Fourier transform infrared imaging spectroscopy of collagen deposition after myocardial infarction

Cheheltani, Rabee; Wang, B.; Sabri, Abdel Karim; Pleshko, Nancy; Kiani, Mohammad F.

doi:10.1109/nebc.2012.6207086

Cited by 1 publication

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“…Several studies related to cardiovascular systems have reported spectral analysis of tissue and disease in terms of resulting biochemical changes. Infrared imaging has been used to study calcifications in aortic valve[ 18 ], for characterizing heart valves [ 19 ], studying diabetes induced changes in myocardium and vessels[ 20 – 23 ], for analyzing cardiac extracellular matrix (ECM) remodeling[ 24 ]; and ECM and serum components following myocardial infarction[ 25 – 28 ]. While these studies successfully demonstrate differentiation between diseased and healthy tissue via lipid and protein composition and collagen content, a histologic analysis consistent with existing pathology practice is lacking.…”

Section: Introductionmentioning

confidence: 99%

Computational Chemical Imaging for Cardiovascular Pathology: Chemical Microscopic Imaging Accurately Determines Cardiac Transplant Rejection

et al. 2015

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Rejection is a common problem after cardiac transplants leading to significant number of adverse events and deaths, particularly in the first year of transplantation. The gold standard to identify rejection is endomyocardial biopsy. This technique is complex, cumbersome and requires a lot of expertise in the correct interpretation of stained biopsy sections. Traditional histopathology cannot be used actively or quickly during cardiac interventions or surgery. Our objective was to develop a stain-less approach using an emerging technology, Fourier transform infrared (FT-IR) spectroscopic imaging to identify different components of cardiac tissue by their chemical and molecular basis aided by computer recognition, rather than by visual examination using optical microscopy. We studied this technique in assessment of cardiac transplant rejection to evaluate efficacy in an example of complex cardiovascular pathology. We recorded data from human cardiac transplant patients’ biopsies, used a Bayesian classification protocol and developed a visualization scheme to observe chemical differences without the need of stains or human supervision. Using receiver operating characteristic curves, we observed probabilities of detection greater than 95% for four out of five histological classes at 10% probability of false alarm at the cellular level while correctly identifying samples with the hallmarks of the immune response in all cases. The efficacy of manual examination can be significantly increased by observing the inherent biochemical changes in tissues, which enables us to achieve greater diagnostic confidence in an automated, label-free manner. We developed a computational pathology system that gives high contrast images and seems superior to traditional staining procedures. This study is a prelude to the development of real time in situ imaging systems, which can assist interventionists and surgeons actively during procedures.

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