Fu Jia, Lin Zhiyong, Zhang Bihui, Qiu Jianxing, Yang Min, Zou Yinghua
Department of Radiology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua Medicine, Tsinghua University, Beijing, China.
Department of Radiology, Peking University First Hospital, Beijing, China.
Cardiovasc Intervent Radiol. 2025 May 12. doi: 10.1007/s00270-025-04007-9.
To investigate magnetic resonance imaging (MRI)-based radiomics for predicting renal function response for patients treated for atherosclerotic renal artery stenosis (ARAS) by endoluminal means.
A cohort of 146 ARAS patients who underwent stenting was analyzed, with retrospective training and prospective validation groups delineated based on the treatment timing. Patients were categorized into benefit and no-benefit groups based on postoperative renal function during follow-up. Optimal radiomics labels were selected from regions of interest (ROIs) including the stenotic side and both kidneys. The nomogram combined optimal radiomics signatures with independent clinical factors using multivariable logistic regression. Shapley Additive exPlanations (SHAP), decision curve analysis (DCA), the net reclassification index (NRI), and the total integrated discrimination index (IDI) were conducted to determine the clinical usefulness of the nomogram.
Split renal function of the stenotic side and diabetes emerged as independent clinical predictors. A nomogram, incorporating these clinical factors and radiomics features from the stenotic side and both kidneys, achieved area under the curve (AUCs) of 0.927 (0.861-0.979) and 0.904 (0.819-0.972) in the training and test groups, respectively, for predicting benefits. The clinical-radiomics model significantly improved diagnostic performance (p = 0.001 and p = 0.011 for the training and test groups, respectively). DCA, NRI, and IDI analyses suggested the nomogram's superiority. SHAP analysis highlighted the radiomics feature from stenotic side kidney as the most critical predictive feature.
Both MRI radiomics and clinical factors may be valuable in pre-treatment counseling of ARAS patients who may benefit from endovascular treatment.
研究基于磁共振成像（MRI）的放射组学，以预测经腔内治疗的动脉粥样硬化性肾动脉狭窄（ARAS）患者的肾功能反应。
分析了146例接受支架置入术的ARAS患者队列，并根据治疗时间划定回顾性训练组和前瞻性验证组。根据随访期间的术后肾功能将患者分为受益组和非受益组。从包括狭窄侧和双肾的感兴趣区域（ROI）中选择最佳放射组学标签。使用多变量逻辑回归将列线图与独立临床因素相结合，生成最佳放射组学特征。进行Shapley加性解释（SHAP）、决策曲线分析（DCA）、净重新分类指数（NRI）和总综合鉴别指数（IDI），以确定列线图的临床实用性。
狭窄侧的分肾功能和糖尿病是独立的临床预测因素。一个结合了这些临床因素以及狭窄侧和双肾的放射组学特征的列线图，在训练组和测试组中预测受益的曲线下面积（AUC）分别为0.927（0.861 - 0.979）和0.904（0.819 - 0.972）。临床 - 放射组学模型显著提高了诊断性能（训练组和测试组的p值分别为0.001和0.011）。DCA、NRI和IDI分析表明列线图具有优越性。SHAP分析突出显示狭窄侧肾脏的放射组学特征是最关键的预测特征。
MRI放射组学和临床因素在可能从血管内治疗中受益的ARAS患者的治疗前咨询中可能都具有价值。
