Computer-Assisted Differentiation between Colon-Mesocolon and Retroperitoneum Using Hyperspectral Imaging (HSI) Technology

Abstract

Complete mesocolic excision (CME), which involves the adequate resection of the tumor-bearing colonic segment with “en bloc” removal of its mesocolon along embryological fascial planes is associated with superior oncological outcomes. However, CME presents a higher complication rate compared to non-CME resections due to a higher risk of vascular injury. Hyperspectral imaging (HSI) is a contrast-free optical imaging technology, which facilitates the quantitative imaging of physiological tissue parameters and the visualization of anatomical structures. This study evaluates the accuracy of HSI combined with deep learning (DL) to differentiate the colon and its mesenteric tissue from retroperitoneal tissue. In an animal study including 20 pig models, intraoperative hyperspectral images of the sigmoid colon, sigmoid mesentery, and retroperitoneum were recorded. A convolutional neural network (CNN) was trained to distinguish the two tissue classes using HSI data, validated with a leave-one-out cross-validation process. The overall recognition sensitivity of the tissues to be preserved (retroperitoneum) and the tissues to be resected (colon and mesentery) was 79.0 ± 21.0% and 86.0 ± 16.0%, respectively. Automatic classification based on HSI and CNNs is a promising tool to automatically, non-invasively, and objectively differentiate the colon and its mesentery from retroperitoneal tissue.

Artificial intelligence in improving the outcome of surgical treatment in colorectal cancer

“…By combining HSI and CNN trained with deep learning on porcine models, Okamoto et al. obtained an automatic distinction of different anatomical layers in CRC surgery, achieving a recognition sensitivity of 79.0 ± 21.0% for the retroperitoneum and 86.0 ± 16.0% for the colon and mesentery ( 25 )..These results are promising in improving the results of complete mesocolic excision, by lowering the complications associated with it (like lesions of the ureter, gonadal vessels)and offering a better oncologic result.…”

In Vitro Antibody Quantification with Hyperspectral Imaging in a Large Field of View for Clinical Applications

“…HSI is a non-invasive, contrast-free tool recently applied in several medical and basic research fields [ 5 , 6 ], like other new emerging technologies [ 7 , 8 ]. Several innovative approaches are under investigation that exploit the capability of HSI to “see beyond” the visible range, such as intraoperative tissue recognition [ 9 ], therapy guidance, and monitoring [ 10 , 11 , 12 , 13 , 14 ].…”