Impact of Temporal Resolution and Methods for Correction on Cardiac Magnetic Resonance Perfusion Quantification.
Monte Carlo simulations
myocardial blood flow
myocardial perfusion quantification
perfusion phantom
temporal resolution
Journal
Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
revised:
14
03
2022
received:
26
01
2022
accepted:
15
03
2022
pubmed:
27
3
2022
medline:
15
11
2022
entrez:
26
3
2022
Statut:
ppublish
Résumé
Acquisition of magnetic resonance first-pass perfusion images is synchronized to the patient's heart rate (HR) and governs the temporal resolution. This is inherently linked to the process of myocardial blood flow (MBF) quantification and impacts MBF accuracy but to an unclear extent. To assess the impact of temporal resolution on quantitative perfusion and compare approaches for accounting for its variability. Prospective phantom and retrospective clinical study. Simulations, a cardiac perfusion phantom, and 30 patients with (16, 53%) or without (14, 47%) coronary artery disease. 3.0 T/2D saturation recovery spoiled gradient echo sequence. Dynamic perfusion data were simulated for a range of reference MBF (1 mL/g/min-5 mL/g/min) and HR (30 bpm-150 bpm). Perfusion imaging was performed in patients and a phantom for different temporal resolutions. MBF and myocardial perfusion reserve (MPR) were quantified without correction for temporal resolution or following correction by either MBF scaling based on the sampling interval or data interpolation prior to quantification. Simulated data were quantified using Fermi deconvolution, truncated singular value decomposition, and one-compartment modeling, whereas phantom and clinical data were quantified using Fermi deconvolution alone. Shapiro-Wilk tests for normality, percentage error (PE) for measuring MBF accuracy in simulations, and one-way repeated measures analysis of variance with Bonferroni correction to compare clinical MBF and MPR. Statistical significance set at P < 0.05. For Fermi deconvolution and an example simulated 1 mL/g/min, the MBF PE without correction for temporal resolution was between 55.4% and -62.7% across 30-150 bpm. PE was between -22.2% and -6.8% following MBF scaling and between -14.2% and -14.2% following data interpolation across the same HR. An interpolated HR of 240 bpm reduced PE to ≤10%. Clinical rest and stress MBF and MPR were significantly different between analyses. Accurate perfusion quantification needs to account for the variability of temporal resolution, with data interpolation prior to quantification reducing MBF variability across different resolutions. 3 TECHNICAL EFFICACY STAGE: 1.
Sections du résumé
BACKGROUND
Acquisition of magnetic resonance first-pass perfusion images is synchronized to the patient's heart rate (HR) and governs the temporal resolution. This is inherently linked to the process of myocardial blood flow (MBF) quantification and impacts MBF accuracy but to an unclear extent.
PURPOSE
To assess the impact of temporal resolution on quantitative perfusion and compare approaches for accounting for its variability.
STUDY TYPE
Prospective phantom and retrospective clinical study.
POPULATION AND PHANTOM
Simulations, a cardiac perfusion phantom, and 30 patients with (16, 53%) or without (14, 47%) coronary artery disease.
FIELD STRENGTH/SEQUENCE
3.0 T/2D saturation recovery spoiled gradient echo sequence.
ASSESSMENT
Dynamic perfusion data were simulated for a range of reference MBF (1 mL/g/min-5 mL/g/min) and HR (30 bpm-150 bpm). Perfusion imaging was performed in patients and a phantom for different temporal resolutions. MBF and myocardial perfusion reserve (MPR) were quantified without correction for temporal resolution or following correction by either MBF scaling based on the sampling interval or data interpolation prior to quantification. Simulated data were quantified using Fermi deconvolution, truncated singular value decomposition, and one-compartment modeling, whereas phantom and clinical data were quantified using Fermi deconvolution alone.
STATISTICAL TESTS
Shapiro-Wilk tests for normality, percentage error (PE) for measuring MBF accuracy in simulations, and one-way repeated measures analysis of variance with Bonferroni correction to compare clinical MBF and MPR. Statistical significance set at P < 0.05.
RESULTS
For Fermi deconvolution and an example simulated 1 mL/g/min, the MBF PE without correction for temporal resolution was between 55.4% and -62.7% across 30-150 bpm. PE was between -22.2% and -6.8% following MBF scaling and between -14.2% and -14.2% following data interpolation across the same HR. An interpolated HR of 240 bpm reduced PE to ≤10%. Clinical rest and stress MBF and MPR were significantly different between analyses.
DATA CONCLUSION
Accurate perfusion quantification needs to account for the variability of temporal resolution, with data interpolation prior to quantification reducing MBF variability across different resolutions.
LEVEL OF EVIDENCE
3 TECHNICAL EFFICACY STAGE: 1.
Identifiants
pubmed: 35338754
doi: 10.1002/jmri.28180
pmc: PMC9790572
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1707-1719Subventions
Organisme : British Heart Foundation
ID : TG/18/2/33768
Pays : United Kingdom
Organisme : Wellcome Trust
ID : WT 203148/Z/16/Z
Pays : United Kingdom
Organisme : Department of Health
ID : CL-2019-17-001
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P01979X/1
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
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