Iterative De-contrasted Image Registration Improves Quantification of Extracellular Volume and Fractional Myocardial Blood Volume

Motivation: Myocardial Extracellular Volume (ECV) and Fractional Myocardial Blood Volume (fMBV) maps, derived from T1 mapping before and after exogenous contrast agent administration, are highly susceptible to image mis-registration. Goal(s): We propose a de-contrast preprocessing step that minimizes contrast variance in regions of interest to improve overall group-wise image registration and mapping accuracy. Approach: An optimized de-contrasting and image registration framework was designed and applied to 11 ECV and 9 fMBV datasets. Registration results and resultant maps with and without de-contrast preprocessing were compared for accuracy and precision. Results: De-contrasting improved image registration accuracy and reduced parametric map variance in myocardial ECV and fMBV. Impact: Iterative de-contrast preprocessing is an effective approach for improving the accuracy of group-wise image registration and quality of parametric mapping in the myocardium in the setting of contrast enhancement.