Nonrigid active shape model-based registration framework for motion correction of cardiac T1 mapping

PurposeAccurate reconstruction of myocardial T-1 maps from a series of T-1-weighted images consists of cardiac motions induced from breathing and diaphragmatic drifts. We propose and evaluate a new framework based on active shape models to correct for motion in myocardial T-1 maps. MethodsMultiple appearance models were built at different inversion time intervals to model the blood-myocardium contrast and brightness changes during the longitudinal relaxation. Myocardial inner and outer borders were automatically segmented using the built models, and the extracted contours were used to register the T-1-weighted images. Data acquired from 210 patients using a free-breathing acquisition protocol were used to train and evaluate the proposed framework. Two independent readers evaluated the quality of the T-1 maps before and after correction using a four-point score. The mean absolute distance and Dice index were used to validate the registration process. ResultsThe testing data set from 180 patients at 5 short axial slices showed a significant decrease of mean absolute distance (from 3.31.6 to 2.3 +/- 0.8mm, P<0.001) and increase of Dice (from 0.89 +/- 0.08 to 0.94 +/- 0.4%, P<0.001) before and after correction, respectively. The T-1 map quality improved in 70 +/- 0.3% of the motion-affected maps after correction. Motion-corrupted segments of the myocardium reduced from 21.8 to 8.5% (P<0.001) after correction. ConclusionThe proposed method for nonrigid registration of T-1-weighted images allows T-1 measurements in more myocardial segments by reducing motion-induced T-1 estimation errors in myocardial segments. Magn Reson Med 80:780-791, 2018. (c) 2018 International Society for Magnetic Resonance in Medicine.