Development and validation of a fully automatic tissue delineation model for brain metastasis using a deep neural network

被引:1
作者
Zhao, Jie-Yi [1 ]
Cao, Qi [2 ]
Chen, Jing [1 ]
Chen, Wei [3 ]
Du, Si-Yu [4 ]
Yu, Jie [5 ]
Zeng, Yi-Miao [4 ]
Wang, Shu-Min [4 ]
Peng, Jing-Yu [4 ]
You, Chao [1 ]
Xu, Jian-Guo [1 ]
Wang, Xiao-Yu [1 ]
机构
[1] Sichuan Univ, West China Hosp, Dept Neurosurg, 37 Guoxue Lane, Chengdu 610041, Peoples R China
[2] Sichuan Univ, West China Univ Hosp 2, Dept Reprod Med Ctr, Chengdu, Peoples R China
[3] Sichuan Univ, West China Hosp, Biomed Big Data Ctr, Chengdu, Peoples R China
[4] Sichuan Univ, West China Sch Med, Chengdu, Peoples R China
[5] Sichuan Univ, West China Sch Publ Hlth, Chengdu, Peoples R China
关键词
Brain metastases; deep neural network; tissue segmentation; magnetic resonance imaging (MRI); Gamma Knife plan; STEREOTACTIC RADIOSURGERY; SEGMENTATION; MANAGEMENT;
D O I
10.21037/qims-22-1216
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: Stereotactic radiosurgery ( SRS) treatment planning requires accurate delineation of brain metastases, a task that can be tedious and time-consuming. Although studies have explored the use of convolutional neural networks (CNNs) in magnetic resonance imaging (MRI) for automatic brain metastases delineation, none of these studies have performed clinical evaluation, raising concerns about clinical applicability. This study aimed to develop an artificial intelligence (AI) tool for the automatic delineation of single brain metastasis that could be integrated into clinical practice. Methods: Data from 426 patients with postcontrast T1-weighted MRIs who underwent SRS between March 2007 and August 2019 were retrospectively collected and divided into training, validation, and testing cohorts of 299, 42, and 85 patients, respectively. Two Gamma Knife (GK) surgeons contoured the brain metastases as the ground truth. A novel 2.5D CNN network was developed for single brain metastasis delineation. The mean Dice similarity coefficient (DSC) and average surface distance (ASD) were used to assess the performance of this method. Results: The mean DSC and ASD values were 88.34%+/- 5.00% and 0.35 +/- 0.21 mm, respectively, for the contours generated with the AI tool based on the testing set. The DSC measure of the AI tool's performance was dependent on metastatic shape, reinforcement shape, and the existence of peritumoral edema (all P values <0.05). The clinical experts' subjective assessments showed that 415 out of 572 slices (72.6%) in the testing cohort were acceptable for clinical usage without revision. The average time spent editing an AI-generated contour compared with time spent with manual contouring was 74 vs. 196 seconds, respectively (P<0.01). Conclusions: The contours delineated with the AI tool for single brain metastasis were in close agreement with the ground truth. The developed AI tool can effectively reduce contouring time and aid in GK treatment planning of single brain metastasis in clinical practice.
引用
收藏
页码:6724 / 6734
页数:11
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