Papers

Peer-reviewed
Dec, 2016

Impact of spillover from white matter by partial volume effect on quantification of amyloid deposition with [C-11]PiB PET

NEUROIMAGE
  • Keisuke Matsubara
  • ,
  • Masanobu Ibaraki
  • ,
  • Hitoshi Shimada
  • ,
  • Yoko Ikoma
  • ,
  • Tetsuya Suhara
  • ,
  • Toshibumi Kinoshita
  • ,
  • Hiroshi Itco

Volume
143
Number
First page
316
Last page
324
Language
English
Publishing type
Research paper (scientific journal)
DOI
10.1016/j.neuroimage.2016.09.028
Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE

High non-specific uptake of [C-11]Pittsburgh compound B ([C-11]PiB) in white matter and signal spillover from white matter, due to partial volume effects, confound radioactivity measured in positron emission tomography (PET) with [C-11]PiB. We aimed to reveal the partial volume effect in absolute values of kinetic parameters for [C-11]PiB, in terms of spillover from white matter. Dynamic data acquired in [C-11]PiB PET scans with five healthy volunteers and eight patients with Alzheimer's disease were corrected with region-based and voxel-based partial volume corrections. Binding potential (BPND) was estimated using the two-tissue compartment model analysis with a plasma input function. Partial volume corrections significantly decreased cortical BPND values. The degree of decrease in healthy volunteers (-52.7 +/- 5.8%) was larger than that in Alzheimer's disease patients (-11.9 +/- 4.2%). The simulation demonstrated that white matter spillover signals due to the partial volume effect resulted in an overestimation of cortical BPND, with a greater degree of overestimation for lower BPND values. Thus, an overestimation due to partial volume effects is more severe in healthy volunteers than in Alzheimer's disease patients. Partial volume corrections may be useful for accurately quantifying A beta deposition in cortical regions. (C) 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license.

Link information
DOI
https://doi.org/10.1016/j.neuroimage.2016.09.028
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000389683000028&DestApp=WOS_CPL
ID information
  • DOI : 10.1016/j.neuroimage.2016.09.028
  • ISSN : 1053-8119
  • eISSN : 1095-9572
  • Web of Science ID : WOS:000389683000028

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