Evidence map›Paper›PMID 34082755›Full record

ArticleBiomedical engineering online2021

A novel specific grading standard study of auto-segmentation of organs at risk in thorax: subjective-objective-combined grading standard.

Yanchen Ying, Hao Wang, Hua Chen, Jianfan Cheng, Hengle Gu, Yan Shao, Yanhua Duan, Aihui Feng, Wen Feng, Xiaolong Fu and 2 more

Abstract read
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Article in Biomedical engineering online, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Yanchen YingDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Hao WangInstitute of Modern Physics, Fudan University, Shanghai, China.
Hua ChenDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Jianfan ChengDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Hengle GuDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Yan ShaoDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Yanhua DuanDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Aihui FengDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Wen FengDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Xiaolong FuDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China.
Hong QuanKey Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and Center for Electronic Microscopy and Department of Physics, Wuhan University, Wuhan, 430070, China.
Zhiyong XuDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, China. xzyong12vip@sina.com.

Funding

the Zhejiang Provincial Natural Science Foundation of China LSY19H180002
6 · The paper itself

Abstract

backgroundTo develop a novel subjective-objective-combined (SOC) grading standard for auto-segmentation for each organ at risk (OAR) in the thorax.

methodsA radiation oncologist manually delineated 13 thoracic OARs from computed tomography (CT) images of 40 patients. OAR auto-segmentation accuracy was graded by five geometric objective indexes, including the Dice similarity coefficient (DSC), the difference of the Euclidean distance between centers of mass (ΔCMD), the difference of volume (ΔV), maximum Hausdorff distance (MHD), and average Hausdorff distance (AHD). The grading results were compared with those of the corresponding geometric indexes obtained by geometric objective methods in the other two centers. OAR auto-segmentation accuracy was also graded by our subjective evaluation standard. These grading results were compared with those of DSC. Based on the subjective evaluation standard and the five geometric indexes, the correspondence between the subjective evaluation level and the geometric index range was established for each OAR.

resultsFor ΔCMD, ΔV, and MHD, the grading results of the geometric objective evaluation methods at our center and the other two centers were inconsistent. For DSC and AHD, the grading results of three centers were consistent. Seven OARs' grading results in the subjective evaluation standard were inconsistent with those of DSC. Six OARs' grading results in the subjective evaluation standard were consistent with those of DSC. Finally, we proposed a new evaluation method that combined the subjective evaluation level of those OARs with the range of corresponding DSC to determine the grading standard. If the DSC ranges between the adjacent levels did not overlap, the DSC range was used as the grading standard. Otherwise, the mean value of DSC was used as the grading standard.

conclusionsA novel OAR-specific SOC grading standard in thorax was developed. The SOC grading standard provides a possible alternative for evaluation of the auto-segmentation accuracy for thoracic OARs.

Indexed as

Image Processing, Computer-AssistedOrgans at RiskThoraxTomography, X-Ray ComputedAgedAutomationFemaleHumansMaleMiddle AgedReference StandardsAuto-segmentationOrgans at riskSOC grading standardThorax

Identifiers

PMID34082755
PMCPMC8173789

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