Comparative evaluation of MR-based partial-volume correction schemes for PET

Abstract

Because of limitations of spatial resolution, quantitative PET measurements of cerebral blood flow, glucose metabolism and neuroreceptor binding are influenced by partial-volume averaging among neighboring tissues with differing tracer concentrations.

Methods: Two MR-based approaches to partial-volume correction of PET images were compared using simulations and a multicompartment phantom. The two-compartment method corrects PET data for the diluting effects of cerebrospinal fluid (CSF) spaces. The more complex three-compartment method also accounts for the effect of partial-volume averaging between gray and white matter. The effects of the most significant sources of error on MR-based partial-volume correction, including misregistration, resolution 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 three-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 suited for comparative PET studies, whereas the three-compartment algorithm is capable of greater accuracy for absolute quantitative measures.