In Vivo Diagnosis of Esophageal Cancer Using Image-Guided Raman Endoscopy and Biomolecular Modeling

Abstract

The aim of this work was to evaluate the biochemical foundation and clinical merit of multimodal image-guided Raman endoscopy technique for real-time in vivo diagnosis of cancer in the esophagus during clinical endoscopic examinations. A novel fiber-optic Raman endoscopy system was utilized for in vivo esophageal Raman measurements at 785 nm laser excitation within 0.5 second under the multimodal wide-field endoscopic imaging (white light reflectance (WLR) imaging, narrow-band imaging (NBI) and autofluorescence imaging (AFI) guidance. A total of 75 esophageal tissue sites from 27 patients were measured, in which 42 in vivo Raman spectra were from normal tissues and 33 in vivo Raman spectra were from malignant tumors as confirmed by histopathology. The biomolecular modeling (non-negativity-constrained least-squares minimization (NNCLSM) utilizing six basis reference spectra from the representative biochemicals ( i.e., actin, collagen, DNA, histones, triolein and glycogen) were employed to estimate the biochemical compositions of esophageal tissue. The resulting diagnostically significant fit coefficients were further utilized through linear discriminant analysis (LDA) and leave-one tissue site-out, cross validation method to develop diagnostic algorithms for esophageal cancer diagnosis. High-quality in vivo Raman spectra in the range of 800–1800 cm−1 can be acquired from normal and cancerous esophageal mucosa in real-time under multimodal endoscopic imaging guidance. Esophageal cancer tissue showed distinct Raman signals mainly associated with cell proliferation, lipid reduction, abnormal nuclear activity and neovasculation. The fit coefficients for actin, DNA, histones, triolein, and glycogen were found to be most significant for construction of the LDA diagnostic model, giving rise to an accuracy of 96.0% ( i.e., sensitivity of 97.0% and specificity of 95.2%) for in vivo diagnosis of esophageal cancer. This study demonstrates that multimodal image-guided Raman endoscopy technique in conjunction with biomolecular modeling has promising potential for the real-time, in vivo diagnosis and detection of esophageal cancer during clinical endoscopic examination.