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ID 116749
タイトル別表記
Cervical Cancer Treatment using AI
著者
Kano, Yosuke Tokushima Prefecture Naruto Hospital
キーワード
cervical cancer
automatic tumor contour segmentation
radiation therapy
diffusion-weighted imaging (DWI)
Dice similarity coefficient (DSC)
資料タイプ
学術雑誌論文
抄録
In cervical cancer treatment, radiation therapy is selected based on the degree of tumor progression, and radiation oncologists are required to delineate tumor contours. To reduce the burden on radiation oncologists, an automatic segmentation of the tumor contours would prove useful. To the best of our knowledge, automatic tumor contour segmentation has rarely been applied to cervical cancer treatment. In this study, diffusion-weighted images (DWI) of 98 patients with cervical cancer were acquired. We trained an automatic tumor contour segmentation model using 2D U-Net and 3D U-Net to investigate the possibility of applying such a model to clinical practice. A total of 98 cases were employed for the training, and they were then predicted by swapping the training and test images. To predict tumor contours, six prediction images were obtained after six training sessions for one case. The six images were then summed and binarized to output a final image through automatic contour segmentation. For the evaluation, the Dice similarity coefficient (DSC) and Hausdorff distance (HD) was applied to analyze the difference between tumor contour delineation by radiation oncologists and the output image. The DSC ranged from 0.13 to 0.93 (median 0.83, mean 0.77). The cases with DSC <0.65 included tumors with a maximum diameter < 40 mm and heterogeneous intracavitary concentration due to necrosis. The HD ranged from 2.7 to 9.6 mm (median 4.7 mm). Thus, the study confirmed that the tumor contours of cervical cancer can be automatically segmented with high accuracy.
掲載誌名
Journal of Radiation Research
ISSN
13499157
cat書誌ID
AA00705792
出版者
Oxford University Press|The Japanese Radiation Research Society|Japanese Society for Radiation Oncology
62
5
開始ページ
934
終了ページ
944
発行日
2021-08-14
権利情報
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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言語
eng
著者版フラグ
出版社版
部局
医学系