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Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy

 Hwa Kyung Byun  ;  Jee Suk Chang  ;  Min Seo Choi  ;  Jaehee Chun  ;  Jinhong Jung  ;  Chiyoung Jeong  ;  Jin Sung Kim  ;  Yongjin Chang  ;  Seung Yeun Chung  ;  Seungryul Lee  ;  Yong Bae Kim 
 RADIATION ONCOLOGY, Vol.16(1) : 203, 2021-10 
Journal Title
Issue Date
Autocontouring ; Breast ; Organs at risk ; Radiotherapy
Purpose: To study the performance of a proposed deep learning-based autocontouring system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts.

Methods: Eleven experts from two institutions delineated nine OARs in 10 cases of adjuvant radiotherapy after breast-conserving surgery. Autocontours were then provided to the experts for correction. Overall, 110 manual contours, 110 corrected autocontours, and 10 autocontours of each type of OAR were analyzed. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to compare the degree of agreement between the best manual contour (chosen by an independent expert committee) and each autocontour, corrected autocontour, and manual contour. Higher DSCs and lower HDs indicated a better geometric overlap. The amount of time reduction using the autocontouring system was examined. User satisfaction was evaluated using a survey.

Results: Manual contours, corrected autocontours, and autocontours had a similar accuracy in the average DSC value (0.88 vs. 0.90 vs. 0.90). The accuracy of autocontours ranked the second place, based on DSCs, and the first place, based on HDs among the manual contours. Interphysician variations among the experts were reduced in corrected autocontours, compared to variations in manual contours (DSC: 0.89-0.90 vs. 0.87-0.90; HD: 4.3-5.8 mm vs. 5.3-7.6 mm). Among the manual delineations, the breast contours had the largest variations, which improved most significantly with the autocontouring system. The total mean times for nine OARs were 37 min for manual contours and 6 min for corrected autocontours. The results of the survey revealed good user satisfaction.

Conclusions: The autocontouring system had a similar performance in OARs as that of the experts' manual contouring. This system can be valuable in improving the quality of breast radiotherapy and reducing interphysician variability in clinical practice.
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1. College of Medicine (의과대학) > Dept. of Radiation Oncology (방사선종양학교실) > 1. Journal Papers
Yonsei Authors
Kim, Yong Bae(김용배) ORCID logo https://orcid.org/0000-0001-7573-6862
Kim, Jinsung(김진성) ORCID logo https://orcid.org/0000-0003-1415-6471
Byun, Hwa Kyung(변화경) ORCID logo https://orcid.org/0000-0002-8964-6275
Chang, Jee Suk(장지석) ORCID logo https://orcid.org/0000-0001-7685-3382
Chung, Seung Yeun(정승연) ORCID logo https://orcid.org/0000-0002-3877-6950
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