Comparative Performance of Quantitative and Qualitative Magnetic Resonance Imaging Metrics in Primary Sclerosing Cholangitis

Abstract

<h3>Background and Aims</h3> Several quantitative and qualitative magnetic resonance imaging (MRI) metrics have been reported to predict outcomes among those with primary sclerosing cholangitis (PSC). We aimed to compare the reproducibility and prognostic performances of MRI biomarkers and examine if combining these measurements adds value. <h3>Methods</h3> We performed a retrospective review of 388 patients with PSC who underwent a magnetic resonance elastography and magnetic resonance cholangiopancreatography. Liver stiffness (LS) was determined by validated automated software, whereas spleen volume was calculated by semiautomated software, and radiologists manually determined the ANALI scores. The primary endpoint was hepatic decompensation. <h3>Results</h3> LS and spleen volume values had perfect and near-perfect agreement (intraclass correlation coefficient of 1.00 and 0.9996, respectively), whereas ANALI with and without gadolinium had a moderate inter-rater agreement between 3 radiologists (kappa = 0.42–0.54 and 0.46–0.57, respectively). As a continuous variable, LS alone was the best predictor of hepatic decompensation (concordance score = 0.90; 95% confidence interval, 0.87–0.93). A quantitative-only MRI model [LS (>4.70 kPa = 2 or ≤4.70 kPa = 0) + spleen volume (>600 mm³ = 1 or ≤600 mm³ = 0)] had the optimal reproducibility and performance (concordance score = 0.85; 95% confidence interval = 0.80–0.89) and enabled patient risk stratification by estimating the 5-year incidence of hepatic decompensation: 7.49%, 44.50%, 70.00%, and 91.30% (score 0–3). <h3>Conclusion</h3> Quantitative MRI markers of fibrosis and portal hypertension generated by automated and semiautomated software are highly reproducible. LS is the single best imaging predictor of hepatic decompensation. However, a quantitative MRI score using LS and spleen volume is well suited to risk stratify those with PSC.