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Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.

Ahlgren, André LU ; Wirestam, Ronnie LU ; Petersen, Esben Thade; Ståhlberg, Freddy LU and Knutsson, Linda LU (2014) In NMR in Biomedicine 27(9). p.1112-1122
Abstract
Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial... (More)
Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
NMR in Biomedicine
volume
27
issue
9
pages
1112 - 1122
publisher
John Wiley & Sons
external identifiers
  • pmid:25066601
  • wos:000340498700012
  • scopus:84905907929
ISSN
0952-3480
DOI
10.1002/nbm.3164
language
English
LU publication?
yes
id
c367bd59-7a72-4001-b1d5-1dbb90214eeb (old id 4581223)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/25066601?dopt=Abstract
date added to LUP
2014-08-09 16:36:59
date last changed
2017-10-22 03:30:02
@article{c367bd59-7a72-4001-b1d5-1dbb90214eeb,
  abstract     = {Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.},
  author       = {Ahlgren, André and Wirestam, Ronnie and Petersen, Esben Thade and Ståhlberg, Freddy and Knutsson, Linda},
  issn         = {0952-3480},
  language     = {eng},
  number       = {9},
  pages        = {1112--1122},
  publisher    = {John Wiley & Sons},
  series       = {NMR in Biomedicine},
  title        = {Partial volume correction of brain perfusion estimates using the inherent signal data of time-resolved arterial spin labeling.},
  url          = {http://dx.doi.org/10.1002/nbm.3164},
  volume       = {27},
  year         = {2014},
}