and complex microenvironment of the human tissues [73–88]. In this respect, infrared thermal and infrared spectroscopic digital imaging data can be used to develop softwares that will be the fingerprint of specific diseases. Fingerprints are supported by computers and could be transferred to pixels for high resolution color classifications that will act as barcodes for early
There is no conflict of interest.
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Article Type: Review Paper
Date of acceptance: March 2022
Date of publication: March 2022
DOI: 10.5772/dmht.05
Copyright: The Author(s), Licensee IntechOpen, License: CC BY 4.0
© 2022 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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