Preoperative multiparametric MRI (mpMRI) helps predict patients' chronic kidney disease (CKD) risk after nephrectomy, according to a study published January 14 in the Journal of Magnetic Resonance Imaging.
Patients with solid renal masses are at risk of chronic kidney disease after surgical kidney removal, and currently, there is no reliable, preoperative predictor of this risk, wrote a team led by Mira Liu, PhD, of Icahn School of Medicine at Mount Sinai in New York City.
To address the issue, the group conducted a study to assess whether presurgical mpMRI could predict chronic kidney disease development and progression to stage III (moderate damage).
The research included 43 participants who underwent nephrectomy for solid renal masses. Each patient had 1.5-tesla, diffusion-weighted echo-planar imaging (DWI) MR imaging that included T1-mapping, multi-echo gradient-echo blood-oxygen-level-dependent (BOLD), and dynamic-contrast-enhanced MRI (DCE-MRI) using 3D T1-weighted gradient-echo.
The team calculated patients' CKD risk from estimated glomerular filtration rate (eGFR), age, diabetes status, and type of surgery (partial or radical nephrectomy).
Multiparametric MRI parameters included the following:
- Cortical and medullary apparent diffusion coefficient
- Intravoxel incoherent motion (IVIM)
- Tri-exponential diffusion (fast, medium, and slow)
- Spectral diffusion from DWI, native T1 from T1-mapping, R2* from BOLD, and renal plasma flow and eGFR from DCE-MRI
The main study outcome was mpMR parameters' correlation with baseline eGFR, prediction of postoperative 12-month eGFR decline (defined as > 5 mL/min/1.73 m2), and stage III CKD development (defined as eGFR < 60 mL/min/1.73 m2). Of the 43 study participants, 30 had normal baseline kidney function (eGFR ≥ 60 mL/min/1.73 m2). Twenty-nine patients completed a 12-month follow-up.
Liu and colleagues reported the following:
- Of the 29 patients, 66% (19 of 29) had normal eGFR at baseline, although 37% (7 of 19) developed stage III CKD.
- eGFR from DCE-MRI correlated with baseline eGFR (correlation coefficient, 0.43 and 0.33, respectively).
- Reduced vascular diffusion predicted eGFR decline (area under the receiver operating curve [AUC] = 0.75).
The group also found that a larger contralateral apparent diffusion coefficient corticomedullary difference (AUC = 0.89), and clinical chronic kidney disease risk score (AUC = 0.81) were the strongest predictors of CKD development -- a result that "may indicate reduced functional reserve," the authors concluded.
Access the full study here.















![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)


