Deep learning pathological microscopic features in endemic nasopharyngeal cancer: Prognostic value and protentional role for individual induction chemotherapy. (20th December 2019)

• Record Type: Journal Article
• Authors: Liu, Kuiyuan; Xia, Weixiong; Qiang, Mengyun; Chen, Xi; Liu, Jia; Guo, Xiang; Lv, Xing
• Is Part Of: Cancer medicine. Volume 9:Number 4(2020)
• Page Start: 1298
• Page End: 1306
• Publication Date: 2019-12-20
• Subjects: DeepSurv -- induction chemotherapy -- nasopharyngeal carcinoma -- pathological microfeatures; 616.994005
• DOI: 10.1002/cam4.2802
• Languages: English
• ISSNs: 2045-7634

Abstract

Abstract: Background: To explore the prognostic value and the role for treatment decision of pathological microscopic features in patients with nasopharyngeal carcinoma (NPC) using the method of deep learning. Methods: The pathological microscopic features were extracted using the software QuPath (version 0.1.3. Queen's University) in the training cohort (Guangzhou training cohort, n = 843). We used the neural network DeepSurv to analyze the pathological microscopic features (DSPMF) and then classified patients into high‐risk and low‐risk groups through the time‐dependent receiver operating characteristic (ROC). The prognosis accuracy of the pathological feature was validated in a validation cohort (n = 212). The primary endpoint was progression‐free survival (PFS). Results: We found 429 pathological microscopic features in the H&E image. Patients with high‐risk scores in the training cohort had shorter 5‐year PFS (HR 10.03, 6.06‐16.61; P < .0001). The DSPMF (C‐index: 0.723) had the higher C‐index than the EBV DNA (C‐index: 0.612) copies and the N stage (C‐index: 0.593). Furthermore, induction chemotherapy (ICT) plus concomitant chemoradiotherapy (CCRT) had better 5‐year PFS to those received CCRT ( P < .0001) in the high‐risk group. Conclusion: The DSPMF is a reliable prognostic tool for survival risk in patients with NPC and might be able to guide the treatment decision. Abstract : The research of this paper is time‐effective, innovative, and practical. It may help clinician to judge the prognosis of the patients with NPC and guide the treatment decision.