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Kalra S, Müller HP, Ishaque A, Zinman L, Korngut L, Genge A, Beaulieu C, Frayne R, Graham SJ, Kassubek J. A prospective harmonized multicenter DTI study of cerebral white matter degeneration in ALS. Neurology 2020; 95:e943-e952. [PMID: 32646955 DOI: 10.1212/wnl.0000000000010235] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 02/17/2020] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE To evaluate progressive white matter (WM) degeneration in amyotrophic lateral sclerosis (ALS). METHODS Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicenter study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centers that included diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALS Functional Rating Scale-Revised [ALSFRS-R]) and upper motor neuron (UMN) function. Voxel-wise whole-brain and quantitative tract-wise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers who underwent the DTI protocol at each center. RESULTS Patients with ALS had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tract-wise analysis revealed reduced FA in the CST, corticopontine/corticorubral tract, and corticostriatal tract. CST FA correlated with UMN function, and frontal lobe FA correlated with the ALSFRS-R score. A progressive decline in CST FA correlated with a decline in the ALSFRS-R score and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe. CONCLUSIONS Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes and, to a lesser degree, in the corticopontine/corticorubral tracts and corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytic methods to address site-related variances, this study is an important milestone toward developing DTI biomarkers for cerebral degeneration in ALS. CLINICALTRIALSGOV IDENTIFIER NCT02405182.
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Affiliation(s)
- Sanjay Kalra
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada.
| | - Hans-Peter Müller
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Abdullah Ishaque
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Lorne Zinman
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Lawrence Korngut
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Angela Genge
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Christian Beaulieu
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Richard Frayne
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Simon J Graham
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
| | - Jan Kassubek
- From the Division of Neurology (S.K.), Department of Medicine, Neuroscience and Mental Health Institute (S.K., A.I.), and Department of Biomedical Engineering (C.B.), University of Alberta, Edmonton, Canada; Department of Neurology (H.-P.M., J.K.), University of Ulm, Germany; Sunnybrook Health Sciences Centre (L.Z., S.J.G.), University of Toronto, Ontario; Departments of Clinical Neurosciences (L.K., R.F.) and Radiology (R.F.), Hotchkiss Brain Institute, University of Calgary, Alberta; Montreal Neurological Institute and Hospital (A.G.), McGill University, Quebec; and Seaman Family MR Research Centre (R.F.), Foothills Medical Centre, Calgary, Alberta, Canada
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Boukadi M, Marcotte K, Bedetti C, Houde JC, Desautels A, Deslauriers-Gauthier S, Chapleau M, Boré A, Descoteaux M, Brambati SM. Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography. Front Neurosci 2019; 12:1055. [PMID: 30692910 PMCID: PMC6339903 DOI: 10.3389/fnins.2018.01055] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Accepted: 12/27/2018] [Indexed: 12/13/2022] Open
Abstract
High angular resolution diffusion imaging (HARDI)-based tractography has been increasingly used in longitudinal studies on white matter macro- and micro-structural changes in the language network during language acquisition and in language impairments. However, test-retest reliability measurements are essential to ascertain that the longitudinal variations observed are not related to data processing. The aims of this study were to determine the reproducibility of the reconstruction of major white matter fiber bundles of the language network using anatomically constrained probabilistic tractography with constrained spherical deconvolution based on HARDI data, as well as to assess the test-retest reliability of diffusion measures extracted along them. Eighteen right-handed participants were scanned twice, one week apart. The arcuate, inferior longitudinal, inferior fronto-occipital, and uncinate fasciculi were reconstructed in the left and right hemispheres and the following diffusion measures were extracted along each tract: fractional anisotropy, mean, axial, and radial diffusivity, number of fiber orientations, mean length of streamlines, and volume. All fiber bundles showed good morphological overlap between the two scanning timepoints and the test-retest reliability of all diffusion measures in most fiber bundles was good to excellent. We thus propose a fairly simple, but robust, HARDI-based tractography pipeline reliable for the longitudinal study of white matter language fiber bundles, which increases its potential applicability to research on the neurobiological mechanisms supporting language.
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Affiliation(s)
- Mariem Boukadi
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,Département de Psychologie, Université de Montréal, Montreal, QC, Canada
| | - Karine Marcotte
- Centre de Recherche du CIUSSS du Nord-de-l'île-de-Montréal, Hôpital du Sacré-Cœur de Montréal, Montreal, QC, Canada.,École d'Orthophonie et d'Audiologie, Faculté de Médecine, Université de Montréal, Montreal, QC, Canada
| | - Christophe Bedetti
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada
| | - Jean-Christophe Houde
- Sherbrooke Connectivity Imaging Lab, Département d'Informatique, Université de Sherbrooke, Montreal, QC, Canada
| | - Alex Desautels
- Centre de Recherche du CIUSSS du Nord-de-l'île-de-Montréal, Hôpital du Sacré-Cœur de Montréal, Montreal, QC, Canada.,CIUSSS du Nord-de-l'île-de-Montréal, Hôpital du Sacré-Cœur de Montréal, Montreal, QC, Canada
| | | | - Marianne Chapleau
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,Département de Psychologie, Université de Montréal, Montreal, QC, Canada
| | - Arnaud Boré
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab, Département d'Informatique, Université de Sherbrooke, Montreal, QC, Canada
| | - Simona M Brambati
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, QC, Canada.,Département de Psychologie, Université de Montréal, Montreal, QC, Canada
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Jiskoot LC, Panman JL, Meeter LH, Dopper EGP, Donker Kaat L, Franzen S, van der Ende EL, van Minkelen R, Rombouts SARB, Papma JM, van Swieten JC. Longitudinal multimodal MRI as prognostic and diagnostic biomarker in presymptomatic familial frontotemporal dementia. Brain 2019; 142:193-208. [PMID: 30508042 PMCID: PMC6308313 DOI: 10.1093/brain/awy288] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 09/26/2018] [Accepted: 10/02/2018] [Indexed: 12/12/2022] Open
Abstract
Developing and validating sensitive biomarkers for the presymptomatic stage of familial frontotemporal dementia is an important step in early diagnosis and for the design of future therapeutic trials. In the longitudinal Frontotemporal Dementia Risk Cohort, presymptomatic mutation carriers and non-carriers from families with familial frontotemporal dementia due to microtubule-associated protein tau (MAPT) and progranulin (GRN) mutations underwent a clinical assessment and multimodal MRI at baseline, 2-, and 4-year follow-up. Of the cohort of 73 participants, eight mutation carriers (three GRN, five MAPT) developed clinical features of frontotemporal dementia ('converters'). Longitudinal whole-brain measures of white matter integrity (fractional anisotropy) and grey matter volume in these converters (n = 8) were compared with healthy mutation carriers ('non-converters'; n = 35) and non-carriers (n = 30) from the same families. We also assessed the prognostic performance of decline within white matter and grey matter regions of interest by means of receiver operating characteristic analyses followed by stepwise logistic regression. Longitudinal whole-brain analyses demonstrated lower fractional anisotropy values in extensive white matter regions (genu corpus callosum, forceps minor, uncinate fasciculus, and superior longitudinal fasciculus) and smaller grey matter volumes (prefrontal, temporal, cingulate, and insular cortex) over time in converters, present from 2 years before symptom onset. White matter integrity loss of the right uncinate fasciculus and genu corpus callosum provided significant classifiers between converters, non-converters, and non-carriers. Converters' within-individual disease trajectories showed a relatively gradual onset of clinical features in MAPT, whereas GRN mutations had more rapid changes around symptom onset. MAPT converters showed more decline in the uncinate fasciculus than GRN converters, and more decline in the genu corpus callosum in GRN than MAPT converters. Our study confirms the presence of spreading predominant frontotemporal pathology towards symptom onset and highlights the value of multimodal MRI as a prognostic biomarker in familial frontotemporal dementia.
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Affiliation(s)
- Lize C Jiskoot
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jessica L Panman
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Lieke H Meeter
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Elise G P Dopper
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, VU Medical Center, Amsterdam, The Netherlands
| | - Laura Donker Kaat
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Sanne Franzen
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Rick van Minkelen
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Serge A R B Rombouts
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Janne M Papma
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - John C van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
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Zhou X, Sakaie KE, Debbins JP, Narayanan S, Fox RJ, Lowe MJ. Scan-rescan repeatability and cross-scanner comparability of DTI metrics in healthy subjects in the SPRINT-MS multicenter trial. Magn Reson Imaging 2018; 53:105-111. [PMID: 30048675 DOI: 10.1016/j.mri.2018.07.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 06/08/2018] [Accepted: 07/21/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE To assess intrascanner repeatability and cross-scanner comparability for diffusion tensor imaging (DTI) metrics in a multicenter clinical trial. METHODS DTI metrics (including longitudinal diffusivity [LD], fractional anisotropy [FA], mean diffusivity [MD], and transverse diffusivity [TD]) from pyramidal tracts for healthy controls were calculated from images acquired on twenty-seven 3T MR scanners (Siemens and GE) with 6 different scanner models and 7 different software versions as part of the NN102/SPRINT-MS clinical trial. Each volunteer underwent two scanning sessions on the same scanner. Signal-to-noise ratio (SNR) and signal-to-noise floor ratio (SNFR) were also assessed. RESULTS DTI metrics showed good scan-rescan repeatability. There were no significant differences between scans and rescans in LD, FA, MD, or TD values. Although the cross-scanner coefficient of variation (CV) values for all DTI metrics were <5.7%, significant differences were observed for LD (p < 3.3e-5) and FA (p < 0.0024) when GE scanners were compared with Siemens scanners. Significant differences were also observed for SNR when comparing GE scanners and Siemens Skyra scanners (p < 1.4e-7) and when comparing Siemens Skyra scanners and TIM Trio scanners (p < 1.0e-10). Analysis of background signal also demonstrated differences between GE and Siemens scanners in terms of signal statistics. The measured signal intensity from a background noise region of interest was significantly higher for GE scanners than for Siemens scanners (p < 1.2e-12). Significant differences were also observed for SNFR when comparing GE scanners and Siemens Skyra scanners (p < 2.5e-11), GE scanners and Siemens Trio scanners (p < 7.5e-11), and Siemens Skyra scanners and TIM Trio scanners (p < 2.5e-9). CONCLUSIONS The good repeatability of the DTI metrics among the 27 scanners used in this study confirms the feasibility of combining DTI data from multiple centers using high angular resolution sequences. Our observations support the feasibility of longitudinal multicenter clinical trials using DTI outcome measures. The noise floor level and SNFR are important parameters that must be assessed when comparing studies that used different scanner models.
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Affiliation(s)
- Xiaopeng Zhou
- School of Health Sciences, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, USA
| | - Ken E Sakaie
- Imaging Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA
| | - Josef P Debbins
- Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, 350 W Thomas Rd, Phoenix, AZ 85013, USA
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, 3801 University St., Montreal, QC H3A2B4, Canada; NeuroRx Research, 3575 Avenue du Parc, Suite 5322, Montreal, QC, H2X 3P9, Canada
| | - Robert J Fox
- Neurological Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA
| | - Mark J Lowe
- Imaging Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195, USA.
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Taylor PA, Alhamud A, van der Kouwe A, Saleh MG, Laughton B, Meintjes E. Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction. Hum Brain Mapp 2016; 37:4405-4424. [PMID: 27436169 DOI: 10.1002/hbm.23318] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 06/16/2016] [Accepted: 07/05/2016] [Indexed: 11/07/2022] Open
Abstract
Diffusion tensor imaging (DTI) is susceptible to several artifacts due to eddy currents, echo planar imaging (EPI) distortion and subject motion. While several techniques correct for individual distortion effects, no optimal combination of DTI acquisition and processing has been determined. Here, the effects of several motion correction techniques are investigated while also correcting for EPI distortion: prospective correction, using navigation; retrospective correction, using two different popular packages (FSL and TORTOISE); and the combination of both methods. Data from a pediatric group that exhibited incidental motion in varying degrees are analyzed. Comparisons are carried while implementing eddy current and EPI distortion correction. DTI parameter distributions, white matter (WM) maps and probabilistic tractography are examined. The importance of prospective correction during data acquisition is demonstrated. In contrast to some previous studies, results also show that the inclusion of retrospective processing also improved ellipsoid fits and both the sensitivity and specificity of group tractographic results, even for navigated data. Matches with anatomical WM maps are highest throughout the brain for data that have been both navigated and processed using TORTOISE. The inclusion of both prospective and retrospective motion correction with EPI distortion correction is important for DTI analysis, particularly when studying subject populations that are prone to motion. Hum Brain Mapp 37:4405-4424, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Paul A Taylor
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa.,African Institute for Mathematical Sciences, Muizenberg, Western Cape, South Africa.,Scientific and Statistical Computing Core, National Institutes of Health, Bethesda, Maryland
| | - A Alhamud
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
| | - Andre van der Kouwe
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Muhammad G Saleh
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
| | - Barbara Laughton
- Department of Paediatrics and Child Health, Stellenbosch University, Children's Infection Diseases Clinical Research Unit, South Africa
| | - Ernesta Meintjes
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
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