ArticleQuantitative imaging in medicine and surgery2024
Development and validation of a radiomics model based on T2-weighted imaging for predicting the efficacy of high intensity focused ultrasound ablation in uterine fibroids.
Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 10 citations in OpenAlex.
- Navigating transcranial mr guided focused ultrasound complexities with machine learning: Overcoming obstacles and expanding therapeutic horizons.Neurosurgical review · 2026Review
- Establishment of a Predictive Model for the Efficacy of High-Intensity Focused Ultrasound in the Treatment of Uterine Fibroids.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025Article
- Predicting the regrowth of residual uterine fibroids after high-intensity focused ultrasound treatment: an interpretable magnetic resonance imaging radiomics model.Quantitative imaging in medicine and surgery · 2025Article
- Ultrasound-based radiomics to predict the volume reduction rate of benign thyroid nodules after microwave ablation.Endocrine · 2025Article
- Multi-sequence magnetic resonance imaging radiomics combined with imaging features predicts the difficulty of HIFU treatment of uterine fibroids.Scientific reports · 2025Article
- A Dual-Sequence MRI-Based Radiomics Model for Predicting High-Intensity Focused Ultrasound Ablation Efficacy in Adenomyosis Treatment.International journal of women's health · 2025Article
- Radiomics and quantitative multi-parametric MRI for predicting uterine fibroid growth.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Multimodal MRI radiomics-based stacking ensemble learning model with automatic segmentation for prognostic prediction of HIFU ablation of uterine fibroids: a multicenter study.Frontiers in physiology · 2024Article
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8 authors at 3 institutions in 1 country.
Funding
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Abstract
Background: The heterogeneity of uterine fibroids in magnetic resonance imaging (MRI) is complex for a subjective visual evaluation, therefore it is difficult for an accurate prediction of the efficacy of high intensity focused ultrasound (HIFU) ablation in fibroids before the treatment. The purpose of this study was to set up a radiomics model based on MRI T2-weighted imaging (T2WI) for predicting the efficacy of HIFU ablation in uterine fibroids, and it would be used in preoperative screening of the fibroids for achieving high non-perfused volume ratio (NPVR). Methods: A total of 178 patients with uterine fibroids were consecutively enrolled and treated with ultrasound-guided HIFU under conscious sedation between February 2017 and December 2021. Among them, 96 patients with 108 uterine fibroids with high ablation efficacy (NPVR ≥80%, h_NPVR) and 82 patients with 92 fibroids with lower ablation efficacy (NPVR <80%, l_NPVR) were retrospectively analyzed. The transverse T2WI images of fibroids were selected, and the fibroids were delineated slice by slice using ITK-SNAP software. The radiomics analysis was performed to find the imaging biomarker for the construction of a predicting model for the evaluation of the ablation efficacy, including the feature extraction, feature selection and model construction. The prediction model was built by logistic regression and assessed by receiver operating characteristic (ROC) curve, and the prediction efficiency of the two models was compared by Delong test. The ratio of the training set to the testing set was 8:2. Results: The logistic regression model showed that the mean area under the curve (AUC) of the training set was 0.817 [95% confidence interval (CI): 0.755-0.882], and the testing set was 0.805 (95% CI: 0.670-0.941), respectively, which indicated a strong classification ability. The Delong test showed that there was no significant difference in the area under the ROC curve between the training set and testing set (P>0.05). Conclusions: The radiomics model based on T2WI is feasible and effective for predicting the efficacy of HIFU ablation in treatment of uterine fibroids.
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