Rapid algorithms for the construction of cerebral blood flow and oxygen utilization images with oxygen-15 and dynamic positron emission tomography

Two rapid estimation algorithms for construction of cerebral blood flow (CB F) and oxygen utilization (CMRO) images with dynamic positron emission tomo graphy (PET) are presented. These algorithms are based on the linear least squares (LLS) and generalized linear least squares (GLLS) methodologies. Us ing the conventional two-compartmental model and multiple tracer studies, w e derived a linear relationship for brain tissue activity to arterial blood activity, time-integrated arterial blood activity and time-integrated brai n tissue activity. The LLS technique is computationally efficient as no reg ression analysis is required, while GLLS is used to refine the estimates ob tained from LLS. A comparative study using non-linear least squares regress ion (NLS) revealed excellent correlation between the new algorithms for var ious noise levels expected in clinical applications. A sensitivity analysis was performed to examine reliability and identifiability of the parameter estimates. In view of the results, LLS and GLLS provide rapid and reliable estimates of CBF and CMRO when applied to dynamic PET data. These algorithm s are particularly suitable for pixel-by-pixel construction of high resolut ion and highly accurate PET functional images. (C) 1999 Elsevier Science Ir eland Ltd. All rights reserved.