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Modeling the residue function in DSC‐MRI simulations: Analytical approximation to in vivo data

Purpose An exponential residue function is commonly used in numerical simulations to assess the accuracy of perfusion quantification using dynamic susceptibility contrast (DSC) MRI. Although this might be a reasonable assumption for normal tissue, microvascular hemodynamics are likely to be signific... Full description

Journal Title: Magnetic Resonance in Medicine November 2014, Vol.72(5), pp.1486-1491
Main Author: Mehndiratta, Amit
Other Authors: Calamante, Fernando , Macintosh, Bradley J. , Crane, David E. , Payne, Stephen J. , Chappell, Michael A.
Format: Electronic Article Electronic Article
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ID: ISSN: 0740-3194 ; E-ISSN: 1522-2594 ; DOI: 10.1002/mrm.25056
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recordid: wj10.1002/mrm.25056
title: Modeling the residue function in DSC‐MRI simulations: Analytical approximation to in vivo data
format: Article
creator:
  • Mehndiratta, Amit
  • Calamante, Fernando
  • Macintosh, Bradley J.
  • Crane, David E.
  • Payne, Stephen J.
  • Chappell, Michael A.
subjects:
  • Residue Function
  • Perfusion Digital Phantom
  • Dsc Simulation
  • Deconvolution
ispartof: Magnetic Resonance in Medicine, November 2014, Vol.72(5), pp.1486-1491
description: Purpose An exponential residue function is commonly used in numerical simulations to assess the accuracy of perfusion quantification using dynamic susceptibility contrast (DSC) MRI. Although this might be a reasonable assumption for normal tissue, microvascular hemodynamics are likely to be significantly altered in pathology. Thus the exponential function may no longer be appropriate and the estimated accuracy of DSC-MRI quantification might be inappropriate. The purpose of this study was to characterize in vivo residue function variations in normal and infarcted tissue in a chronic atherosclerotic disease cohort, and to find the most appropriate model for use in DSC simulations. Methods Residue functions were measured in vivo in patients with atherosclerotic disease using a nonparametric Control Point Interpolation method, which has been shown to provide a robust characterization of the shape of the residue function. The observed residue functions were approximated with five commonly used analytical expressions: exponential, bi-exponential, Lorentzian, and Fermi functions, and a previously proposed Vascular Model. Results The lowest error was found with the bi-exponential function approximations to the in vivo residue functions from both normal and infarcted tissue. Conclusion A bi-exponential model should therefore be used in future numerical simulations of DSC-MRI instead of the exponential function. Magn Reson Med 72:1486-1491, 2014. copyright 2013 Wiley Periodicals, Inc.
language:
source:
identifier: ISSN: 0740-3194 ; E-ISSN: 1522-2594 ; DOI: 10.1002/mrm.25056
fulltext: fulltext
issn:
  • 0740-3194
  • 07403194
  • 1522-2594
  • 15222594
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titleModeling the residue function in DSC‐MRI simulations: Analytical approximation to in vivo data
creatorMehndiratta, Amit ; Calamante, Fernando ; Macintosh, Bradley J. ; Crane, David E. ; Payne, Stephen J. ; Chappell, Michael A.
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subjectResidue Function ; Perfusion Digital Phantom ; Dsc Simulation ; Deconvolution
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descriptionPurpose An exponential residue function is commonly used in numerical simulations to assess the accuracy of perfusion quantification using dynamic susceptibility contrast (DSC) MRI. Although this might be a reasonable assumption for normal tissue, microvascular hemodynamics are likely to be significantly altered in pathology. Thus the exponential function may no longer be appropriate and the estimated accuracy of DSC-MRI quantification might be inappropriate. The purpose of this study was to characterize in vivo residue function variations in normal and infarcted tissue in a chronic atherosclerotic disease cohort, and to find the most appropriate model for use in DSC simulations. Methods Residue functions were measured in vivo in patients with atherosclerotic disease using a nonparametric Control Point Interpolation method, which has been shown to provide a robust characterization of the shape of the residue function. The observed residue functions were approximated with five commonly used analytical expressions: exponential, bi-exponential, Lorentzian, and Fermi functions, and a previously proposed Vascular Model. Results The lowest error was found with the bi-exponential function approximations to the in vivo residue functions from both normal and infarcted tissue. Conclusion A bi-exponential model should therefore be used in future numerical simulations of DSC-MRI instead of the exponential function. Magn Reson Med 72:1486-1491, 2014. copyright 2013 Wiley Periodicals, Inc.
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