Value of a combined magnetic resonance-enhanced and diffusion-weighted imaging dual-sequence radiomics model in predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids.

IF 3.2 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING BMC Medical Imaging Pub Date : 2025-02-17 DOI:10.1186/s12880-025-01593-5
Xiao Huang, Li Shen, Yuyao Liu, Qingxue Li, Shanwei Bai, Fang Wang, Quan Yang
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Abstract

Objective: To establish a joint radiomics model based on T1 contrast-enhanced (T1C) imaging and diffusion-weighted imaging (DWI), and investigate its value in predicting the efficacy of high-intensity focused ultrasound (HIFU) in ablating uterine fibroids.

Methods: This multicenter retrospective study included 195 patients with uterine fibroids. Their data were divided into training (n = 120), internal test (n = 30), and external test (n = 45) sets. The radiomic features were extracted from T1C and DWI sequences. Logistic regression was used to develop the T1C, DWI, integration, and joint models, and receiver operating characteristic curves were used to assess model performance. The Delong test was used to compare the predictive efficacies of different models, and the best model was used for external validation and development of the nomogram.

Results: Eight T1C features, six DWI features, and three imaging features were retained for the modeling. The areas under the curve were 0.852 and 0.769 for the integrated model on the training and internal test sets, respectively; 0.857 and 0.824 for the joint model on the training and internal test sets, respectively, which were higher than those of the single-sequence model; and 0.857 for the joint model on the external test set.

Conclusions: A joint radiomics model based on T1C and DWI data can effectively predict the efficacy of HIFU for ablating uterine fibroids and guide the development of individualized clinical treatment plans.

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磁共振增强和弥散加权成像双序列放射组学模型在预测子宫肌瘤高强度聚焦超声消融疗效中的价值。
目的:建立基于T1增强成像(T1C)和弥散加权成像(DWI)的联合放射组学模型,探讨其对高强度聚焦超声(HIFU)消融子宫肌瘤疗效的预测价值。方法:对195例子宫肌瘤患者进行多中心回顾性研究。他们的数据被分为训练集(n = 120)、内部测试集(n = 30)和外部测试集(n = 45)。从T1C和DWI序列中提取放射学特征。采用Logistic回归建立T1C、DWI、整合和联合模型,并使用受试者工作特征曲线评估模型的性能。采用Delong检验比较不同模型的预测效果,选取最佳模型进行外部验证和拟合。结果:保留8个T1C特征、6个DWI特征和3个影像学特征进行建模。综合模型在训练集和内部测试集上的曲线下面积分别为0.852和0.769;联合模型在训练集和内部测试集上分别为0.857和0.824,均高于单序列模型;外部测试集上的联合模型为0.857。结论:基于T1C和DWI数据的联合放射组学模型可有效预测HIFU治疗子宫肌瘤的疗效,指导临床个体化治疗方案的制定。
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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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