ArticleScientific reports2025
Multi-sequence magnetic resonance imaging radiomics combined with imaging features predicts the difficulty of HIFU treatment of uterine fibroids.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- A multimodal dataset and predictive model for the treatment of uterine fibroids with focused ultrasound ablation surgery.Scientific data · 2026Article
- Machine Learning Model for Predicting Pheochromocytomas/Paragangliomas Surgery Difficulty: A Retrospective Cohort Study.Annals of surgical oncology · 2025Article
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Authors and funding
6 authors.
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Abstract
To establish a multivariate linear regression model for predicting the difficulty of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids based on multi-sequence magnetic resonance imaging radiomics features. A retrospective analysis was conducted on 218 patients with uterine fibroids who underwent HIFU treatment, including 178 cases from Yongchuan Hospital of Chongqing Medical University and 40 cases from the Second Affiliated Hospital of Chongqing Medical University (external validation set). Radiomics features were extracted and selected from magnetic resonance images, and potentially related imaging features were collected. The energy efficiency factor (EEF) was used as the dependent variable. Imaging models, radiomics models, and joint models were established using a stepwise approach. The model with the highest R
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