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Abstract #2998

A Linear Model approach for treating partial volumes in quantitative 1H MRS of cortical grey matter – application to an osteoarthritis pain study

Franklyn Howe1, Amber Law1,2, and Nidhi Sofat3,4
1Molecular and Clinical Sciences Research Institute, St George's, University of London, London, United Kingdom, 2King's College London, London, United Kingdom, 3Infection & Immunity Research Institute, St George's, University of London, London, United Kingdom, 4Dept Rheumatology, St George's Hospital Foundation Trust, London, United Kingdom

Synopsis

Keywords: Data Processing, Spectroscopy

Motivation: The accuracy of absolute quantitation of metabolites by 1H MRS in grey-matter is compromised in the presence of partial volumes of CSF

Goal(s): To develop a linear model of metabolite concentration estimates as a function of partial volumes

Approach: The effects of varying tissue fractions and relaxation times on metabolite concentrations were modelled to investigate how they affected the variability in metabolite concentration estimates

Results: A general linear model with parameters relating to tissue partial volume as covariates enables statistical comparisons of absolute metabolite levels between patient sub-groups without a priori knowledge of tissue relaxation times.

Impact: A General Linear Model statistical approach enables robust comparison of cortical grey matter metabolite concentrations between patient groups, and minimises the propagation of errors that occurs when the tissue partial volume properties are inaccurately estimated.

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Keywords