Cardiac Magnetic Resonance-Derived Parametric Mapping Radiomics for Prediction of Left Ventricular Reverse Remodeling...

We investigated whether radiomic scores (RadScores), computed from high-dimensional quantitative features extracted from cardiac magnetic resonance parametric mapping images, can predict left ventricular reverse remodeling (LVRR) in patients with nonischemic dilated cardiomyopathy.

This retrospective analysis included 74 patients with nonischemic dilated cardiomyopathy who received optimized medical therapy and underwent cardiac magnetic resonance. LVRR was defined as a left ventricular ejection fraction ≥40% with ≥10% increase at least 180 days after cardiac magnetic resonance. RadScores were calculated for each case as linear combinations of selected radiomic features, with coefficients derived from least absolute shrinkage and selection operator-penalized logistic regression on native longitudinal relaxation time (T1) and extracellular volume (ECV) fraction maps. Predictive performance for LVRR was evaluated using logistic regression and receiver operating characteristic analyses.

Patients with LVRR (n=31, 42%) had higher T1-RadScore (0.72±1.52 versus -1.54±2.66; P<0.0001), higher ECV-RadScore (0.24±0.65 versus -0.16±0.64; P=0.005), lower mean-ECV (31.5%±3.8% versus 34.9%±6.0%; P=0.004), and lower extent of late gadolinium enhancement (0.19±0.58 versus 2.99±6.5; P=0.047) than those without LVRR. The area under the receiver operating characteristic curve for predicting LVRR was 0.834 (95% CI, 0.716-0.909) for the T1-RadScore and 0.718 (95% CI, 0.573-0.827) for the ECV-RadScore. Adding T1- and ECV-RadScore combination to the extent of late gadolinium enhancement model significantly improved the area under the receiver operating characteristic curve from 0.618 to 0.903 (P<0.0001).

Radiomic scores extracted from native T1 and ECV maps may enhance LVRR prediction and provide incremental value beyond traditional late gadolinium enhancement assessment in patients with dilated cardiomyopathy.