Uncertainty estimation in dynamic contrast-enhanced MRI
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3739407
- author
- Garpebring, Anders ; Brynolfsson, Patrik ; Yu, Jun ; Wirestam, Ronnie LU ; Johansson, Adam ; Asklund, Thomas and Karlsson, Mikael
- organization
- publishing date
- 2013
- 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 & 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
- 2022-01-25 21:16:44
@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}}, keywords = {{uncertainty estimation; dynamic contrast-enhanced-MRI; precision; analysis; accuracy}}, language = {{eng}}, number = {{4}}, pages = {{992--1002}}, publisher = {{John Wiley & 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}}, }