PMID- 25175542
OWN - NLM
STAT- MEDLINE
DCOM- 20150716
LR  - 20161125
IS  - 1095-9572 (Electronic)
IS  - 1053-8119 (Linking)
VI  - 102 Pt 2
DP  - 2014 Nov 15
TI  - Surface-based partial-volume correction for high-resolution PET.
PG  - 674-87
LID - S1053-8119(14)00711-3 [pii]
LID - 10.1016/j.neuroimage.2014.08.037 [doi]
AB  - Tissue radioactivity concentrations, measured with positron emission tomography 
      (PET) are subject to partial volume effects (PVE) due to the limited spatial 
      resolution of the scanner. Last generation high-resolution PET cameras with a 
      full width at half maximum (FWHM) of 2-4mm are less prone to PVEs than previous 
      generations. Corrections for PVEs are still necessary, especially when studying 
      small brain stem nuclei or small variations in cortical neuroreceptor 
      concentrations which may be related to cytoarchitectonic differences. Although 
      several partial-volume correction (PVC) algorithms exist, these are frequently 
      based on a priori assumptions about tracer distribution or only yield corrected 
      values of regional activity concentrations without providing PVE corrected 
      images. We developed a new iterative deconvolution algorithm (idSURF) for PVC of 
      PET images that aims to overcome these limitations by using two innovative 
      techniques: 1) the incorporation of anatomic information from a cortical gray 
      matter surface representation, extracted from magnetic resonance imaging (MRI) 
      and 2) the use of anatomically constrained filtering to attenuate noise. PVE 
      corrected images were generated with idSURF implemented into a non-interactive 
      processing pipeline. idSURF was validated using simulated and clinical PET data 
      sets and compared to a frequently used standard PVC method (Geometric Transfer 
      Matrix: GTM). The results on simulated data sets show that idSURF consistently 
      recovers accurate radiotracer concentrations within 1-5% of true values. Both 
      radiotracer concentrations and non-displaceable binding potential (BPnd) values 
      derived from clinical PET data sets with idSURF were highly correlated with those 
      obtained with the standard PVC method (R(2) = 0.99, error = 0%-3.2%). These 
      results suggest that idSURF is a valid and potentially clinically useful PVC 
      method for automatic processing of large numbers of PET data sets.
CI  - Copyright (c) 2014 Elsevier Inc. All rights reserved.
FAU - Funck, Thomas
AU  - Funck T
AD  - Montreal Neurological Institute, McGill University, Montreal, Canada; Jewish 
      General Hospital, Montreal Canada.
FAU - Paquette, Caroline
AU  - Paquette C
AD  - Jewish General Hospital, Montreal Canada; Department of Neurology and 
      Neurosurgery, Montreal, Canada.
FAU - Evans, Alan
AU  - Evans A
AD  - Montreal Neurological Institute, McGill University, Montreal, Canada.
FAU - Thiel, Alexander
AU  - Thiel A
AD  - Jewish General Hospital, Montreal Canada; Department of Neurology and 
      Neurosurgery, Montreal, Canada. Electronic address: alexander.thiel@mcgill.ca.
LA  - eng
GR  - MOP-115107/Canadian Institutes of Health Research/Canada
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20140829
PL  - United States
TA  - Neuroimage
JT  - NeuroImage
JID - 9215515
SB  - IM
MH  - Aged
MH  - Algorithms
MH  - Artifacts
MH  - Female
MH  - Gray Matter/*anatomy & histology/*diagnostic imaging
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - Models, Neurological
MH  - *Positron-Emission Tomography
OTO - NOTNLM
OT  - Cortical thickness
OT  - Magnetic resonance imagery
OT  - Partial-volume correction
OT  - Positron emission tomography
EDAT- 2014/09/02 06:00
MHDA- 2015/07/17 06:00
CRDT- 2014/09/02 06:00
PHST- 2014/04/22 00:00 [received]
PHST- 2014/08/09 00:00 [revised]
PHST- 2014/08/20 00:00 [accepted]
PHST- 2014/09/02 06:00 [entrez]
PHST- 2014/09/02 06:00 [pubmed]
PHST- 2015/07/17 06:00 [medline]
AID - S1053-8119(14)00711-3 [pii]
AID - 10.1016/j.neuroimage.2014.08.037 [doi]
PST - ppublish
SO  - Neuroimage. 2014 Nov 15;102 Pt 2:674-87. doi: 10.1016/j.neuroimage.2014.08.037. 
      Epub 2014 Aug 29.