Quantitative Bayesian model-based analysis of amide proton transfer MRI
Amide Proton Transfer (APT) reports on contrast derived from the exchange of protons between amide groups and water. Commonly, APT contrast is quantified by asymmetry analysis, providing an ensemble contrast of both amide proton concentration and exchange rate. An alternative is to sample the off‐re...
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Published in | Magnetic resonance in medicine Vol. 70; no. 2; pp. 556 - 567 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Blackwell Publishing Ltd
01.08.2013
Wiley Subscription Services, Inc |
Subjects | |
Online Access | Get full text |
ISSN | 0740-3194 1522-2594 1522-2594 |
DOI | 10.1002/mrm.24474 |
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Summary: | Amide Proton Transfer (APT) reports on contrast derived from the exchange of protons between amide groups and water. Commonly, APT contrast is quantified by asymmetry analysis, providing an ensemble contrast of both amide proton concentration and exchange rate. An alternative is to sample the off‐resonant spectrum and fit an exchange model, permitting the APT effect to be quantified, correcting automatically for confounding effects of spillover, field inhomogeneity, and magnetization transfer. Additionally, it should permit amide concentration and exchange rate to be independently quantified. Here, a Bayesian method is applied to this problem allowing pertinent prior information to be specified. A three‐pool model was used incorporating water protons, amide protons, and magnetization transfer effect. The method is demonstrated in simulations, creatine phantoms with varying pH and in vivo (n = 7). The Bayesian model‐based approach was able to quantify the APT effect accurately (root‐mean‐square error < 2%) even when subject to confounding field variation and magnetization transfer effect, unlike traditional asymmetry analysis. The in vivo results gave approximate APT concentration (relative to water) and exchange rate values of 3 × 10−3 and 15 s−1. A degree of correlation was observed between these parameter making the latter difficult to quantify with absolute accuracy, suggesting that more optimal sampling strategies might be required. Magn Reson Med 70:556–567, 2013. © 2012 Wiley Periodicals, Inc. |
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Bibliography: | istex:93BBE3330C6DBC6DB3FC8941A39C38D1DBD5B090 ArticleID:MRM24474 Qualcomm Scholarship from Qualcomm Inc. Wellcome Trust and EPSRC - No. WT088877/Z/09/Z ark:/67375/WNG-6S6DNN70-T Cancer Research UK - No. C5255/A12678 ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0740-3194 1522-2594 1522-2594 |
DOI: | 10.1002/mrm.24474 |