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      Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation

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          Abstract

          Multicomponent driven equilibrium steady-state observation of T 1 and T 2 (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin content. mcDESPOT has a clinically feasible acquisition time and high signal-to-noise ratio (SNR) relative to other MWF techniques. However, disagreement exists in the literature between experimental studies that show MWF maps with plausible grey matter-white matter (GM-WM) contrast and theoretical work that questions the accuracy and precision of mcDESPOT. We demonstrate that mcDESPOT parameter estimation is inaccurate and imprecise if intercompartmental exchange is included in the microstructural model, but that significant bias results if exchange is neglected. The source of apparent MWF contrast is likely due to the complex convergence behaviour of the Stochastic Region Contraction (SRC) method commonly used to fit the mcDESPOT model. mcDESPOT-derived parameter estimates are hence not directly relatable to the underlying microstructural model and are only comparable to others using similar acquisition schemes and fitting constraints.

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          In vivo visualization of myelin water in brain by magnetic resonance.

          We exploit the intrinsic difference in magnetic resonance spin-spin relaxation time, T2, between water associated with myelin sheaths and water in other central nervous system tissue in order to measure myelin water content within any region of an image or to generate indirectly a myelin map of the brain. In normal volunteers, myelin water maps give the expected myelin distribution. In multiple sclerosis patients, lesions exhibit different myelin water contents providing insight into the demyelination process unavailable from conventional magnetic resonance images. In vivo myelin measurement has important applications in the clinical management of multiple sclerosis and other white matter diseases.
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            Gleaning multicomponent T1 and T2 information from steady-state imaging data.

            The driven-equilibrium single-pulse observation of T(1) (DESPOT1) and T(2) (DESPOT2) are rapid, accurate, and precise methods for voxelwise determination of the longitudinal and transverse relaxation times. A limitation of the methods, however, is the inherent assumption of single-component relaxation. In a variety of biological tissues, in particular human white matter (WM) and gray matter (GM), the relaxation has been shown to be more completely characterized by a summation of two or more relaxation components, or species, each believed to be associated with unique microanatomical domains or water pools. Unfortunately, characterization of these components on a voxelwise, whole-brain basis has traditionally been hindered by impractical acquisition times. In this work we extend the conventional DESPOT1 and DESPOT2 approaches to include multicomponent relaxation analysis. Following numerical analysis of the new technique, renamed multicomponent driven equilibrium single pulse observation of T(1)/T(2) (mcDESPOT), whole-brain multicomponent T(1) and T(2) quantification is demonstrated in vivo with clinically realistic times of between 16 and 30 min. Results obtained from four healthy individuals and two primary progressive multiple sclerosis (MS) patients demonstrate the future potential of the approach for identifying and assessing tissue changes associated with several neurodegenerative conditions, in particular those associated with WM. (c) 2008 Wiley-Liss, Inc.
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              Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state.

              A novel, fully 3D, high-resolution T(1) and T(2) relaxation time mapping method is presented. The method is based on steady-state imaging with T(1) and T(2) information derived from either spoiling or fully refocusing the transverse magnetization following each excitation pulse. T(1) is extracted from a pair of spoiled gradient recalled echo (SPGR) images acquired at optimized flip angles. This T(1) information is combined with two refocused steady-state free precession (SSFP) images to determine T(2). T(1) and T(2) accuracy was evaluated against inversion recovery (IR) and spin-echo (SE) results, respectively. Error within the T(1) and T(2) maps, determined from both phantom and in vivo measurements, is approximately 7% for T(1) between 300 and 2000 ms and 7% for T(2) between 30 and 150 ms. The efficiency of the method, defined as the signal-to-noise ratio (SNR) of the final map per voxel volume per square root scan time, was evaluated against alternative mapping methods. With an efficiency of three times that of multipoint IR and three times that of multiecho SE, our combined approach represents the most efficient of those examined. Acquisition time for a whole brain T(1) map (25 x 25 x 10 cm) is less than 8 min with 1 mm(3) isotropic voxels. An additional 7 min is required for an identically sized T(2) map and postprocessing time is less than 1 min on a 1 GHz PIII PC. The method therefore permits real-time clinical acquisition and display of whole brain T(1) and T(2) maps for the first time. Copyright 2003 Wiley-Liss, Inc.
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                Author and article information

                Journal
                9215515
                Neuroimage
                Neuroimage
                NeuroImage
                1053-8119
                1095-9572
                15 July 2019
                28 March 2019
                04 March 2020
                27 March 2020
                : 195
                : 78-88
                Affiliations
                [a ]Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, SE1 7EH, United Kingdom
                [b ]Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, SE1 7EH, United Kingdom
                [c ]Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, Camberwell, London, SE5 8AB, United Kingdom
                Author notes
                [* ]Corresponding author. Department of Perinatal Imaging and Health, 1st Floor South Wing, St. Thomas' Hospital, London, SE1 7EH, United Kingdom. daniel.d.west@ 123456kcl.ac.uk (D.J. West).
                Article
                EMS85964
                10.1016/j.neuroimage.2019.03.049
                7100802
                30930311
                cecd82c1-4c1b-40e7-8dd5-b6eae6412488

                This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/).

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                Categories
                Article

                Neurosciences
                mcdespot,myelin water fraction,stochastic region contraction,intercompartmental exchange,white matter-grey matter contrast,quantitative mri

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