Identification of Metastatic Lymph Nodes in MR Imaging with Faster Region-Based Convolutional Neural Networks

MRI is the gold standard for confirming a pelvic lymph node metastasis diagnosis. Traditionally, medical radiologists have analyzed MRI image features of regional lymph nodes to make diagnostic decisions based on their subjective experience; this diagnosis lacks objectivity and accuracy. This study...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2018-09, Vol.78 (17), p.5135-5143
Hauptverfasser: Lu, Yun, Yu, Qiyue, Gao, Yuanxiang, Zhou, Yunpeng, Liu, Guangwei, Dong, Qian, Ma, Jinlong, Ding, Lei, Yao, Hongwei, Zhang, Zhongtao, Xiao, Gang, An, Qi, Wang, Guiying, Xi, Jinchuan, Yuan, Weitang, Lian, Yugui, Zhang, Dianliang, Zhao, Chunbo, Yao, Qin, Liu, Wei, Zhou, Xiaoming, Liu, Shuhao, Wu, Qingyao, Xu, Wenjian, Zhang, Jianli, Wang, Dongshen, Sun, Zhenqing, Gao, Yuan, Zhang, Xianxiang, Hu, Jilin, Zhang, Maoshen, Wang, Guanrong, Zheng, Xuefeng, Wang, Lei, Zhao, Jie, Yang, Shujian
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Sprache:eng
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Zusammenfassung:MRI is the gold standard for confirming a pelvic lymph node metastasis diagnosis. Traditionally, medical radiologists have analyzed MRI image features of regional lymph nodes to make diagnostic decisions based on their subjective experience; this diagnosis lacks objectivity and accuracy. This study trained a faster region-based convolutional neural network (Faster R-CNN) with 28,080 MRI images of lymph node metastasis, allowing the Faster R-CNN to read those images and to make diagnoses. For clinical verification, 414 cases of rectal cancer at various medical centers were collected, and Faster R-CNN-based diagnoses were compared with radiologist diagnoses using receiver operating characteristic curves (ROC). The area under the Faster R-CNN ROC was 0.912, indicating a more effective and objective diagnosis. The Faster R-CNN diagnosis time was 20 s/case, which was much shorter than the average time (600 s/case) of the radiologist diagnoses. Faster R-CNN enables accurate and efficient diagnosis of lymph node metastases. .
ISSN:0008-5472
1538-7445
DOI:10.1158/0008-5472.CAN-18-0494