Advancing precise diagnosis of nasopharyngeal carcinoma through endoscopy-based radiomics analysis
Yun Xu,
Jiesong Wang,
Chenxin Li,
Yong Su,
Hewei Peng,
Lanyan Guo,
Shaojun Lin,
Jingao Li,
Dan Wu
Affiliations
Yun Xu
Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China; Fujian Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian, China
Jiesong Wang
Department of Lymphoma & Head and Neck Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China
Chenxin Li
Department of Electrical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China
Yong Su
Department of Radiation Oncology, Jiangxi Cancer Hospital, Jiangxi, China; National Health Commission (NHC) Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal Carcinoma (Jiangxi Cancer Hospital of Nanchang University), Nanchang, China
Hewei Peng
Department of Epidemiology and Health Statistics, Fujian Provincial Key Laboratory of Environment Factors and Cancer, School of Public Health, Fujian Medical University, Fuzhou, China
Lanyan Guo
School of Medical Imaging, Fujian Medical University, Fuzhou, China
Shaojun Lin
Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China; Fujian Key Laboratory of Translational Cancer Medicine, Fuzhou, Fujian, China
Jingao Li
Department of Radiation Oncology, Jiangxi Cancer Hospital, Jiangxi, China; National Health Commission (NHC) Key Laboratory of Personalized Diagnosis and Treatment of Nasopharyngeal Carcinoma (Jiangxi Cancer Hospital of Nanchang University), Nanchang, China
Dan Wu
Tianjin Key Laboratory of Human Development and Reproductive Regulation, Tianjin Central Hospital of Gynecology Obstetrics and Nankai University Affiliated Hospital of Obstetrics and Gynecology, Tianjin, China; Tianjin Cancer Institute, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin, China; Corresponding author
Summary: Nasopharyngeal carcinoma (NPC) has high metastatic potential and is hard to detect early. This study aims to develop a deep learning model for NPC diagnosis using optical imagery. From April 2008 to May 2021, we analyzed 12,087 nasopharyngeal endoscopic images and 309 videos from 1,108 patients. The pretrained model was fine-tuned with stochastic gradient descent on the final layers. Data augmentation was applied during training. Videos were converted to images for malignancy scoring. Performance metrics like AUC, accuracy, and sensitivity were calculated based on the malignancy score. The deep learning model demonstrated high performance in identifying NPC, with AUC values of 0.981 (95% confidence of interval [CI] 0.965–0.996) for the Fujian Cancer Hospital dataset and 0.937 (0.905–0.970) for the Jiangxi Cancer Hospital dataset. The proposed model effectively diagnoses NPC with high accuracy, sensitivity, and specificity across multiple datasets. It shows promise for early NPC detection, especially in identifying latent lesions.
