Perfusion quantification using voxel‐wise proton density and median signal decay in PREFUL MRI

PURPOSE Contrast-free lung MRI based on Fourier decomposition is an attractive method to monitor various lung diseases. However, the accuracy of the current perfusion quantification is limited. In this study, a new approach for perfusion quantification based on voxel-wise proton density and median signal decay toward the steady state for Fourier decomposition-based techniques is proposed called QQuantified (QQuant ). METHODS Twenty patients with chronic obstructive pulmonary disease and 18 patients with chronic thromboembolic pulmonary hypertension received phase-resolved functional lung-MRI (PREFUL) and dynamic contrast-enhanced (DCE)-MRI. Nine healthy participants received phase-resolved functional lung-MRI only. Median values of QQuant were compared to a Fourier decomposition perfusion quantification presented by Kjorstad et al (QKjorstad ) and validated toward pulmonary blood flow derived by DCE-MRI (PBFDCE ). Blood fraction maps determined by the new approach were calculated. Regional and global correlation coefficients were calculated, and Bland-Altman plots were created. Histogram analyses of all cohorts were created. RESULTS The introduced parameter QQuant showed only 2 mL/min/100 mL mean deviation to PBFDCE in the patient cohort and showed less bias than QKjorstad . Significant increases of regional correlation with PBFDCE were achieved (r = 0.3 vs. r = 0.2, P < .01*). The trend of global correlation toward PBFDCE is not uniform, showing higher values for QKjorstad in the chronic obstructive pulmonary disease cohort than for QQuant and vice versa in the chronic thromboembolic pulmonary hypertension cohort. In contrast to QKjorstad , QQuant perfusion maps indicate a physiologic dorsoventral gradient in supine position similar to PBFDCE with similar value distribution in the histograms. CONCLUSION We proposed a new approach for perfusion quantification of phase-resolved functional lung measurements. The developed parameter QQuant reveals a higher accuracy compared to QKjorstad .