ORIGINAL RESEARCH article
Front. Physiol.
Sec. Medical Physics and Imaging
Volume 16 - 2025 | doi: 10.3389/fphys.2025.1602866
Machine learning-based predictive analysis of energy efficiency factors necessary for the HIFU treatment of adenomyosis
Provisionally accepted
- Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
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Purpose: This study aimed to develop a joint model combining T2-weighted imaging (T2WI) compressed lipid radiomics and clinical parameters to predict the energy efficiency factor (EEF) required for high-intensity focused ultrasound (HIFU) ablation in adenomyosis patients.: This retrospective study included 169 adenomyosis patients who underwent HIFU ablation between September 2021 and May 2024. EEF values were calculated based on T2WI-FS sequences, and radiomics features were extracted.Predictive features were selected using MRMR and LASSO methods, and two joint models were developed based on decision tree and random forest algorithms for EEF prediction.The decision tree model demonstrated a test set MAE of 8.095, while the random forest model exhibited an MAE of 8.231. The Wilcoxon rank sum test for the test set revealed that the discrepancy in predictive performance between the two models was statistically significant (p < 0.05). The correlation coefficients were 0.768 and 0.777, and the R 2 coefficients of the two models in the test set were 0.559 and 0.549, respectively.The joint model integrating T2WI radiomics and clinical data accurately predicted EEF values for HIFU ablation in adenomyosis. This approach provides a foundation for optimizing HIFU dosing strategies, enhancing treatment safety and efficacy.
Keywords: Adenomyosis, Magnetic Resonance Imaging, High intensity focused ultrasound, Energy efficiency factor, prediction
Received: 09 Apr 2025; Accepted: 14 Jul 2025.
Copyright: © 2025 Liu, Liu, Wang, Wan and Huang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaohua Huang, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China
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