机构:[1]Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA[2]Department of Radiation Oncology, Sichuan Cancer Hospital, Chengdu, China四川省肿瘤医院[3]Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China浙江省肿瘤医院[4]Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA[5]Department of Radiation Oncology, Xiangya Hospital, Central South University, Changsha, China
Purpose: We evaluated the feasibility of using an automatic segmentation tool to delineate cardiac substructures from noncontrast computed tomography (CT) images for cardiac dosimetry and toxicity analyses for patients with nonsmall cell lung cancer (NSCLC) after radiotherapy.Material and methods: We used an in-house developed multi-atlas segmentation tool to delineate 11cardiac substructures, including the whole heart, four heart chambers, and six greater vessels, automatically from the averaged 4D-CT planning images of 49 patients with NSCLC. Two experienced radiation oncologists edited the auto-segmented contours. Times for automatic segmentation and modification were recorded. The modified contours were compared with the auto-segmented contours in terms of Dice similarity coefficient (DSC) and mean surface distance (MSD) to evaluate the extent of modification. Differences in dose-volume histogram (DVH) characteristics were also evaluated for the modified versus auto-segmented contours.Results: The mean automatic segmentation time for all 11 structures was 7-9min. For the 49 patients, the mean DSC values (SD) ranged from .73 +/-.08 to .95 +/-.04, and the mean MSD values ranged from 1.3 +/-.6mm to 2.9 +/- 5.1mm. Overall, the modifications were small; the largest modifications were in the pulmonary vein and the inferior vena cava. The heart V30 (volume receiving dose 30Gy) and the mean dose to the whole heart and the four heart chambers were not different for the modified versus the auto-segmented contours based on the statistically significant condition of p<.05. Also, the maximum dose to the great vessels was no different except for the pulmonary vein.Conclusions: Automatic segmentation of cardiac substructures did not require substantial modifications. Dosimetric evaluation showed no significant difference between the auto-segmented and modified contours for most structures, which suggests that the auto-segmented contours can be used to study cardiac dose-responses in clinical practice.
基金:
University of Texas MD Anderson Cancer Center Institutional Research Grant (IRG) Program; University of Texas MD Anderson Cancer Center support Grant [CA016672]
第一作者机构:[1]Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA[2]Department of Radiation Oncology, Sichuan Cancer Hospital, Chengdu, China
通讯作者:
通讯机构:[4]Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA[*1]Department of Radiation Physics, Unit 1420, The University of Texas MD Anderson Cancer Center, 1400 Pressler St., Houston, TX 77030, USA
推荐引用方式(GB/T 7714):
Luo Yangkun,Xu Yujin,Liao Zhongxing,et al.Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis?[J].ACTA ONCOLOGICA.2019,58(1):81-87.doi:10.1080/0284186X.2018.1521985.
APA:
Luo, Yangkun,Xu, Yujin,Liao, Zhongxing,Gomez, Daniel,Wang, Jingqian...&Yang, Jinzhong.(2019).Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis?.ACTA ONCOLOGICA,58,(1)
MLA:
Luo, Yangkun,et al."Automatic segmentation of cardiac substructures from noncontrast CT images: accurate enough for dosimetric analysis?".ACTA ONCOLOGICA 58..1(2019):81-87