Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP)

Abstract

We report results of a study utilizing a novel tissue classification method, based on label-free spectral techniques, for the classification of lung cancer histopathological samples on a tissue microarray. The spectral diagnostic method allows reproducible and objective classification of unstained tissue sections. This is accomplished by acquiring infrared data sets containing thousands of spectra, each collected from tissue pixels ∼6 μm on edge; these pixel spectra contain an encoded snapshot of the entire biochemical composition of the pixel area. The hyperspectral data sets are subsequently decoded by methods of multivariate analysis that reveal changes in the biochemical composition between tissue types, and between various stages and states of disease. In this study, a detailed comparison between classical and spectral histopathology is presented, suggesting that spectral histopathology can achieve levels of diagnostic accuracy that is comparable to that of multipanel immunohistochemistry.

High-resolution FTIR imaging of colon tissues for elucidation of individual cellular and histopathological features

“…IR spectroscopy can provide information about these variations that can be used to identify, understand and in some cases even predict the possibility of the occurrence of a disease. In this regard, IR spectroscopy has been investigated as a potential cancer diagnostic tool in various tissue types including some highly prevalent cancers such as lung, 2 colon, [3][4][5][6][7] oral cavity, 8 liver, 9 prostate, [10][11][12] breast, [13][14][15] lymphnode, 16,17 cervix, 18 etc. Using IR spectroscopic imaging approaches, biological material can be imaged to obtain bio-molecular information, where each pixel of the image constitutes a spectrum with a specific bio-molecular signature.…”

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

“…Investigators are now focusing on patient issues and outcomes (126). Notably, recent studies show that it is possible to classify tissue into carcinoma and benign at human-competitive accuracy (127), relate the cancer detected to the most probable grade (128), and to prognosticate (129). …”

Label-free molecular imaging of the kidney

“…To date, oncology is the largest field of application to be explored by VS. Several types of cancer including melanoma and 170 brain metastasis, 171 as well as breast, 172 colon, 173 and lung cancer, 174 can be diagnosed by VS. In kidney research, VS has been used to evaluate renal cancers, which represent almost 2% of cancers worldwide.…”