Neuroimage Analysis Center (NAC)

Microstructure Imaging core

The Microstructure Imaging Core is focussing on developing novel in-vivo magnetic resonance imaging (MRI) technologies that will increase the microstructural specificity related to neurological pathologies. The core title, “Microstructure Imaging,” relates to the fact that we will work with MRI quantities that are sensitive to micrometer scale anatomy, a much smaller scale than the typical measurement of voxel size. We will focus on measurements from diffusion MRI (dMRI) that are sensitive to the micrometer displacement of water molecules, reflecting the tissue geometry, and from MR spectroscopy (MRS), which quantifies the chemical nuclei within the tissue microstructure, allowing detection of metabolic changes. 

  • Carl-Fredrik Westin, PhD

    Professor of Radiology, Harvard Medical School

    Director, Laboratory for Mathematics in Imaging (LMI)

    Center Director, Neuroimaging Analysis Center (NAC)

    Carl-Fredrik (C-F) Westin, is the founding director of the Laboratory of Mathematics in Imaging (LMI, http://lmi.med.harvard.edu), Distinguished Robert Greenes Chair, and Professor of Radiology at...

    Department of Radiology
    Brigham and Women's Hospital, Harvard Medical School
    1249 Boylston Street, Boston, MA 02215
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  • Dr. David Banks

    Associate Professor, Department of Electrical Engineering & Computer Science, University of Tennessee

    LMI: He served as a Visiting Professor of Radiology, Harvard Medical School, 2005-2006.
     
    Areas of Interest
    • Display of biomedical and scientific data
    • Interactive simulation
    • 3D rendering
    Edu...
    Min H. Kao Building, Suite 401
    1520 Middle Drive
    Knoxville, TN 37996-2250
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  • Chantal Tax

    Chantal completed her Biomedical Engineering bachelor degree at Eindhoven University of Technology. During her master Medical Engineering at the same university she focussed on biomedical modeling and...

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  • Dr. Demian Wassermann

    Research Associate (chargé de recherche) at the Athena Team, INRIA Sophia Antipolis-Méditerranée

    LMI: 2010 - 2013

    My work mainly focuses on developing mathematical models of brain anatomy, through Diffusion MRI and their clinical applications. I also have interests in image registration and...

    2004 route des Lucioles, 06902, Sophia-Antipolis CEDEX, France
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  • Dr. Arne Hans

    Post-doctoral Research Fellow, Computational Radiology Laboratory (CRL), Department of Radiology at Children's Hospital, Boston

    LMI: 2004 - 2005

    Arne received his MSc in Medical Computer Science from the University of Heidelberg, Germany, in 2002, and his PhD in Medical Sciences from the University of Duisburg-Essen, Germany...

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  • Dr. Carlos A. Castano Moraga

    Business Analytics, Fujitsu Technology Solutions, Spain

    Previous: Head of R&D Gnarum Tecnologia y Energia, Spain

    LMI: 2004

    He was a visiting research fellow  during 4 months at LMI (June-September 2014).

  • O’Donnell LJ, Pasternak O. Does diffusion MRI tell us anything about the white matter? An overview of methods and pitfalls.. Schizophr Res. 2015;161(1):133–41. doi:10.1016/j.schres.2014.09.007

    One key pitfall in diffusion magnetic resonance imaging (dMRI) clinical neuroimaging research is the challenge of understanding and interpreting the results of a complex analysis pipeline. The sophisticated algorithms employed by the analysis software, combined with the relatively non-specific nature of many diffusion measurements, lead to challenges in interpretation of the results. This paper is aimed at an intended audience of clinical researchers who are learning about dMRI or trying to interpret dMRI results, and who may be wondering "Does dMRI tell us anything about the white matter?" We present a critical review of dMRI methods and measures used in clinical neuroimaging research, focusing on the most commonly used analysis methods and the most commonly reported measures. We describe important pitfalls in every section, and provide extensive references for the reader interested in more detail.

  • Wassermann D, Makris N, Rathi Y, Shenton M, Kikinis R, Kubicki M, Westin C-F. The White Matter Query Language: A Novel Approach for Describing Human White Matter Anatomy. Brain Struct Funct. 2016;221(9):4705–4721. doi:10.1007/s00429-015-1179-4

    We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tracts from diffusion MRI volumes. Further, our method simplifies the quantification and statistical analysis of white matter tracts on large diffusion MRI databases. This work reflects the careful syntactical definition of major white matter fiber tracts in the human brain based on a neuroanatomist’s expert knowledge. The framework is based on a novel query language with a near-to-English textual syntax. This query language makes it possible to construct a dictionary of anatomical definitions that describe white matter tracts. The definitions include adjacent gray and white matter regions, and rules for spatial relations. This novel method makes it possible to automatically label white matter anatomy across subjects. After describing this method, we provide an example of its implementation where we encode anatomical knowledge in human white matter for ten association and 15 projection tracts per hemisphere, along with seven commissural tracts. Importantly, this novel method is comparable in accuracy to manual labeling. Finally, we present results applying this method to create a white matter atlas from 77 healthy subjects, and we use this atlas in a small proof-of-concept study to detect changes in association tracts that characterize schizophrenia.

  • Hong Y, O’Donnell LJ, Savadjiev P, Zhang F, Wassermann D, Pasternak O, Johnson H, Paulsen J, Vonsattel J-P, Makris N, et al. Genetic load determines atrophy in hand cortico-striatal pathways in presymptomatic Huntington’s disease. Hum Brain Mapp. 2018;39(10):3871–3883. doi:10.1002/hbm.24217

    Huntington’s disease (HD) is an inherited neurodegenerative disorder that causes progressive breakdown of striatal neurons. Standard white matter integrity measures like fractional anisotropy and mean diffusivity derived from diffusion tensor imaging were analyzed in prodromal-HD subjects; however, they studied either a whole brain or specific subcortical white matter structures with connections to cortical motor areas. In this work, we propose a novel analysis of a longitudinal cohort of 243 prodromal-HD individuals and 88 healthy controls who underwent two or more diffusion MRI scans as part of the PREDICT-HD study. We separately trace specific white matter fiber tracts connecting the striatum (caudate and putamen) with four cortical regions corresponding to the hand, face, trunk, and leg motor areas. A multi-tensor tractography algorithm with an isotropic volume fraction compartment allows estimating diffusion of fast-moving extra-cellular water in regions containing crossing fibers and provides quantification of a microstructural property related to tissue atrophy. The tissue atrophy rate is separately analyzed in eight cortico-striatal pathways as a function of CAG-repeats (genetic load) by statistically regressing out age effect from our cohort. The results demonstrate a statistically significant increase in isotropic volume fraction (atrophy) bilaterally in hand fiber connections to the putamen with increasing CAG-repeats, which connects the genetic abnormality (CAG-repeats) to an imaging-based microstructural marker of tissue integrity in specific white matter pathways in HD. Isotropic volume fraction measures in eight cortico-striatal pathways are also correlated significantly with total motor scores and diagnostic confidence levels, providing evidence of their relevance to HD clinical presentation.