Suppression of pulmonary vasculature in lung perfusion MRI using correlation analysis.

The purpose of the study was to evaluate the feasibility of suppressing the pulmonary vasculature in lung perfusion MRI using cross-correlation analysis (CCA). Perfusion magnetic resonance imaging (MRI) (3D FLASH, TR/TE/flip angle: 0.8 ms/2.1 ms/40 degrees ) of the lungs was performed in seven healthy volunteers at 1.5 Tesla after injection of Gd-DTPA. CCA was performed pixel-wise in lung segmentations using the signal time-course of the main pulmonary artery and left atrium as references. Pixels with high correlation coefficients were considered as arterial or venous and excluded from further analysis. Quantitative perfusion parameters [pulmonary blood flow (PBF) and volume (PBV)] were calculated for manual lung segmentations separately, with the entire left and right lung with all intrapulmonary vessels (IPV) included, excluded manually or excluded using CCA. The application of CCA allowed reliable suppression of hilar and large IPVs. Using vascular suppression by CCA, perfusion parameters were significantly reduced (p </= 0.001). The reduction was 8% for PBF and 13% for PBV compared with manual exclusion and 15% for PBF and 25% for PBV when all vessel structures were included. The application of CCA improves the visualisation and quantification of lung perfusion in MRI. Overestimation of perfusion parameters caused by pulmonary vessels is significantly reduced.