A study on statistically reliable and computationally efficient algorithms for generating local cerebral blood flow parametric images with positron emission tomography

Journal Article · Tue Jun 01 00:00:00 EDT 1993 · IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States)

DOI:https://doi.org/10.1109/42.232247· OSTI ID:6145794

Feng, Dagan; Wang, Zhizhong ^[1]; Huang, Sung Cheng ^[2]

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1. Univ. of Sydney (Australia). Basser Dept. of Computer Science
2. Univ. of California, Los Angeles, CA (United States). Dept. of Radiological Sciences

With the advent of positron emission tomography (PET), a variety of techniques have been developed to measure local cerebral blood flow (LCBF) noninvasively in humans. It is essential that the techniques developed should be statistically reliable and computationally efficient. A potential class of techniques, which includes linear least squares (LS), linear weighted least squares (WLS), linear generalized least squares (GLS), and linear generalized weighted least squares (GWLS), is proposed. The statistical characteristics of the new methods were examined by computer simulation. The authors present a comparison of these four methods with two other rapid estimation techniques developed by Huang et al. and Alpert, and two classical methods, the unweighted and weighted nonlinear least squares regression which are supposed to have optimal statistical properties. The results show that the new methods can take full advantage of the contribution from the fine temporal sampling data of modern tomographs, and thus provide statistically reliable estimates that are comparable to those obtained from nonlinear least squares regression. The new methods also have high computational efficiency, and the parameters can be estimated directly from operational equations in one single step. Therefore, they can potentially be used in image-wide estimation of local cerebral blood flow and distribution volume with positron emission tomography.

• OSTI ID: 6145794
• Journal Information: IEEE Transactions on Medical Imaging (Institute of Electrical and Electronics Engineers); (United States), Vol. 12:2; ISSN 0278-0062
• Country of Publication: United States
• Language: English

Related Subjects

62 RADIOLOGY AND NUCLEAR MEDICINE
BRAIN
POSITRON COMPUTED TOMOGRAPHY
CEREBRAL CORTEX
BLOOD FLOW
RELIABILITY
ALGORITHMS
COMPUTERIZED SIMULATION
LEAST SQUARE FIT
BODY
CENTRAL NERVOUS SYSTEM
CEREBRUM
COMPUTERIZED TOMOGRAPHY
DIAGNOSTIC TECHNIQUES
EMISSION COMPUTED TOMOGRAPHY
MATHEMATICAL LOGIC
MAXIMUM-LIKELIHOOD FIT
NERVOUS SYSTEM
NUMERICAL SOLUTION
ORGANS
SIMULATION
TOMOGRAPHY
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