An Artificial Intelligence System for the Detection of Bladder Cancer via Cystoscopy: A Multicenter Diagnostic Study

Autor: Jian Huang, Wen Dong, Zeshi Chen, Zhiwen Chen, Xuefan Yang, Baorui Yuan, Yonghai Zhang, Hongbing Mei, Jiexin Pan, Qiang Lv, Hao Chen, Xiayao Diao, Wenjian Liao, Tianxin Lin, Xiaozhou Zhou, Chenglong Wu, Rui-Yun Zhang, Haotian Lin, Shaoxu Wu, Yuanfeng Zhang, Haige Chen, Guang Qian, Xiong Chen, Shizhong Xu
Rok vydání: 2021
Předmět:
Zdroj: JNCI: Journal of the National Cancer Institute. 114:220-227
ISSN: 1460-2105
0027-8874
Popis: Background Cystoscopy plays an important role in bladder cancer (BCa) diagnosis and treatment, but its sensitivity needs improvement. Artificial intelligence has shown promise in endoscopy, but few cystoscopic applications have been reported. We report a Cystoscopy Artificial Intelligence Diagnostic System (CAIDS) for BCa diagnosis. Methods In total, 69 204 images from 10 729 consecutive patients from 6 hospitals were collected and divided into training, internal validation, and external validation sets. The CAIDS was built using a pyramid scene parsing network and transfer learning. A subset (n = 260) of the validation sets was used for a performance comparison between the CAIDS and urologists for complex lesion detection. The diagnostic accuracy, sensitivity, specificity, and positive and negative predictive values and 95% confidence intervals (CIs) were calculated using the Clopper-Pearson method. Results The diagnostic accuracies of the CAIDS were 0.977 (95% CI = 0.974 to 0.979) in the internal validation set and 0.990 (95% CI = 0.979 to 0.996), 0.982 (95% CI = 0.974 to 0.988), 0.978 (95% CI = 0.959 to 0.989), and 0.991 (95% CI = 0.987 to 0.994) in different external validation sets. In the CAIDS vs urologists’ comparisons, the CAIDS showed high accuracy and sensitivity (accuracy = 0.939, 95% CI = 0.902 to 0.964; sensitivity = 0.954, 95% CI = 0.902 to 0.983) with a short latency of 12 seconds, much more accurate and quicker than the expert urologists. Conclusions The CAIDS achieved accurate BCa detection with a short latency. The CAIDS may provide many clinical benefits, from increasing the diagnostic accuracy for BCa, even for commonly misdiagnosed cases such as flat cancerous tissue (carcinoma in situ), to reducing the operation time for cystoscopy.
Databáze: OpenAIRE
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