A computationally efficient algorithm for determining regional cerebral blood flow in heterogeneous tissues by positron emission tomography

Citation
K. Schmidt et L. Sokoloff, A computationally efficient algorithm for determining regional cerebral blood flow in heterogeneous tissues by positron emission tomography, IEEE MED IM, 20(7), 2001, pp. 618-632
Citations number
33
Language
INGLESE
art.tipo
Article
Categorie Soggetti
Radiology ,Nuclear Medicine & Imaging","Eletrical & Eletronics Engineeing
Journal title
IEEE TRANSACTIONS ON MEDICAL IMAGING
ISSN journal
0278-0062 → ACNP
Volume
20
Issue
7
Year of publication
2001
Pages
618 - 632
Database
ISI
SICI code
0278-0062(200107)20:7<618:ACEAFD>2.0.ZU;2-U
Abstract
nclusion of brain tissues with different rates of blood flow and metabolism within a voxel or region of interest is an unavoidable problem with positr on emission tomography due to its limited spatial resolution. Because regio nal cerebral blood flow (rCBF) is higher in gray matter than in white matte r, the partial volume effect leads to underestimation of rCBF in gray matte r when rCBF in the region as a whole is determined. Furthermore, weighted-a verage rCBF itself is underestimated if the kinetic model used in the analy sis fails to account for the tissue heterogeneity. We have derived a comput ationally efficient method for estimating both gray matter and weighted-ave rage rCBF in heterogeneous tissues and validated the method in simulation s tudies. The method is based on a model that represents a heterogeneous tiss ue as a weighted mixture of two homogeneous tissues. A linear least squares algorithm is used to estimate the model parameters.