Department of Radiology, Weill Cornell Medicine, New York, 10022, USA.
The Rogosin Institute, New York, 10021, USA.
Sci Rep. 2024 Jun 14;14(1):13794. doi: 10.1038/s41598-024-62776-8.
Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was compared to ( ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or ( ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( ) and PKD2 mutation ( ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.
梅奥影像学分类（MIC）用于预测常染色体显性多囊肾病（ADPKD）患者未来的肾脏生长，其计算基于单次 MRI/CT 扫描，假设肾脏体积呈指数增长，出生时身高校正的总肾脏体积为 150 mL/m。然而，当有多份扫描结果时，如何结合这些信息以提高预测准确性尚不清楚。在此，我们研究了具有 8 年以上影像学随访（平均 11 年）的 ADPKD 患者（），以建立真实的肾脏生长轨迹。将 MIC 的年度肾脏生长率预测与真实值以及 1 参数和 2 参数最小二乘法拟合进行比较。MIC 预测总肾脏体积增长率的年化平均绝对误差为，而当有 4 次测量值时，2 参数拟合相同的 MIC 所使用的指数生长曲线的平均绝对误差为，当有 3 次测量值与 MIC 一起平均时的平均绝对误差为。单因素分析显示，男性（）和 PKD2 突变（）与 MIC 性能较差相关。在有 3 次或更多 CT/MRI 扫描的 ADPKD 患者中，2 参数最小二乘法拟合预测肾脏体积增长率优于 MIC，尤其是在男性和 PKD2 突变患者中，MIC 准确性较差。
