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Arterial Input Functions and Tissue Response Curves in Dynamic Glucose-Enhanced (DGE) Imaging: Comparison Between glucoCEST and Blood Glucose Sampling in Humans

Knutsson, Linda LU ; Seidemo, Anina LU ; Rydhög, Anna LU ; Markenroth Bloch, Karin LU orcid ; Kalyani, Rita R ; Andersen, Mads ; Maly Sundgren, Pia LU orcid ; Wirestam, Ronnie LU orcid ; Helms, Gunther LU orcid and van Zijl, Peter C M , et al. (2018) In Tomography : a journal for imaging research 4(4). p.164-171
Abstract
Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative... (More)
Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative responses with a peak intensity that was of the order of 10 times smaller than the AIF peak and a shape that was susceptible to both noise and partial volume effects with CSF, attributed to the low contrast-to-noise ratio. The CSF response curves showed a rather large and steady increase of the glucose uptake during the scan, due to the rapid uptake of D-glucose in CSF. Importantly, and contrary to gadolinium studies, the curves differed substantially among volunteers, which was interpreted to be caused by variations in insulin response. In conclusion, while AIFs and tissue response curves can be measured in DGE experiments,
partial volume effects, low concentration of D-glucose in tissue, and osmolality effects between tissue and blood may prohibit quantification of normal tissue perfusion parameters. However, separation of tumor responses from normal tissue responses would most likely be feasible. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Tomography : a journal for imaging research
volume
4
issue
4
pages
164 - 171
publisher
Grapho Publications LLC
external identifiers
  • pmid:30588502
ISSN
2379-1381
DOI
10.18383/j.tom.2018.00025
project
Natural sugar as an MRI contrast agent for cancer diagnosis
language
English
LU publication?
yes
id
37b4be8c-a33f-46bc-a83c-685bc392553f
date added to LUP
2019-01-11 16:30:19
date last changed
2021-09-02 04:00:59
@article{37b4be8c-a33f-46bc-a83c-685bc392553f,
  abstract     = {Dynamic glucose-enhanced (DGE) imaging uses chemical exchange saturation transfer magnetic resonance imaging to retrieve information about the microcirculation using infusion of a natural sugar (D-glucose). However, this new approach is not yet well understood with respect to the dynamic tissue response. DGE time curves for arteries, normal brain tissue, and cerebrospinal fluid (CSF) were analyzed in healthy volunteers and compared with the time dependence of sampled venous plasma blood glucose levels. The arterial response curves (arterial input function [AIF]) compared reasonably well in shape with the time curves of the sampled glucose levels but could also differ substantially. The brain tissue response curves showed mainly negative responses with a peak intensity that was of the order of 10 times smaller than the AIF peak and a shape that was susceptible to both noise and partial volume effects with CSF, attributed to the low contrast-to-noise ratio. The CSF response curves showed a rather large and steady increase of the glucose uptake during the scan, due to the rapid uptake of D-glucose in CSF. Importantly, and contrary to gadolinium studies, the curves differed substantially among volunteers, which was interpreted to be caused by variations in insulin response. In conclusion, while AIFs and tissue response curves can be measured in DGE experiments,<br/>partial volume effects, low concentration of D-glucose in tissue, and osmolality effects between tissue and blood may prohibit quantification of normal tissue perfusion parameters. However, separation of tumor responses from normal tissue responses would most likely be feasible.},
  author       = {Knutsson, Linda and Seidemo, Anina and Rydhög, Anna and Markenroth Bloch, Karin and Kalyani, Rita R and Andersen, Mads and Maly Sundgren, Pia and Wirestam, Ronnie and Helms, Gunther and van Zijl, Peter C M and Xu, Xiang},
  issn         = {2379-1381},
  language     = {eng},
  month        = {12},
  number       = {4},
  pages        = {164--171},
  publisher    = {Grapho Publications LLC},
  series       = {Tomography : a journal for imaging research},
  title        = {Arterial Input Functions and Tissue Response Curves in Dynamic Glucose-Enhanced (DGE) Imaging: Comparison Between glucoCEST and Blood Glucose Sampling in Humans},
  url          = {http://dx.doi.org/10.18383/j.tom.2018.00025},
  doi          = {10.18383/j.tom.2018.00025},
  volume       = {4},
  year         = {2018},
}