Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China.
Department of Pathology, West China Hospital of Sichuan University, Chengdu, China; Huaxi Glioma Center, West China Hospital of Sichuan University, Chengdu, China.
World Neurosurg. 2023 Jul;175:e1283-e1291. doi: 10.1016/j.wneu.2023.04.118. Epub 2023 May 4.
To explore the predictive value of quantitative features extracted from conventional magnetic resonance imaging (MRI) in distinguishing Zinc Finger Translocation Associated (ZFTA)-RELA fusion-positive and wild-type ependymomas.
Twenty-seven patients with pathologically confirmed ependymomas (17 patients with ZFTA-RELA fusions and 10 ZFTA-RELA fusion-negative patients) who underwent conventional MRI were enrolled in this retrospective study. Two experienced neuroradiologists who were blinded to the histopathological subtypes independently extracted imaging features using Visually Accessible Rembrandt Images annotations. The consistency between the readers was evaluated with the Kappa test. The imaging features with significant differences between the 2 groups were obtained using the least absolute shrinkage and selection operator regression model. Logistic regression analysis and receiver operating characteristic analysis were performed to analyze the diagnostic performance of the imaging features in predicting the ZFTA-RELA fusion status in ependymoma.
There was a good interevaluator agreement on the imaging features (kappa value range 0.601-1.000). Enhancement quality, thickness of the enhancing margin, and edema crossing the midline have high predictive performance in identifying ZFTA-RELA fusion-positive and ZFTA-RELA fusion-negative ependymomas (C-index = 0.862 and area under the curve= 0.8618).
Quantitative features extracted from preoperative conventional MRI by Visually Accessible Rembrandt Images provide high discriminatory accuracy in predicting the ZFTA-RELA fusion status of ependymoma.
探讨从常规磁共振成像(MRI)中提取的定量特征在区分锌指转录因子相关(ZFTA)-RELA 融合阳性和野生型室管膜瘤中的预测价值。
本回顾性研究纳入了 27 例经病理证实的室管膜瘤患者(17 例 ZFTA-RELA 融合阳性,10 例 ZFTA-RELA 融合阴性),所有患者均接受了常规 MRI 检查。两位经验丰富的神经放射科医生对患者的 MRI 图像进行了分析,他们对组织病理学亚型并不知情。两位医生使用 Visually Accessible Rembrandt Images 注释工具独立提取了影像特征,然后通过 Kappa 检验评估了读者之间的一致性。采用最小绝对值收缩和选择算子回归模型获取两组间存在显著差异的影像特征。通过逻辑回归分析和受试者工作特征曲线分析,评估了这些影像特征在预测室管膜瘤中 ZFTA-RELA 融合状态方面的诊断性能。
两位评估者在影像特征方面具有良好的一致性(kappa 值范围为 0.601-1.000)。增强质量、增强边界的厚度以及水肿是否跨越中线对识别 ZFTA-RELA 融合阳性和 ZFTA-RELA 融合阴性室管膜瘤具有较高的预测性能(C 指数=0.862,曲线下面积=0.8618)。
通过 Visually Accessible Rembrandt Images 从术前常规 MRI 中提取的定量特征能够高度准确地预测室管膜瘤中 ZFTA-RELA 融合状态。