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子宫肌瘤子宫动脉栓塞术:体积反应的预测性 MRI 特征。

Uterine Artery Embolization of Uterine Leiomyomas: Predictive MRI Features of Volumetric Response.

机构信息

Tawam Hospital, Al Ain, Abu Dhabi, PO Box 64624, United Arab Emirates.

Al Ain Hospital, Al Ain, Abu Dhabi, United Arab Emirates.

出版信息

AJR Am J Roentgenol. 2021 Apr;216(4):967-974. doi: 10.2214/AJR.20.22906. Epub 2021 Feb 17.

Abstract

The purpose of this article was to evaluate MRI features of uterine leiomyomas that predict volumetric response after uterine artery embolization (UAE). This retrospective study included 75 patients with 212 uterine leiomyomas who were successfully treated between August 2013 and December 2018. To predict uterine volumetric response, age, number of lesions, and baseline uterine volume were assessed. To predict leiomyoma volumetric response, a multivariate regression analysis was performed to evaluate six predictive factors: location, baseline leiomyoma volume, signal intensity on T1-weighted and T2-weighted MRI, heterogeneity of signal intensity on T2-weighted MRI, and vascularity on subtraction imaging (SI). A five-variable predictive ROC model was developed to evaluate the diagnostic accuracy of the signal intensity ratio on T2-weighted MRI, enhancement ratio, heterogeneity ratio on T2-weighted MRI, location, and baseline leiomyoma volume in predicting at least 40% leiomyoma volumetric response. Age, number of leiomyomas, and baseline uterine volume were not predictive of uterine volumetric response. A submucosal location was the best predictive factor of leiomyoma volumetric response, and it showed 32.2% more leiomyoma volumetric response compared with a nonsubmucosal location ( < .001). Hyperintensity on T2-weighted MRI was the second best predictive factor of leiomyoma volumetric response, and it showed 16.9% more volumetric response compared with hypointense leiomyomas ( = .013). A small baseline leiomyoma volume (< 58 cm) was associated with 10.2% more leiomyoma volumetric response compared with larger leiomyomas ( = .01). Leiomyomas that were hyperintense on SI showed 7.9% more leiomyoma volumetric response compared with those that were hypointense ( = .014). The five-variable ROC model showed high diagnostic accuracy with an AUC of 0.85, sensitivity of 82%, and specificity of 71%. A submucosal location, hyperintensity on T2-weighted MRI, small baseline leiomyoma volume (< 58 cm), and hyperintense leiomyoma on subtraction imaging are the main independent favorable predictors of leiomyoma volumetric response after UAE. An accurate predictive ROC model was developed that may help in selecting patients suitable for UAE. Quantitative assessment of heterogeneity on T2-weighted MRI showed promising results as a predictor of volumetric response, and further research in this area using texture analysis and radiomics is suggested.

摘要

本文旨在评估磁共振成像(MRI)特征,以预测子宫动脉栓塞术(UAE)后子宫的体积变化。这项回顾性研究纳入了 75 名 212 个子宫肌瘤患者,这些患者于 2013 年 8 月至 2018 年 12 月期间成功接受了治疗。为了预测子宫体积变化,评估了年龄、病变数量和基线子宫体积等因素。为了预测子宫肌瘤体积变化,进行了多元回归分析,以评估六个预测因素:位置、基线子宫肌瘤体积、T1 加权和 T2 加权 MRI 的信号强度、T2 加权 MRI 信号强度的异质性以及减影成像(SI)的血管性。建立了一个五变量预测 ROC 模型,以评估 T2 加权 MRI 信号强度比、强化率、T2 加权 MRI 异质性比、位置和基线子宫肌瘤体积预测至少 40%子宫肌瘤体积变化的诊断准确性。年龄、子宫肌瘤数量和基线子宫体积均不能预测子宫体积变化。黏膜下位置是预测子宫肌瘤体积变化的最佳预测因素,与非黏膜下位置相比,其体积变化增加 32.2%(<.001)。T2 加权 MRI 高信号是预测子宫肌瘤体积变化的第二大预测因素,与低信号子宫肌瘤相比,其体积变化增加 16.9%(=.013)。基线子宫肌瘤体积较小(< 58cm)与较大的子宫肌瘤相比,体积变化增加 10.2%(=.01)。在 SI 上呈高信号的子宫肌瘤与呈低信号的子宫肌瘤相比,体积变化增加 7.9%(=.014)。五变量 ROC 模型具有较高的诊断准确性,AUC 为 0.85,灵敏度为 82%,特异性为 71%。黏膜下位置、T2 加权 MRI 高信号、基线子宫肌瘤体积较小(< 58cm)和 SI 上高信号的子宫肌瘤是 UAE 后子宫肌瘤体积变化的主要独立有利预测因素。建立了一个准确的预测 ROC 模型,可能有助于选择适合 UAE 的患者。T2 加权 MRI 异质性的定量评估显示出作为体积变化预测指标的有前途的结果,建议在该领域使用纹理分析和放射组学进行进一步研究。

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