Robust Fitting of [11C]-WAY-100635 PET Data

Fitting of a positron emission tomography (PET) time–activity curve is typically accomplished according to the least squares (LS) criterion, which is optimal for data having Gaussian distributed errors, but not robust in the presence of outliers. Conversely, quantile regression (QR) provides robust...

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Bibliographic Details
Published in:Journal of cerebral blood flow and metabolism 2010-07, Vol.30 (7), p.1366-1372
Main Authors: Zanderigo, Francesca, Ogden, Robert Todd, Chang, Chung, Choy, Stephen, Wong, Andrew, Parsey, Ramin Vaziri
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Biological and medical sciences
Brain - anatomy & histology
Brain - metabolism
Carbon Radioisotopes - chemistry
Carbon Radioisotopes - metabolism
Disorders of higher nervous function. Focal brain diseases. Central vestibular syndrome and deafness. Brain stem syndromes
Female
Humans
Image Interpretation, Computer-Assisted - methods
Male
Medical sciences
Middle Aged
Models, Biological
Nervous system (semeiology, syndromes)
Neurology
Normal Distribution
Original
Piperazines - chemistry
Piperazines - metabolism
Positron-Emission Tomography - methods
Pyridines - chemistry
Pyridines - metabolism
Radiopharmaceuticals - chemistry
Radiopharmaceuticals - metabolism
Serotonin Antagonists - chemistry
Serotonin Antagonists - metabolism
Vascular diseases and vascular malformations of the nervous system
Young Adult
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Description
Summary:Fitting of a positron emission tomography (PET) time–activity curve is typically accomplished according to the least squares (LS) criterion, which is optimal for data having Gaussian distributed errors, but not robust in the presence of outliers. Conversely, quantile regression (QR) provides robust estimates not heavily influenced by outliers, sacrificing a little efficiency relative to LS when no outliers are present. Given these considerations, we hypothesized that QR would improve parameter estimate accuracy as measured by reduced intersubject variance in distribution volume (VT) compared with LS in PET modeling. We compare VT values after applying QR with those using LS on 49 controls studied with [11C]-WAY-100635. QR decreases the standard deviation of the VT estimates (relative improvement range: 0.08% to 3.24%), while keeping the within-group average VT values almost unchanged. QR variance reduction results in fewer subjects required to maintain the same statistical power in group analysis without additional hardware and/or image registration to correct head motion.
ISSN:0271-678X
1559-7016
DOI:10.1038/jcbfm.2010.20