Young oncologists benefit more than experts from deep learning-based organs-at-risk contouring modeling in nasopharyngeal carcinoma radiotherapy: A multi-institution clinical study exploring working experience and institute group style factor

被引：2

作者：

Song, Ying ^{[1
,2
]}

Hu, Junjie ^{[2
]}

Wang, Qiang ^{[1
,2
]}

Yu, Chengrong ^{[2
]}

Su, Jiachong ^{[1
]}

Chen, Lin ^{[1
]}

Jiang, Xiaorui ^{[3
]}

Chen, Bo ^{[3
]}

Zhang, Lei ^{[4
]}

Yu, Qian ^{[4
]}

Li, Ping ^{[1
]}

Wang, Feng ^{[1
]}

Bai, Sen ^{[1
]}

Luo, Yong ^{[1
]}

Yi, Zhang ^{[2
]}

机构：

[1] Sichuan Univ, West China Hosp, Canc Ctr, 37 Guo Xue Alley, Chengdu 610065, Peoples R China

[2] Sichuan Univ, Coll Comp Sci, Machine Intelligence Lab, 24 South Sect 1 First Ring Rd, Chengdu 610065, Peoples R China

[3] First Peoples Hosp Chengdu, Dept Oncol, 18 Wanxiang North Rd High-tech Zone, Chengdu 610041, Peoples R China

[4] Second Peoples Hosp Chengdu, Dept Oncol, Chengdu, Peoples R China

来源：

CLINICAL AND TRANSLATIONAL RADIATION ONCOLOGY | 2023年 / 41卷

关键词：

Deep learning; Contouring; Organs; -at; -risk; Nasopharyngeal carcinoma radiotherapy; Working experience; SEGMENTATION; DELINEATION; HEAD;

D O I：

10.1016/j.ctro.2023.100635

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Background: To comprehensively investigate the behaviors of oncologists with different working experiences and institute group styles in deep learning-based organs-at-risk (OAR) contouring. Methods: A deep learning-based contouring system (DLCS) was modeled from 188 CT datasets of patients with nasopharyngeal carcinoma (NPC) in institute A. Three institute oncology groups, A, B, and C, were included; each contained a beginner and an expert. For each of the 28 OARs, two trials were performed with manual contouring first and post-DLCS edition later, for ten test cases. Contouring performance and group consistency were quantified by volumetric and surface Dice coefficients. A volume-based and a surface-based oncologist satisfaction rate (VOSR and SOSR) were defined to evaluate the oncologists' acceptance of DLCS.Results: Based on DLCS, experience inconsistency was eliminated. Intra-institute consistency was eliminated for group C but still existed for group A and group B. Group C benefits most from DLCS with the highest number of improved OARs (8 for volumetric Dice and 10 for surface Dice), followed by group B. Beginners obtained more numbers of improved OARs than experts (7 v.s. 4 in volumetric Dice and 5 v.s. 4 in surface Dice). VOSR and SOSR varied for institute groups, but the rates of beginners were all significantly higher than those of experts for OARs with experience group significance. A remarkable positive linear relationship was found between VOSR and post-DLCS edition volumetric Dice with a coefficient of 0.78. Conclusions: The DLCS was effective for various institutes and the beginners benefited more than the experts.

引用

页数：9