Feasibility of simultaneous whole-brain imaging on an integrated PET-MRI system using an enhanced 2-point Dixon attenuation correction method - Anazodo, Udunna C.; Thiessen, Jonathan D.; Ssali, Tracy; Mandel, Jonathan; Günther, Matthias; Butler, John; Pavlosky, William; Prato, Frank S.; Thompson, R. Terry; St. Lawrence, Keith S. (Frontiers in Neuroscience, 2015)
Purpose: To evaluate a potential approach for improved attenuation correction (AC) of PET in simultaneous PET and MRI brain imaging, a straightforward approach that adds bone information missing on Dixon AC was explored. Methods: Bone information derived from individual T1-weighted MRI data using segmentation tools in SPM8, were added to the standard Dixon AC map. Percent relative difference between PET reconstructed with Dixon+bone and with Dixon AC maps were compared across brain regions of 13 oncology patients. The clinical potential of the improved Dixon AC was investigated by comparing relative perfusion (rCBF) measured with arterial spin labeling to relative glucose uptake (rPETdxbone) measured simultaneously with 18F-flurodexoyglucose in several regions across the brain. Results: A gradual increase in PET signal from center to the edge of the brain was observed in PET reconstructed with Dixon+bone. A 5-20% reduction in regional PET signals were observed in data corrected with standard Dixon AC maps. These regional underestimations of PET were either reduced or removed when Dixon+bone AC was applied. The mean relative correlation coefficient between rCBF and rPETdxbone was r = 0.53 (p<0.001). Marked regional variations in rCBF-to-rPET correlation were observed, with the highest associations in the caudate and cingulate and the lowest in limbic structures. All findings were well matched to observations from previous studies conducted with PET data reconstructed with computed tomography derived AC maps. Conclusion: Adding bone information derived from T1-weighted MRI to Dixon AC maps can improve underestimation of PET activity in hybrid PET-MRI neuroimaging.