Riyahi Sadjad, Dev Hreedi, Blumenfeld Jon D, Rennert Hanna, Yin Xiaorui, Attari Hanieh, Barash Irina, Chicos Ines, Bobb Warren, Donahue Stephanie, Prince Martin R
Department of Radiology, Weill Cornell Medicine, New York, New York, USA.
The Rogosin Institute, New York, New York, USA.
J Magn Reson Imaging. 2021 Feb;53(2):564-576. doi: 10.1002/jmri.27360. Epub 2020 Sep 23.
Screening for rapidly progressing autosomal dominant polycystic kidney disease (ADPKD) is necessary for assigning and monitoring therapies. Height-adjusted total kidney volume (ht-TKV) is an accepted biomarker for clinical prognostication, but represents only a small fraction of information on abdominal MRI.
To investigate the utility of other MR features of ADPKD to predict progression.
Single-center retrospective.
Longitudinal data from 186 ADPKD subjects with baseline serum creatinine, PKD gene testing, abdominal MRI measurements, and ≥2 follow-up serum creatinine were reviewed.
FIELD STRENGTH/SEQUENCE: 1.5T, T -weighted single-shot fast spin echo, T -weighted 3D spoiled gradient echo (liver accelerated volume acquisition) and 2D cine velocity encoded gradient echo (phase contrast MRA).
Ht-TKV, renal blood flow (RBF), number and fraction of renal and hepatic cysts, bright T hemorrhagic renal cysts, and liver and spleen volumes were independently assessed by three observers blinded to estimated glomerular filtration rate (eGFR) data.
Linear mixed-effect models were applied to predict eGFR over time using MRI features at baseline adjusted for confounders. Validation was performed in 158 patients who had follow-up MRI using receiver operator characteristic, sensitivity, and specificity.
Hemorrhagic cysts, fraction of renal and hepatic cysts, height-adjusted liver and spleen volumes were significant independent predictors of future eGFR (final prediction model R = 0.88 P < 0.05). The number of hemorrhagic cysts significantly improved the prediction compared to ht-TKV in predicting future eGFR (area under the curve [AUC] = 0.94, 95% confidence interval [CI]: 0.9-0.94 vs. R = 0.9, 95% CI: 0.85-0.9, P = 0.045). For baseline eGFR ≥60 ml/min/1.73m , sensitivity for predicting eGFR<45 ml/min/1.73m by ht-TKV alone was 29%. Sensitivity increased to 72% with all MRI variables in the model (P < 0.05 = 0.019), whereas specificity was unchanged, 100% vs. 99%.
Combining multiple MR features including hemorrhagic renal cysts, renal cyst fraction, liver and spleen volume, hepatic cyst fraction, and renal blood flow enhanced sensitivity for predicting eGFR decline in ADPKD compared to the standard model including only ht-TKV. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:564-576.
筛查快速进展的常染色体显性遗传性多囊肾病（ADPKD）对于确定和监测治疗方案很有必要。身高校正后的总肾体积（ht-TKV）是临床预后的公认生物标志物，但仅占腹部MRI信息的一小部分。
研究ADPKD的其他磁共振成像（MR）特征对预测疾病进展的作用。
单中心回顾性研究。
回顾了186例ADPKD患者的纵向数据，这些患者有基线血清肌酐、PKD基因检测、腹部MRI测量结果，且有≥2次随访血清肌酐数据。
场强/序列：1.5T，T加权单次激发快速自旋回波序列、T加权三维扰相梯度回波序列（肝脏加速容积采集）和二维电影速度编码梯度回波序列（相位对比磁共振血管造影）。
由三位对估计肾小球滤过率（eGFR）数据不知情的观察者独立评估ht-TKV、肾血流量（RBF）、肾囊肿和肝囊肿的数量及比例、T高信号出血性肾囊肿以及肝脏和脾脏体积。
应用线性混合效应模型，使用基线时经混杂因素校正的MRI特征预测随时间变化的eGFR。对158例进行了随访MRI检查患者，采用受试者工作特征曲线、敏感性和特异性进行验证。
出血性囊肿、肾囊肿和肝囊肿比例、身高校正后的肝脏和脾脏体积是未来eGFR的显著独立预测因素（最终预测模型R = 0.88，P < 0.05）。与ht-TKV相比，出血性囊肿数量在预测未来eGFR方面显著提高了预测能力（曲线下面积[AUC] = 0.94，95%置信区间[CI]：0.9 - 0.94 vs. R = 0.9，95% CI：0.85 - 0.9，P = 0.045）。对于基线eGFR≥60 ml/min/1.73m²，仅用ht-TKV预测eGFR<45 ml/min/1.73m²的敏感性为29%。模型中纳入所有MRI变量后，敏感性增至72%（P < 0.05 = 0.019），而特异性不变，分别为100%和99%。
与仅包括ht-TKV的标准模型相比，综合出血性肾囊肿、肾囊肿比例、肝脏和脾脏体积、肝囊肿比例以及肾血流量等多种MR特征，可提高预测ADPKD患者eGFR下降的敏感性。证据等级2 技术效能分级2 J.MAGN.RESON.IMAGING 2021;53:56
