Imperial College London
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DrSoniaNielles-Vallespin

Faculty of Medicine, National Heart & Lung Institute

Senior Lecturer in Physics of CMR
 
 
 
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s.nielles-vallespin

 
 
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Guy Scadding BuildingRoyal Brompton Campus

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Summary

 

Publications

Citation

BibTex format

@article{Xue:2019:10.1002/mrm.27954,
author = {Xue, H and Brown, LAE and Nielles-Vallespin, S and Plein, S and Kellman, P},
doi = {10.1002/mrm.27954},
journal = {Magnetic Resonance in Medicine},
pages = {712--730},
title = {Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation},
url = {http://dx.doi.org/10.1002/mrm.27954},
volume = {83},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - PurposeQuantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization.MethodsProposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixelwise mapping. A distributed kinetics model, bloodtissue exchange model, is implemented, computing pixelwise maps of myocardial blood flow (mL/min/g), permeabilitysurfacearea product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g).ResultsThirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeabilitysurfacearea product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50).ConclusionsAn inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial eva
AU  - Xue,H
AU  - Brown,LAE
AU  - Nielles-Vallespin,S
AU  - Plein,S
AU  - Kellman,P
DO  - 10.1002/mrm.27954
EP  - 730
PY  - 2019///
SN  - 0740-3194
SP  - 712
TI  - Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation
T2  - Magnetic Resonance in Medicine
UR  - http://dx.doi.org/10.1002/mrm.27954
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000483282300001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://onlinelibrary.wiley.com/doi/full/10.1002/mrm.27954
VL  - 83
ER  -
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