{"title":"基于非增强MRI放射组学的子宫腺肌症高强度聚焦超声消融临床结果预测","authors":"Ziyi Liu, Ziyan Liu, Xiyao Wan, Yuan Wang, Xiaohua Huang","doi":"10.1080/02656736.2025.2468766","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The study aimed to develop a non-enhanced MRI-based radiomics model for the preoperative prediction of the efficacy of adenomyosis after high-intensity focused ultrasound (HIFU) treatment.</p><p><strong>Methods: </strong>The data of 130 patients with adenomyosis who underwent HIFU treatment were reviewed. Based on a non-perfused volume ratio (NPVR) of 50%, the patients were assigned to high ablation rate and low ablation rate groups. A radiomics model was constructed from the screened radiomics features and its output probability was calculated as the radiomics score (Radscore). The clinical-imaging model was constructed from the independent predictors of clinical-imaging characteristics. The combined model was constructed by integrating Radscore and clinical-imaging independent predictors. Receiver operating characteristic (ROC) curves, the Delong test, and decision curve analysis (DCA) were used to evaluate the models.</p><p><strong>Results: </strong>The combined model had the best overall performance among the three models. The AUC (95% CI), specificity, sensitivity, accuracy, and precision of the combined model were 0.860 (0.786-0.935), 0.780, 0.756, 0.769, 0.738 in the training set, and 0.878 (0.774-0.983), 0.859, 0.667, 0.769, 0.800 in the test set, respectively. The Delong test showed that the performance of both the radiomics and combined models differed significantly from the clinical-imaging model. But the performance of the combined and the radiomics model was statistically equivalent. The DCA indicated that the combined model had better clinical net benefit.</p><p><strong>Conclusion: </strong>The combined model based on non-enhanced MRI radiomics was effective in predicting the outcome of HIFU ablation of adenomyosis before surgery.</p>","PeriodicalId":14137,"journal":{"name":"International Journal of Hyperthermia","volume":"42 1","pages":"2468766"},"PeriodicalIF":3.0000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of clinical outcome for high-intensity focused ultrasound ablation of adenomyosis based on non-enhanced MRI radiomics.\",\"authors\":\"Ziyi Liu, Ziyan Liu, Xiyao Wan, Yuan Wang, Xiaohua Huang\",\"doi\":\"10.1080/02656736.2025.2468766\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>The study aimed to develop a non-enhanced MRI-based radiomics model for the preoperative prediction of the efficacy of adenomyosis after high-intensity focused ultrasound (HIFU) treatment.</p><p><strong>Methods: </strong>The data of 130 patients with adenomyosis who underwent HIFU treatment were reviewed. Based on a non-perfused volume ratio (NPVR) of 50%, the patients were assigned to high ablation rate and low ablation rate groups. A radiomics model was constructed from the screened radiomics features and its output probability was calculated as the radiomics score (Radscore). The clinical-imaging model was constructed from the independent predictors of clinical-imaging characteristics. The combined model was constructed by integrating Radscore and clinical-imaging independent predictors. Receiver operating characteristic (ROC) curves, the Delong test, and decision curve analysis (DCA) were used to evaluate the models.</p><p><strong>Results: </strong>The combined model had the best overall performance among the three models. The AUC (95% CI), specificity, sensitivity, accuracy, and precision of the combined model were 0.860 (0.786-0.935), 0.780, 0.756, 0.769, 0.738 in the training set, and 0.878 (0.774-0.983), 0.859, 0.667, 0.769, 0.800 in the test set, respectively. The Delong test showed that the performance of both the radiomics and combined models differed significantly from the clinical-imaging model. But the performance of the combined and the radiomics model was statistically equivalent. The DCA indicated that the combined model had better clinical net benefit.</p><p><strong>Conclusion: </strong>The combined model based on non-enhanced MRI radiomics was effective in predicting the outcome of HIFU ablation of adenomyosis before surgery.</p>\",\"PeriodicalId\":14137,\"journal\":{\"name\":\"International Journal of Hyperthermia\",\"volume\":\"42 1\",\"pages\":\"2468766\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Hyperthermia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/02656736.2025.2468766\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/2/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hyperthermia","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/02656736.2025.2468766","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/23 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Prediction of clinical outcome for high-intensity focused ultrasound ablation of adenomyosis based on non-enhanced MRI radiomics.
Objectives: The study aimed to develop a non-enhanced MRI-based radiomics model for the preoperative prediction of the efficacy of adenomyosis after high-intensity focused ultrasound (HIFU) treatment.
Methods: The data of 130 patients with adenomyosis who underwent HIFU treatment were reviewed. Based on a non-perfused volume ratio (NPVR) of 50%, the patients were assigned to high ablation rate and low ablation rate groups. A radiomics model was constructed from the screened radiomics features and its output probability was calculated as the radiomics score (Radscore). The clinical-imaging model was constructed from the independent predictors of clinical-imaging characteristics. The combined model was constructed by integrating Radscore and clinical-imaging independent predictors. Receiver operating characteristic (ROC) curves, the Delong test, and decision curve analysis (DCA) were used to evaluate the models.
Results: The combined model had the best overall performance among the three models. The AUC (95% CI), specificity, sensitivity, accuracy, and precision of the combined model were 0.860 (0.786-0.935), 0.780, 0.756, 0.769, 0.738 in the training set, and 0.878 (0.774-0.983), 0.859, 0.667, 0.769, 0.800 in the test set, respectively. The Delong test showed that the performance of both the radiomics and combined models differed significantly from the clinical-imaging model. But the performance of the combined and the radiomics model was statistically equivalent. The DCA indicated that the combined model had better clinical net benefit.
Conclusion: The combined model based on non-enhanced MRI radiomics was effective in predicting the outcome of HIFU ablation of adenomyosis before surgery.