Because of limitations of spatial resolution, quantitative PET measurements
of cerebral blood flow, glucose metabolism and neuroreceptor binding are i
nfluenced by partial-volume averaging among neighboring tissues with differ
ing tracer concentrations. Methods: Two MR-based approaches to partial-volu
me correction of PET images were compared using simulations and a multicomp
artment phantom. The two-compartment method corrects PET data for the dilut
ing effects of cerebrospinal fluid (CSF) spaces. The more complex three-com
partment method also accounts for the effect of partial-volume averaging be
tween gray and white matter. The effects of the most significant sources of
error on MR-based partial-volume correction, including misregistration, re
solution mismatch, segmentation errors and white matter heterogeneity, were
evaluated. We also examined the relative usefulness of both approaches in
PET studies of aging and neurodegenerative disease. Results: Although the t
hree-compartment method was highly accurate (with 100% gray matter recovery
achieved in simulations), it was also more sensitive to all errors tested,
particularly image segmentation and PET-MR registration. Conclusion: Based
on these data, we conclude that the two-compartment approach is better sui
ted for comparative PET studies, whereas the three-compartment algorithm is
capable of greater accuracy for absolute quantitative measures.