医学
肾脏疾病
比例危险模型
有效扩散系数
峰度
危险系数
生物标志物
磁共振成像
阶段(地层学)
内科学
泌尿科
肿瘤科
接收机工作特性
放射科
肾功能
置信区间
古生物学
生物化学
统计
化学
数学
生物
作者
Yan Liu,Gumuyang Zhang,Xiaoyan Peng,Xuemei Li,Hao Sun,Limeng Chen
摘要
ABSTRACT Background Renal fibrosis is the strongest prognostic predictor of end-stage renal disease (ESRD) in chronic kidney disease (CKD). Diffusion kurtosis imaging (DKI) is a promising method of magnetic resonance imaging successfully used to assess renal fibrosis in immunoglobulin A nephropathy. This study aimed to be the first to evaluate the long-term prognostic value of DKI in CKD patients. Methods Forty-two patients with CKD were prospectively enrolled, and underwent DKI on a clinical 3T MR scanner. We excluded patients with comorbidities that could affect the volume or the components of the kidney. DKI parameters, including mean Kurtosis (K), mean diffusivity and apparent diffusion coefficient (ADC) of kidney cortex were obtained by region-of-interest measurement. We followed up these patients for a median of 43 months and investigated the correlations between each DKI parameter and overall renal prognosis. Results Both K and ADC values were correlated well with the estimated glomerular filtration rate (eGFR) on recruitment and the eGFR of the last visit in follow-up (P ˂ 0.001). K and ADC values were also well associated with the eGFR slopes in CKD patients, both with the first–last time point slope (P = 0.011 and P ˂ 0.001, respectively) and with the regression slope (P = 0.010 and P ˂ 0.001, respectively). Cox proportional hazard regression indicated that lower eGFR and ADC values independently predicted eGFR loss of ˃30% and ESRD. The receiver operating characteristic analysis showed that K and ADC values were predictable for renal prognosis, and ADC displayed better capabilities for both ESRD [area under the curve (AUC) 0.936, sensitivity 92.31%, specificity 82.76%] and the composite endpoint (eGFR loss ˃30% or ESRD) (AUC 0.881, sensitivity 66.67%, specificity 96.3%). Conclusions Renal ADC values obtained from DKI showed significant predictive value for the prognosis of CKD patients, which could be a promising noninvasive technique in follow-up.
科研通智能强力驱动
Strongly Powered by AbleSci AI