A fusion model integrating magnetic resonance imaging radiomics and deep learning features for predicting alpha-thalassemia X-linked intellectual disability mutation status in isocitrate dehydrogenase-mutant high-grade astrocytoma: a multicenter study

作者全名："Liu, Zhi; Xu, Xinyi; Zhang, Wang; Zhang, Liqiang; Wen, Ming; Gao, Jueni; Yang, Jun; Kan, Yubo; Yang, Xing; Wen, Zhipeng; Chen, Shanxiong; Cao, Xu"

作者地址："[Liu, Zhi] Chongqing Hosp Tradit Chinese Med, Dept Radiol, Chongqing, Peoples R China; [Xu, Xinyi; Zhang, Liqiang; Wen, Ming; Gao, Jueni] Chongqing Med Univ, Affiliated Hosp 1, Dept Radiol, Chongqing, Peoples R China; [Zhang, Wang; Chen, Shanxiong] Southwest Univ, Coll Comp & Informat Sci, 2 Tiansheng Rd, Chongqing 400715, Peoples R China; [Yang, Jun] Chongqing Med Univ, Univ Town Hosp, Dept Endocrinol, Chongqing, Peoples R China; [Kan, Yubo; Cao, Xu] Chengdu Univ Tradit Chinese Med, Sch Med & Life Sci, 37,12 Qiao Rd, Chengdu 610032, Peoples R China; [Yang, Xing] Chongqing United Med Imaging Ctr, Dept Radiol, Chongqing, Peoples R China; [Wen, Zhipeng] Univ Elect Sci & Technol China, Sichuan Canc Hosp & Inst, Sichuan Canc Ctr, Sch Med,Dept Radiol, Chengdu, Peoples R China; [Wen, Zhipeng] Univ Elect Sci & Technol China, Sichuan Canc Hosp & Inst, Sichuan Clin Res Ctr Canc, Sichuan Canc Ctr,Affiliated Canc Hosp,Dept Radiol, 55 Renmin South Rd, Chengdu 610042, Peoples R China"

通信作者："Chen, SX (通讯作者)，Southwest Univ, Coll Comp & Informat Sci, 2 Tiansheng Rd, Chongqing 400715, Peoples R China.; Cao, X (通讯作者)，Chengdu Univ Tradit Chinese Med, Sch Med & Life Sci, 37,12 Qiao Rd, Chengdu 610032, Peoples R China.; Wen, ZP (通讯作者)，Univ Elect Sci & Technol China, Sichuan Canc Hosp & Inst, Sichuan Clin Res Ctr Canc, Sichuan Canc Ctr,Affiliated Canc Hosp,Dept Radiol, 55 Renmin South Rd, Chengdu 610042, Peoples R China."

来源：QUANTITATIVE IMAGING IN MEDICINE AND SURGERY

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001229739600001

JCR分区：Q2

影响因子：2.8

年份：2024

卷号：14

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Radiomics; deep learning (DL); magnetic resonance imaging (MRI); brain neoplasms; astrocytoma

摘要："Background:The mutational status of alpha-thalassemia X-linked intellectual disability (ATRX) is an important indicator for the treatment and prognosis of high-grade gliomas, but reliable AT R X testing currently requires invasive procedures. The objective ofthis study was to develop a clinical trait-imaging fusion model that combines preoperative magnetic resonance imaging (MRI) radiomics and deep learning (DL) features with clinical variables to predict ATRX status in isocitrate dehydrogenase (IDH)-mutant high-grade astrocytoma. Methods:A total of 234 patients with IDH-mutant high-grade astrocytoma (120 ATRX mutant type, 114 ATRX wild type) from 3 centers were retrospectively analyzed. Radiomics and DL features from different regions (edema, tumor, and the overall lesion) were extracted to construct multiple imaging models by combining different features in different regions for predicting ATRX status. An optimal imaging model was then selected, and its features and linear coefficients were used to calculate an imaging score. Finally, a fusion model was developed by combining the imaging score and clinical variables. The performance and application value of the fusion model were evaluated through the comparison of receiver operating characteristic curves, the construction of a nomogram, calibration curves, decision curves, and clinical application curves. Results:The overall hybrid model constructed with radiomics and DL features from the overall lesion was 263 identified as the optimal imaging model. The fusion model showed the best prediction performance with an area under curve of 0.969 in the training set, 0.956 in the validation set, and 0.949 in the test set as compared to the optimal imaging model (0.966, 0.916, and 0.936, respectively) and clinical model (0.677, 0.641, 0.772, respectively). Conclusions: The clinical trait-imaging fusion model based on preoperative MRI could effectively predict the ATRX mutation status of individuals with IDH-mutant high-grade astrocytoma and has the potential to help patients through the development of a more effective treatment strategy before treatment."

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