Suppr超能文献

一种基于磁共振成像的新型评分系统,用于预测超声引导高强度聚焦超声消融治疗子宫肌瘤的难度。

A novel scoring system based on magnetic resonance imaging for the prediction of the difficulty of ultrasound-guided high-intensity focused ultrasound ablation for uterine fibroids.

机构信息

State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, China.

Chongqing Key Laboratory of Biomedical Engineering, Chongqing Medical University, Chongqing, China.

出版信息

Int J Hyperthermia. 2024;41(1):2386098. doi: 10.1080/02656736.2024.2386098. Epub 2024 Aug 4.

Abstract

OBJECTIVE

To develop a novel scoring system based on magnetic resonance imaging (MRI) for predicting the difficulty of ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation for uterine fibroids.

MATERIALS AND METHODS

A total of 637 patients with uterine fibroids were enrolled. Sonication time, non-perfused volume ratio (NPVR), and ultrasound energy delivered for ablating 1 mm of fibroid tissue volume (E/V) were each classified as three levels and assigned scores from 0 to 2, respectively. Treatment difficulty level was then assessed by adding up the scores of sonication time, NPVR and E/V for each patient. The patients with score lower than 3 were categorized into low difficulty group, with score equal to or greater than 3 were categorized into high difficulty group. The potential predictors for treatment difficulty were compared between the two groups. Multifactorial logistic regression analysis model was created by analyzing the variables. The difficulty score system was developed using the beta coefficients of the logistic model.

RESULTS

Signal intensity on T2WI, fibroid location index, largest diameter of fibroids, abdominal wall thickness, homogeneity of the signal of fibroids, and uterine position were independent influencing factors for the difficulty of USgHIFU for uterine fibroids. A prediction equation was obtained: difficulty score = 17 × uterine position (anteverted =0, retroverted =1)+71 × signal intensity (hypointense = 0, isointense/hyperintense = 1) +8 × enhancement (homogenous = 0, heterogeneous = 1)+25×(largest diameter of fibroids-20) +35 × (fibroid location index -0.2) +1×(abdominal wall thickness -5).

CONCLUSIONS

This scoring system established based on MRI findings can be used to reliably predict the difficulty level of USgHIFU treatment of uterine fibroids.

摘要

目的

基于磁共振成像(MRI)开发一种新的评分系统,以预测超声引导高强度聚焦超声(USgHIFU)消融治疗子宫肌瘤的难度。

材料与方法

共纳入 637 例子宫肌瘤患者。将超声时间、无灌注体积比(NPVR)和用于消融 1mm 肌瘤组织体积的超声能量(E/V)分别分为 3 个等级,并分别赋予 0 至 2 的评分。然后通过为每位患者累加超声时间、NPVR 和 E/V 的评分来评估治疗难度级别。评分低于 3 分的患者归入低难度组,评分等于或大于 3 分的患者归入高难度组。比较两组间治疗难度的潜在预测因素。采用多因素逻辑回归分析模型,通过分析变量建立模型。使用逻辑模型的β系数建立难度评分系统。

结果

T2WI 信号强度、肌瘤位置指数、肌瘤最大直径、腹壁厚度、肌瘤信号均匀性和子宫位置是影响 USgHIFU 治疗子宫肌瘤难度的独立影响因素。得到一个预测方程:难度评分=17×子宫位置(前倾=0,后倾=1)+71×信号强度(低信号=0,等/高信号=1)+8×增强(均匀=0,不均匀=1)+25×(肌瘤最大直径-20)+35×(肌瘤位置指数-0.2)+1×(腹壁厚度-5)。

结论

基于 MRI 表现建立的评分系统可用于可靠预测 USgHIFU 治疗子宫肌瘤的难度级别。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验