Kwon Yeji, Yoon Jongjin, Jung Dae Chul, Oh Young Taik, Han Kyunghwa, Jung Minsun, Kang Byung Chul
Department of Radiology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Yonsei Med J. 2025 Apr;66(4):249-258. doi: 10.3349/ymj.2024.0082.
Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection.
Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations.
Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of non-TCMR categories (Banff categories 2, 5, and 6) (=0.026) and showed equal or higher AUC values than multiple machine learning classifiers.
Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.
肾移植排斥反应,无论是急性还是慢性,在许多受者中都很普遍。本研究旨在确定多个多普勒超声参数以预测肾移植排斥反应。
在2021年11月至2022年4月期间,对61例肾移植受者进行前瞻性研究,排除了2例接受双重移植的患者和7例患有肾积水的患者。分析排除了11例(10例因缺少多普勒数据或病理报告,1例因四分位数间距/中位数离散值过高),最终对50例患者进行分析。由三位经验丰富的泌尿生殖放射科医生评估临床特征、彩色多普勒成像、超微血管成像和剪切波成像参数。活检组织的班夫分类作为参考标准。采用单变量和多变量逻辑回归、列联表矩阵和多种机器学习模型来评估相关性。
对50例肾移植受者(平均年龄53.26±8.86岁;29例男性)进行了评估。弹性(≤14.8 kPa)在预测(临界)T细胞介导的排斥反应(TCMR)类别(班夫类别3和4)的组合方面显示出显著相关性(=0.006),并且与各种分类器相比,在受试者操作特征曲线(AUC)下的面积值相同或更高。离散度(>15.0 m/s/kHz)是预测非TCMR类别(班夫类别2、5和6)组合的唯一显著因素(=0.026),并且显示出与多个机器学习分类器相同或更高的AUC值。
弹性(≤14.8 kPa)与(临界)TCMR类别组合显示出显著相关性,而离散度(>15.0 m/s/kHz)与肾移植中非TCMR类别组合显著相关。