Knowledge Management System of Hefei Institute of Physical Science,CAS
The radiomic-clinical model using the SHAP method for assessing the treatment response of whole-brain radiotherapy: a multicentric study | |
Wang, Yixin1,2,3; Lang, Jinwei1,2; Zuo, Joey Zhaoyu1,2; Dong, Yaqin4; Hu, Zongtao1,3; Xu, Xiuli3; Zhang, Yongkang3; Wang, Qinjie1,2; Yang, Lizhuang1,2,3; Wong, Stephen T. C.5; Wang, Hongzhi1,2,3; Li, Hai1,2,3 | |
2022-06-09 | |
发表期刊 | EUROPEAN RADIOLOGY |
ISSN | 0938-7994 |
通讯作者 | Wang, Hongzhi(wanghz@hfcas.ac.cn) ; Li, Hai(hli@cmpt.ac.cn) |
摘要 | Objective To develop and validate a pretreatment magnetic resonance imaging (MRI)-based radiomic-clinical model to assess the treatment response of whole-brain radiotherapy (WBRT) by using SHapley Additive exPlanations (SHAP), which is derived from game theory, and can explain the output of different machine learning models. Methods We retrospectively enrolled 228 patients with brain metastases from two medical centers (184 in the training cohort and 44 in the validation cohort). Treatment responses of patients were categorized as a non-responding group vs. a responding group according to the Response Assessment in Neuro-Oncology Brain Metastases (RANO-BM) criteria. For each tumor, 960 features were extracted from the MRI sequence. The least absolute shrinkage and selection operator (LASSO) was used for feature selection. A support vector machine (SVM) model incorporating clinical factors and radiomic features wase used to construct the radiomic-clinical model. SHAP method explained the SVM model by prioritizing the importance of features, in terms of assessment contribution. Results Three radiomic features and three clinical factors were identified to build the model. Radiomic-clinical model yielded AUCs of 0.928 (95%CI 0.901-0.949) and 0.851 (95%CI 0.816-0.886) for assessing the treatment response in the training cohort and validation cohort, respectively. SHAP summary plot illustrated the feature's value affected the feature's impact attributed to model, and SHAP force plot showed the integration of features' impact attributed to individual response. Conclusion The radiomic-clinical model with the SHAP method can be useful for assessing the treatment response of WBRT and may assist clinicians in directing personalized WBRT strategies in an understandable manner. |
关键词 | Magnetic resonance imaging Neoplasm metastasis Machine learning Radiotherapy Game theory |
DOI | 10.1007/s00330-022-08887-0 |
关键词[WOS] | CELL LUNG-CANCER ; GRADED PROGNOSTIC ASSESSMENT ; RADIATION-THERAPY ; BREAST-CANCER ; METASTASES ; SURVIVAL ; STRATIFICATION ; PREDICTION ; EFFICACY |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Key R&D Program of Anhui Province[201904a07020104] ; Natural Science Fund of Anhui Province[2008085MC69] ; Collaborative Innovation Program of Hefei Science Center[2020HSC-CIP001] ; Collaborative Innovation Program of Hefei Science Center[2021HSC-CIP013] ; General scientific research project of Anhui Provincial Health Commission[AHWJ2021b150] ; Natural Science Fund of Hefei City[2021033] ; CAS Anhui Province Key Laboratory of Medical Physics and Technology[LMPT201904] ; Director's Fund of Hefei Cancer Hospital of CAS[YZJJ2019C14] ; Director's Fund of Hefei Cancer Hospital of CAS[YZJJ2019A04] |
项目资助者 | Key R&D Program of Anhui Province ; Natural Science Fund of Anhui Province ; Collaborative Innovation Program of Hefei Science Center ; General scientific research project of Anhui Provincial Health Commission ; Natural Science Fund of Hefei City ; CAS Anhui Province Key Laboratory of Medical Physics and Technology ; Director's Fund of Hefei Cancer Hospital of CAS |
WOS研究方向 | Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000808417600002 |
出版者 | SPRINGER |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.hfcas.ac.cn:8080/handle/334002/131176 |
专题 | 中国科学院合肥物质科学研究院 |
通讯作者 | Wang, Hongzhi; Li, Hai |
作者单位 | 1.Chinese Acad Sci, Hefei Inst Phys Sci, Inst Hlth & Med Technol, Anhui Prov Key Lab Med Phys & Technol, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Hefei 230026, Peoples R China 3.Chinese Acad Sci, Hefei Canc Hosp, Dept Oncol, Hefei 230031, Peoples R China 4.Anhui Med Univ, Dept Radiat Oncol, Affiliated Hosp 1, Hefei 230022, Peoples R China 5.Houston Methodist Canc Ctr, Dept Syst Med & Bioengn, Weill Cornell Med Coll, Houston, TX 77030 USA |
推荐引用方式 GB/T 7714 | Wang, Yixin,Lang, Jinwei,Zuo, Joey Zhaoyu,et al. The radiomic-clinical model using the SHAP method for assessing the treatment response of whole-brain radiotherapy: a multicentric study[J]. EUROPEAN RADIOLOGY,2022. |
APA | Wang, Yixin.,Lang, Jinwei.,Zuo, Joey Zhaoyu.,Dong, Yaqin.,Hu, Zongtao.,...&Li, Hai.(2022).The radiomic-clinical model using the SHAP method for assessing the treatment response of whole-brain radiotherapy: a multicentric study.EUROPEAN RADIOLOGY. |
MLA | Wang, Yixin,et al."The radiomic-clinical model using the SHAP method for assessing the treatment response of whole-brain radiotherapy: a multicentric study".EUROPEAN RADIOLOGY (2022). |
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