| Literature DB >> 33436684 |
Marcelo Saito Nogueira1,2, Siddra Maryam3,4, Michael Amissah3,4, Huihui Lu3, Noel Lynch5, Shane Killeen5, Micheal O'Riordain5, Stefan Andersson-Engels3,4.
Abstract
Colorectal cancer (CRC) is the third most common type of cancer worldwide and the second most deadly. Recent research efforts have focused on developing non-invasive techniques for CRC detection. In this study, we evaluated the diagnostic capabilities of diffuse reflectance spectroscopy (DRS) for CRC detection by building 6 classification models based on support vector machines (SVMs). Our dataset consists of 2889 diffuse reflectance spectra collected from freshly excised ex vivo tissues of 47 patients over wavelengths ranging from 350 and 1919 nm with source-detector distances of 630-µm and 2500-µm to probe different depths. Quadratic SVMs were used and performance was evaluated using twofold cross-validation on 10 iterations of randomized training and test sets. We achieved (93.5 ± 2.4)% sensitivity, (94.0 ± 1.7)% specificity AUC by probing the superficial colorectal tissue and (96.1 ± 1.8)% sensitivity, (95.7 ± 0.6)% specificity AUC by sampling deeper tissue layers. To the best of our knowledge, this is the first DRS study to investigate the potential of probing deeper tissue layers using larger SDD probes for CRC detection in the luminal wall. The data analysis showed that using a broader spectrum and longer near-infrared wavelengths can improve the diagnostic accuracy of CRC as well as probing deeper tissue layers.Entities:
Year: 2021 PMID: 33436684 PMCID: PMC7804163 DOI: 10.1038/s41598-020-79517-2
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379