Peer Reviewed: IR Spectroscopy in Clinical and Diagnostic Applications

Dubois, Janie; Shaw, R. Anthony

doi:10.1021/ac041647v

Cited by 39 publications

(54 citation statements)

References 27 publications

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“…Another feature which makes them attractive for modern clinical laboratories is that both methods can be automated. Recent reviews described several aspects in the field of IR and Raman spectroscopy such as biomedical applications to diagnose tissues [1], chemical imaging of biological tissue with synchrotron IR radiation [2], clinical and diagnostic applications [3], metabolic fingerprinting [4] and noninvasive biochemical analysis of single cells [5]. The progress in vibrational spectroscopy for medical diagnosis was summarized in a book that was divided into chapters about (i) the diagnosis of lymph nodes, (ii) individual human cells, (iii) micro-organisms, (iv) transmissible spongiform encephalopathy, (v) head and neck cancer, (vi) high-throughput histopathology, (vii) human cervix, (viii) esophageal and bladder, (ix) neuro-oncology and (x) erythrocytes [6].…”

Section: Introductionmentioning

confidence: 99%

Disease recognition by infrared and Raman spectroscopy

Krafft¹,

Steiner²,

Beleites³

et al. 2009

Journal of Biophotonics

265

175

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Infrared (IR) and Raman spectroscopy are emerging biophotonic tools to recognize various diseases. The current review gives an overview of the experimental techniques, data-classification algorithms and applications to assess soft tissues, hard tissues and body fluids. The methodology section presents the principles to combine vibrational spectroscopy with microscopy, lateral information and fiber-optic probes. A crucial step is the classification of spectral data by a variety of algorithms. We discuss unsupervised algorithms such as cluster analysis or principal component analysis and supervised algorithms such as linear discriminant analysis, soft independent modeling of class analogies, artificial neural networks support vector machines, Bayesian classification, partial least-squares regression and ensemble methods. The selected topics include tumors of epithelial tissue, brain tumors, prion diseases, bone diseases, atherosclerosis, kidney stones and gallstones, skin tumors, diabetes and osteoarthritis.

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Section: Introductionmentioning

confidence: 99%

Disease recognition by infrared and Raman spectroscopy

Krafft¹,

Steiner²,

Beleites³

et al. 2009

Journal of Biophotonics

265

175

View full text Add to dashboard Cite

show abstract

“…Nevertheless, available morphological data can in many cases be insufficient for an accurate verification of the pathological (tumor) process so that a conclusion about whether the tumor is benign or malignant is presumptuous in nature [2]. Because fundamental life processes, from single-celled organisms to man, are carried out on the molecular level, novel methods that investigate the pathology of organs on the structural and molecular interaction level are being developed in addition to the aforementioned biomedical diagnostic methods in order to detect the signatures of the presence of a malignant pathology.Formation and metamorphosis of a tumor can be detected in IR spectra of proteins, nucleic acids, lipids, and hydrocarbons because any oncological disease is accompanied by biochemical changes in these molecular cell components of the human body [3,4]. As a result, traditional methods of vibrational spectroscopy are viewed as effective…”

mentioning

confidence: 99%

“…Formation and metamorphosis of a tumor can be detected in IR spectra of proteins, nucleic acids, lipids, and hydrocarbons because any oncological disease is accompanied by biochemical changes in these molecular cell components of the human body [3,4]. As a result, traditional methods of vibrational spectroscopy are viewed as effective…”

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confidence: 99%

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IR spectroscopic methods for diagnosis of oncological pathologies in human tissues (Review)

2009

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Modern problems in the diagnosis of oncological pathologies using spectroscopic methods of analysis are considered. Fourier-transform IR spectroscopy methods are illustrated by investigation of tissues of breast, thyroid gland, stomach, kidney, lung, and skin excised during surgical intervention. IR spectra of surgical material are compared with data of histological analysis. Spectra of proteins and lipids in malignant neoplasms differ from those in benign tumors and in tissues beyond the pathological focus. Differences in protein spectra are attributed to changes in the supramolecular structure due to cleavage of intramolecular C=OH-N hydrogen bonds. Differences in IR spectra of lipids in neoplasms, when compared with those in normal tissues, are caused by changes in the structure of side chains of fatty-acid radicals appearing in malignant tumors. Spectral signatures of malignant pathology are revealed.Introduction. Timely detection of oncological pathology is of prime importance for selecting effective methods for treating oncological diseases. However, the diagnosis of malignant neoplasms is a very complicated aspect of oncology because tumors often manifest clinically as various symptoms, especially in early stages.The essence of the problem is that diagnostic methods currently used in medical practice such as visual, palpation, ultrasound, and x-ray, in addition to MRI and CT are capable in principle of detecting only a tumorous mass. The final conclusion about whether the detected pathology is benign or malignant is made based on morphological investigations. A correct diagnosis is possible only with careful adherence to procedures for obtaining and processing the material to be analyzed. Important considerations for a reliable diagnosis are subjective factors such as the special professional training and experience of the surgeon and a highly qualified pathologist.The morphological diagnosis of a tumor is established based on a whole set of signatures such as cytological characteristics, cell topography, their relationships to basal membranes, vessels, and the condition of the stroma, which acts as a mediator between neoplasms and the organism as a whole. Morphological signatures of malignancy are idiosyncratic to each organ and tissue and can vary considerably. Therefore, both clinical data and results of laboratory tests are very significant for a differential diagnosis of malignant tumors and elucidation of the factors stimulating malignant growth. Information about the tumor location, its growth rate, and the age of the patient can in several instances play a decisive role in the morphological diagnosis [1]. Nevertheless, available morphological data can in many cases be insufficient for an accurate verification of the pathological (tumor) process so that a conclusion about whether the tumor is benign or malignant is presumptuous in nature [2]. Because fundamental life processes, from single-celled organisms to man, are carried out on the molecular level, novel methods that investigate the pathology o...

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“…Because of its sensitivity to both molecular structure and molecular interactions, the infrared spectrum is referred as chemical fingerprint of the sample. Consequently, infrared spectroscopy was frequently utilized as a diagnostic tool for the detection of biochemical processes and even diseases (19)(20)(21). Infrared spectroscopy has also become a versatile tool in microbiology as a method for the discrimination of microorganism (22,23).…”

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confidence: 99%

Rapid and label‐free classification of human glioma cells by infrared spectroscopic imaging

et al. 2008

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The discrimination of cell types is a crucial task in cell biology. Available techniques, based on an irreversible treatment of the cells, do not allow a sensitive label-free characterization under in situ conditions. Infrared spectroscopic imaging is a new and useful tool for studying individual cells. It has established itself as a powerful method to probe the molecular composition and to indicate the biochemistry of cells. Monolayers of cultivated U343, T1115 and T508 human glioma cells were characterized using infrared spectroscopic imaging. A classification algorithm based on linear discriminant analysis was developed to distinguish different cells without labeling. The classification is based upon spectral features which mainly arise from proteins, nucleic acids, and cholesterol. An accuracy of 91% and 84% was obtained for cells of U343 and T1115, respectively. Cells of the T508 cell line exhibit some misclassifications resulting in a lower accuracy rate of 73%. As the results demonstrate, the potential of infrared spectroscopic imaging method to assess the overall molecular composition of cells in a non-destructive manner opens the possibility to characterize cells on a molecular level without labels or an irreversible treatment. '

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Peer Reviewed: IR Spectroscopy in Clinical and Diagnostic Applications

Abstract: IR spectroscopy's sensitivity to molecularstructure and interactions provides a "molecular fingerprint", which is the basis for biomedical applications.

Cited by 39 publications

References 27 publications

Disease recognition by infrared and Raman spectroscopy

Disease recognition by infrared and Raman spectroscopy

IR spectroscopic methods for diagnosis of oncological pathologies in human tissues (Review)

Rapid and label‐free classification of human glioma cells by infrared spectroscopic imaging

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