Evidence map›Paper›PMID 41607533›Full record

ArticleFrontiers in oncology2025

Intratumoral and peritumoral radiomics for preoperative prediction of the efficacy of HIFU ablation for uterine fibroids based on multiparametric MRI: a multicenter study.

Chengwei Li, Hongjian Liao, Jian Liu, Jin Gao

Abstract read
In one paragraph

Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chengwei LiDepartment of Radiology, The Third People's Hospital of Chengdu, Chengdu, China.
Hongjian LiaoDepartment of Radiology, The Third People's Hospital of Chengdu, Chengdu, China.
Jian LiuDepartment of Radiology, The Third People's Hospital of Chengdu, Chengdu, China.
Jin GaoDepartment of Radiology, The Third People's Hospital of Chengdu, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To assess the predictive value of intratumoral and multiregion peritumoral radiomics based on multiparametric MRI for preoperatively predicting the efficacy of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids. Materials and methods: This retrospective study included 360 patients with uterine fibroids treated with high-intensity focused ultrasound (HIFU) at Center A (training set: N = 240; internal testing set: N = 60) and Center B (external testing set: N = 60). Patients were grouped into sufficient or insufficient ablation categories based on postoperative non-perfusion volume ratio. Intratumoral regions (TRs) were manually delineated on T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (CE-T1WI). Peritumoral regions (PTRs) were generated by expanding the tumor boundary by 1 mm, 3 mm, and 5 mm. Radiomics features were extracted from TRs and PTRs on both MRI sequences. Key features for preoperative prediction were selected using t-tests, Pearson correlation, and LASSO regression. Support vector machine (SVM) models were built for TRs from T2WI and CE-T1WI, and for combined intratumoral and peritumoral regions (T-PTRs). A fusion model integrated optimal T-PTRs features from both sequences. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The T-PTRs radiomics models outperformed the TR models, with the T-PTRs (3 mm) model demonstrating optimal performance. The integration of T2WI and CE-T1WI further enhanced the T-PTRs model, yielding an AUC of 0.892(0.814-0.969) on the internal test set and an AUC of 0.828(0.741 - 0.915) on the external validation set. Conclusion: The predictive model based on intratumoral and peritumoral radiomics features serves as a valuable tool for predicting the therapeutic efficacy of HIFU ablation of uterine fibroids.

Indexed as

efficacy predictionhigh-intensity focused ultrasoundmagnetic resonance imagingradiomicsuterine fibroids

Identifiers

PMID41607533
PMCPMC12834714

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.