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Uncertainty estimation in dynamic contrast-enhanced MRI

Garpebring, Anders ; Brynolfsson, Patrik ; Yu, Jun ; Wirestam, Ronnie LU ; Johansson, Adam ; Asklund, Thomas and Karlsson, Mikael (2013) In Magnetic Resonance in Medicine 69(4). p.992-1002
Abstract
Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated... (More)
Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty. Magn Reson Med 69:9921002, 2013. (c) 2012 Wiley Periodicals, Inc. (Less)
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author
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
uncertainty estimation, dynamic contrast-enhanced-MRI, precision, analysis, accuracy
in
Magnetic Resonance in Medicine
volume
69
issue
4
pages
992 - 1002
publisher
John Wiley and Sons Inc.
external identifiers
  • wos:000316629300013
  • scopus:84875371501
  • pmid:22714717
ISSN
1522-2594
DOI
10.1002/mrm.24328
language
English
LU publication?
yes
id
c4341711-a285-41a5-af27-de3678975533 (old id 3739407)
date added to LUP
2016-04-01 10:14:45
date last changed
2020-10-04 03:28:20
@article{c4341711-a285-41a5-af27-de3678975533,
  abstract     = {Using dynamic contrast-enhanced MRI (DCE-MRI), it is possible to estimate pharmacokinetic (PK) parameters that convey information about physiological properties, e.g., in tumors. In DCE-MRI, errors propagate in a nontrivial way to the PK parameters. We propose a method based on multivariate linear error propagation to calculate uncertainty maps for the PK parameters. Uncertainties in the PK parameters were investigated for the modified Kety model. The method was evaluated with Monte Carlo simulations and exemplified with in vivo brain tumor data. PK parameter uncertainties due to noise in dynamic data were accurately estimated. Noise with standard deviation up to 15% in the baseline signal and the baseline T1 map gave estimated uncertainties in good agreement with the Monte Carlo simulations. Good agreement was also found for up to 15% errors in the arterial input function amplitude. The method was less accurate for errors in the bolus arrival time with disagreements of 23%, 32%, and 29% for Ktrans, ve, and vp, respectively, when the standard deviation of the bolus arrival time error was 5.3 s. In conclusion, the proposed method provides efficient means for calculation of uncertainty maps, and it was applicable to a wide range of sources of uncertainty. Magn Reson Med 69:9921002, 2013. (c) 2012 Wiley Periodicals, Inc.},
  author       = {Garpebring, Anders and Brynolfsson, Patrik and Yu, Jun and Wirestam, Ronnie and Johansson, Adam and Asklund, Thomas and Karlsson, Mikael},
  issn         = {1522-2594},
  language     = {eng},
  number       = {4},
  pages        = {992--1002},
  publisher    = {John Wiley and Sons Inc.},
  series       = {Magnetic Resonance in Medicine},
  title        = {Uncertainty estimation in dynamic contrast-enhanced MRI},
  url          = {http://dx.doi.org/10.1002/mrm.24328},
  doi          = {10.1002/mrm.24328},
  volume       = {69},
  year         = {2013},
}