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Detection of Perfusion Deficits in Multiphase Computed Tomography Angiography—A Stroke Imaging Technique Based on Iodine Mapping on Spectral Computed Tomography: Initial Findings

Fransson, Veronica LU orcid ; Mellander, Helena LU orcid ; Wasselius, Johan LU and Ydström, Kristina LU (2021) In Journal of Computer Assisted Tomography 45(4). p.618-624
Abstract
Objective: The purpose of this study was to explore a novel method for
brain tissue differentiation using quantitative analysis of multiphase computed
tomography (CT) angiography (MP-CTA) on spectral CT, to assess
whether it can distinguish underperfused fromnormal tissue, using CT perfusion
(CTP) as reference.
Methods: Noncontrast CT and MP-CTA images from 10 patients were
analyzed in vascular regions through measurements of Hounsfield unit (HU)
at 120 kV, HU at 40 keV, and iodine density. Regions were categorized
as normal or ischemic according to CTP. Hounsfield unit and iodine
density were compared regarding ability to separate normal and ischemic
tissue, the difference in maximum time derivative... (More)
Objective: The purpose of this study was to explore a novel method for
brain tissue differentiation using quantitative analysis of multiphase computed
tomography (CT) angiography (MP-CTA) on spectral CT, to assess
whether it can distinguish underperfused fromnormal tissue, using CT perfusion
(CTP) as reference.
Methods: Noncontrast CT and MP-CTA images from 10 patients were
analyzed in vascular regions through measurements of Hounsfield unit (HU)
at 120 kV, HU at 40 keV, and iodine density. Regions were categorized
as normal or ischemic according to CTP. Hounsfield unit and iodine
density were compared regarding ability to separate normal and ischemic
tissue, the difference in maximum time derivative of the right over
left hemisphere ratio.
Results: Iodine density had the highest maximum time derivatives and
generated the largest mean separation between normal and ischemic tissue.
Conclusions: The method can be used to categorize tissue as normal or
underperfused. Using iodine quantification seems to give a more distinct
differentiation of perfusion defects compared with conventional HU. (Less)
Please use this url to cite or link to this publication:
author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Computer Assisted Tomography
volume
45
issue
4
pages
618 - 624
publisher
Lippincott Williams & Wilkins
external identifiers
  • scopus:85111289595
  • pmid:34176878
ISSN
1532-3145
DOI
10.1097/RCT.0000000000001173
project
Improvements in brain imaging using spectral computed tomography - Development and evaluation of novel techniques
language
English
LU publication?
yes
id
bda21fcc-3f63-444e-9ff4-b49d72e1919c
date added to LUP
2021-07-22 11:08:37
date last changed
2025-05-01 03:22:34
@article{bda21fcc-3f63-444e-9ff4-b49d72e1919c,
  abstract     = {{Objective: The purpose of this study was to explore a novel method for<br/>brain tissue differentiation using quantitative analysis of multiphase computed<br/>tomography (CT) angiography (MP-CTA) on spectral CT, to assess<br/>whether it can distinguish underperfused fromnormal tissue, using CT perfusion<br/>(CTP) as reference.<br/>Methods: Noncontrast CT and MP-CTA images from 10 patients were<br/>analyzed in vascular regions through measurements of Hounsfield unit (HU)<br/>at 120 kV, HU at 40 keV, and iodine density. Regions were categorized<br/>as normal or ischemic according to CTP. Hounsfield unit and iodine<br/>density were compared regarding ability to separate normal and ischemic<br/>tissue, the difference in maximum time derivative of the right over<br/>left hemisphere ratio.<br/>Results: Iodine density had the highest maximum time derivatives and<br/>generated the largest mean separation between normal and ischemic tissue.<br/>Conclusions: The method can be used to categorize tissue as normal or<br/>underperfused. Using iodine quantification seems to give a more distinct<br/>differentiation of perfusion defects compared with conventional HU.}},
  author       = {{Fransson, Veronica and Mellander, Helena and Wasselius, Johan and Ydström, Kristina}},
  issn         = {{1532-3145}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{618--624}},
  publisher    = {{Lippincott Williams & Wilkins}},
  series       = {{Journal of Computer Assisted Tomography}},
  title        = {{Detection of Perfusion Deficits in Multiphase Computed Tomography Angiography—A Stroke Imaging Technique Based on Iodine Mapping on Spectral Computed Tomography: Initial Findings}},
  url          = {{http://dx.doi.org/10.1097/RCT.0000000000001173}},
  doi          = {{10.1097/RCT.0000000000001173}},
  volume       = {{45}},
  year         = {{2021}},
}