Department of Engineering Physics, Polytechnique Montreal, Montreal, Quebec, Canada.
Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), Montreal, Quebec, Canada.
J Biophotonics. 2022 Feb;15(2):e202100198. doi: 10.1002/jbio.202100198. Epub 2021 Dec 7.
Up to 70% of ovarian cancer patients are diagnosed with advanced-stage disease and the degree of cytoreduction is an important survival prognostic factor. The aim of this study was to evaluate if Raman spectroscopy could detect cancer from different organs within the abdominopelvic region, including the ovaries. A Raman spectroscopy probe was used to interrogate specimens from a cohort of nine patients undergoing cytoreductive surgery, including four ovarian cancer patients and three patients with endometrial cancer. A feature-selection algorithm was developed to determine which spectral bands contributed to cancer detection and a machine-learning model was trained. The model could detect cancer using only eight spectral bands. The receiver-operating-characteristic curve had an area-under-the-curve of 0.96, corresponding to an accuracy, a sensitivity and a specificity of 90%, 93% and 88%, respectively. These results provide evidence multispectral Raman spectroscopy could be developed to detect ovarian cancer intraoperatively.
多达 70%的卵巢癌患者被诊断为晚期疾病,肿瘤细胞减灭术的程度是一个重要的生存预后因素。本研究旨在评估拉曼光谱是否可以检测腹盆腔内不同器官的癌症,包括卵巢。使用拉曼光谱探头对 9 名接受细胞减灭术的患者的标本进行检测,其中包括 4 名卵巢癌患者和 3 名子宫内膜癌患者。开发了一种特征选择算法来确定哪些光谱带有助于癌症检测,并训练了一个机器学习模型。该模型仅使用 8 个光谱带即可检测癌症。受试者工作特征曲线下面积为 0.96,对应于 90%的准确率、93%的灵敏度和 88%的特异性。这些结果为多光谱拉曼光谱术可用于术中检测卵巢癌提供了证据。