Novel approach to MRI based risk stratification of uterine myometrial lesions

IF 3.2 3区医学 Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

European Journal of Radiology Pub Date : 2025-04-17 DOI:10.1016/j.ejrad.2025.112126

Eva Zlotykamien-Taieb , Diana Gherman , Rana Al Rouhban , Marie Florin , Emile Darai , Bassam Haddad , Yohann Dabi , Safaa Arbel , Priyanka Jha , Isabelle Thomassin-Naggara

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引用次数: 0

Abstract

Background

Surgery for uterine mesenchymal tumors is common in gynecology. Preoperative diagnosis of malignant tumors can lead to appropriate management for the lesions.

Purpose

This study aims to externally validate a previous MRI-based expert consensus algorithm and evaluate the potential modification of MR-based scoring system’s accuracy in diagnosing uterine mesenchymal tumors (UMT).

Material and methods

With institutional ethics committee approval and a waiver of informed consent (CRM-2405–410), a bicentric retrospective observational cohort study was conducted from January 2018 to December 2023. The study included women with a pathological diagnosis of uterine mesenchymal tumor following a pelvic MRI within six months. Clinical and MR criteria were blindly recorded by two radiologists (6- and 3-years’ experience in gynaecological MR imaging) who assessed several MR features. Continuous variables were analyzed using a Mann–Whitney test, and categorical variables using Fisher’s exact test. Odds ratios (OR) for predicting malignancy were calculated with 95% confidence intervals and p-values.

Results

The cohort included 455 women (mean age: 43 years, range: 15–82 years) with mesenchymal tumors: 437 leiomyomas, 2 STUMPs (0.4 %), and 16 malignant UMT (3.5 %). Using initial criteria (enlarged pelvic lymph nodes, T2W signal intensity, DW signal intensity compared to endometrium, and ADC cutoff value of 0.9 × 10⁻³ mm²/sec), the model accurately classified 421 out of 455 cases (Accuracy: 92,5% (CI 93,1–94,3) and missed with 7 tumors (5 leiomyosarcomas, 2 STUMP). The sensitivity was 61.1 % (CI95% 38.5–83.6) and specificity was 93.8 % (CI95% 91.2–95.8) A modified algorithmic approach added “irregular tumor margins” and menopausal status, modified DW signal compared to bladder, and an elevated ADC cutoff value of 1.23 × 10⁻³ mm²/sec, improving classification to 446 out of 455 cases (Accuracy: 98 % (CI95% 97.1 %-98.1 %) with only 3 missed tumors (2 STUMP and one leiomyosarcoma). The sensitivity was 83.3 % (CI95% 79–88) and specificity was 98.6 % (CI95% 98–99). The new algorithm significantly improved accuracy (p = 0.001), allowing the development of a 5-category scoring system.

Conclusion

Modified MR imaging evaluation algorithms increase true positive diagnosis of malignant UMTs leading to effective differentiation from benign leiomyomas. The new algorithm can allow for appropriate triage of potentially malignant UMTs, alleviating risk associated with morcellation in patients with uterine leiomyosarcoma.

Summary

Our study demonstrates that combining 5 criteria based on multivariate analysis in a new algorithm (T2W signal, DW signal, ADC cut off value of 1.23 x 10–3 mm2/sec, tumor margins and menopausal status) allows us to distinguish benign from malignant uterine mesenchymal tumors with an accuracy of 98 % (CI95% 97,1%-98,1%), a sensitivity of 83.3 % (CI95% 79–88) and a specificity of 98.6 % (CI95% 98–99). This model allows to build a stratification score that would help in the management of typical and atypical uterine lesions.

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基于MRI的子宫肌层病变危险分层新方法

背景子宫间质肿瘤的手术治疗在妇科很常见。恶性肿瘤的术前诊断可以导致对病变的适当处理。目的本研究旨在外部验证先前基于mri的专家共识算法，并评估基于mri的评分系统诊断子宫间充质肿瘤（UMT）准确性的潜在修改。材料和方法经机构伦理委员会批准和知情同意豁免（CRM-2405-410），于2018年1月至2023年12月进行了一项双中心回顾性观察队列研究。该研究包括六个月内盆腔MRI病理诊断为子宫间质瘤的妇女。临床和磁共振标准由两名放射科医生（分别有6年和3年的妇科磁共振成像经验）盲目记录，他们评估了几个磁共振特征。使用Mann-Whitney检验分析连续变量，使用Fisher精确检验分析分类变量。以95%置信区间和p值计算预测恶性肿瘤的优势比（OR）。结果该队列包括455名女性（平均年龄：43岁，范围：15-82岁）间充质肿瘤：437例平滑肌瘤，2例STUMPs(0.4%)， 16例恶性UMT（3.5%）。使用初始标准（盆腔淋巴结肿大，T2W信号强度，与子宫内膜相比的DW信号强度，ADC截止值为0.9 × 10−3 mm2/sec），该模型准确分类421例（准确率：92.5% (CI 93,1 - 94,3)），漏诊7例（5例平滑肌肉瘤，2例STUMP）。灵敏度为61.1% (CI95% 38.5-83.6)，特异性为93.8% （CI95% 91.2-95.8）。一种改进的算法方法增加了“不规则肿瘤边缘”和绝经状态，与膀胱相比DW信号改善，ADC截止值升高1.23 × 10−3 mm2/sec，将455例患者的分类提高到446例(准确率：98% (CI95% 97.1% - 98.1%)，只有3例漏诊（2例STUMP和1例平滑肌肉瘤）。敏感性为83.3% (CI95% 79 ~ 88)，特异性为98.6% （CI95% 98 ~ 99）。新算法显著提高了准确率（p = 0.001），允许开发5类评分系统。结论改进的MR成像评估算法提高了恶性umt的真阳性诊断，从而有效地与良性平滑肌瘤鉴别。新的算法可以允许对潜在的恶性umt进行适当的分类，减轻子宫平滑肌肉瘤患者分块相关的风险。您的研究表明，结合基于多变量分析的5个标准（T2W信号、DW信号、ADC截止值1.23 × 10-3 mm2/sec、肿瘤边缘和绝经状态）的新算法，我们可以区分子宫间质肿瘤的良恶性，准确率为98% (CI95% 97,1%- 98.1%)，灵敏度为83.3% (CI95% 79-88)，特异性为98.6% （CI95% 98 - 99）。该模型允许建立一个分层评分，将有助于管理典型和非典型子宫病变。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

European Journal of Radiology 医学-核医学

CiteScore

6.70

自引率

3.00%

发文量

398

审稿时长

42 days

期刊介绍： European Journal of Radiology is an international journal which aims to communicate to its readers, state-of-the-art information on imaging developments in the form of high quality original research articles and timely reviews on current developments in the field. Its audience includes clinicians at all levels of training including radiology trainees, newly qualified imaging specialists and the experienced radiologist. Its aim is to inform efficient, appropriate and evidence-based imaging practice to the benefit of patients worldwide.