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
机构：[1]Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.[2]Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.重庆医科大学附属第一医院[3]College of Computer & Information Science, Southwest University, Chongqing, China.[4]Department of Endocrinology, University-Town Hospital of Chongqing Medical University, Chongqing, China.[5]School of Medical and Life Sciences Chengdu University of Traditional Chinese Medicine, Chengdu, China.[6]Department of Radiology, Chongqing United Medical Imaging Center, Chongqing, China.[7]Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China.四川省人民医院四川省肿瘤医院
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 ATRX testing currently requires invasive procedures. The objective of this 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.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.The overall hybrid model constructed with radiomics and DL features from the overall lesion was 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).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.2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.
基金：
This study was supported by the Science and
Technology Research Program of Chongqing Municipal
Education Commission (No. KJZD-K202200203).
第一作者机构：[1]Department of Radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.
共同第一作者：
通讯作者：
推荐引用方式(GB/T 7714)：
Liu Zhi,Xu Xinyi,Zhang Wang,et al.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[J].Quantitative Imaging In Medicine And Surgery.2024,14(1):251-263.doi:10.21037/qims-23-807.
APA：
Liu Zhi,Xu Xinyi,Zhang Wang,Zhang Liqiang,Wen Ming...&Cao Xu.(2024).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.Quantitative Imaging In Medicine And Surgery,14,(1)
MLA：
Liu Zhi,et al."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".Quantitative Imaging In Medicine And Surgery 14..1(2024):251-263
