Esophageal cancer has seen an increase in incidence in recent decades; early intervention is key in improving patient outcomes. As a result screening techniques must be improved in order to detect early cancer and dysplasia endoscopically. Polarized light imaging (PLI) and optical coherence tomography (OCT) are of interest due to their capabilities to probe microstructural tissue properties.
In this study healthy and cancerous esophageal tissue samples are imaged with PLI and OCT systems. Classification algorithms are developed to identify polarimetric properties from PLI and Haralick texture features from OCT which are key in distinguishing between the healthy and diseased tissue.
Esophageal cancer’s increasing prevalence coupled with a 5-year average survival rate below 20% due largely to late detection indicates a significant need for improved imaging tools that can detect and localize early, unseen lesions and be incorporated into endoscopy for screening and evaluation of early symptoms. While white light imaging or virtual chromoendoscopy contrast-enhancement techniques like narrow-band imaging have largely seen commercialization, there remain emerging label-free imaging-based techniques that show promise for improving diagnosis and biopsy guidance. Among them we investigate the clinical potential of hyperspectral (HSI) and autofluorescence imaging (AFI) which lend themselves well to implementation in an endoscopic system. We performed ex-vivo imaging on esophageal biopsies suspicious for carcinoma (N=11) and/or Barrett’s esophagus (N=6) and adjacent normal appearing squamous mucosa in the same patient as controls. Our results indicate AFI and HSI are both promising imaging modalities for detecting and localizing morphological and metabolic changes associated with esophageal cancer.
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