This article has an accompanying continuing medical education activity, also eligible for MOC credit, on page e15. Learning Objective: Upon completion of this CME exercise, successful learners will be able to evaluate the potential of raster-scanning optoacoustic mesoscopy for gastrointestinal imaging. Scan the quick response (QR) code to the left with your mobile device to watch this article's video abstract and others. Don't have a QR code reader? Get one by searching 'QR Scanner' in your mobile device's app store.
Screening colonoscopy is crucial in reducing the mortality of colorectal cancer. However, detecting adenomas against the backdrop of an inflamed mucosa (e.g. in ulcerative colitis) remains exceedingly difficult. Therefore, we aimed to improve neoplastic lesion detection by employing a fluorescencebased endoscopic approach. We used the well-established murine AOM/DSS model to induce inflammation-driven carcinogenesis in the colon. In our diagnostic approach, we evaluated Chlorin e6 polyvinylpyrrolidone (Ce6-PVP)-based fluorescence endoscopy in comparison to standard whitelight endoscopy. A specialized pathologist then analyzed the histology of the detected lesions. Complementary in vitro studies were performed using human cell lines and a murine organoid system. Ce6-PVP-based fluorescence endoscopy had an improved detection rate of 100% (8/8) in detecting high-grade dysplasias and carcinomas over white-light detection alone with 75% (6/8). Trade-off for this superior detection rate was an increased rate of false positive lesions with an increase in the false discovery rate from 45% for white-light endoscopy to 81% for fluorescence endoscopy. We demonstrate in a proof-of-concept study that Ce6-PVP-based fluorescence endoscopy is a highly sensitive red flag technology to identify biopsy-worthy lesions in the colon. Achieving high adenoma detection rates during screening colonoscopy remains a formidable challenge as small or flat lesions are particularly difficult to detect 1-3. Among the technologies used to improve white-light endoscopy and increase detection rates, fluorescence-enhanced endoscopy has proven exceptionally promising. Specifically targeted fluorophores have been applied both systemically (intravenously) and topically (e.g. via enema) 4, 5 to detect dysplastic lesions in the colon with overall encouraging results. However, how to best identify relevant sites for biopsy in inflamed colonic mucosa, e.g. in inflammatory bowel diseases such as ulcerative colitis, remains an open question. It is generally accepted that the disease-specific risk for developing a colorectal carcinoma begins roughly 7 years after diagnosis of UC and a recent meta-analysis has supported that the risk for CRC is positively correlated with inflammatory activity 6. However, discerning non-neoplastic inflammatory alterations from neoplastic lesions during colonoscopy gets increasingly difficult with increasing inflammatory activity. Conflicting data on the best approach for surveillance strategies necessitate further research into emerging technologies such as fluorescence endoscopy.
Multi- and hyperspectral endoscopy are possibilities to improve the endoscopic detection of neoplastic lesions in the colon and rectum during colonoscopy. However, most studies in this context are performed on histological samples/biopsies or ex vivo. This leads to the question if previous results can be transferred to an in vivo setting. Therefore, the current study evaluated the usefulness of multispectral endoscopy in identifying neoplastic lesions in the colon. The data set consists of 25 mice with colonic neoplastic lesions and the data analysis is performed by machine learning. Another question addressed was whether adding additional spatial features based on Gauss–Laguerre polynomials leads to an improved detection rate. As a result, detection of neoplastic lesions was achieved with an MCC of 0.47. Therefore, the classification accuracy of multispectral colonoscopy is comparable with hyperspectral colonoscopy in the same spectral range when additional spatial features are used. Moreover, this paper strongly supports the current path towards the application of multi/hyperspectral endoscopy in clinical settings and shows that the challenges from transferring results from ex vivo to in vivo endoscopy can be solved.
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