Advanced Neuroimaging Methods Nearing Clinical Translation
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Public Health Julie C. Chapman, PsyD Director of Neuroscience War Related Illness & Injury Study Center Veterans Affairs Medical Center, Washington, DC Assistant Professor of Neurology Georgetown University School of Medicine Advanced Neuroimaging Methods Nearing Clinical Translation
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Advanced Neuroimaging Methods Nearing Clinical Translation. Julie C. Chapman, PsyD Director of Neuroscience War Related Illness & Injury Study Center Veterans Affairs Medical Center, Washington, DC Assistant Professor of Neurology Georgetown University School of Medicine. - PowerPoint PPT Presentation
Transcript of Advanced Neuroimaging Methods Nearing Clinical Translation
Public Health
Julie C. Chapman, PsyDDirector of Neuroscience
War Related Illness & Injury Study Center
Veterans Affairs Medical Center, Washington, DC
Assistant Professor of NeurologyGeorgetown University School of
Medicine
Advanced Neuroimaging MethodsNearing Clinical Translation
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Patrick M. Sullivan, MAResearch Assistant
Chapman LaboratoryWar Related Illness & Injury Study
CenterVeterans Affairs Medical Center,
Washington, DC
Advanced Neuroimaging MethodsNearing Clinical Translation
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Disclaimer
The views expressed in this presentation are those of the author and DO NOT reflect the official
policy of the
Department of Veterans Affairsor
the United States Government
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Diffusion Tensor Imaging:What’s the big hairy deal? DTI has been primarily used in research
However, DTI is currently used in some clinical settings
How can DTI be helpful to healthcare providers? A basic understanding of DTI aids literature
review Scientific findings influence the way we
practice
DTI studies of mild TBI provide a good example
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mTBI Diagnosis: A History
Dubious perception of mTBI with persisting symptoms
Little physiologic evidence of injury: Clinical brain scans Physical
examination
Neuropsychologic data: differences between those with and without mTBI
Litigation inherently will be involved in some cases of mTBI.
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mTBI Diagnosis: A History
1980’s Positron Emission Tomography (PET) studies: Humayun et al. (1984) Rao et al. (1989)
PET studies found differences between groups with and without TBI.
Objective physiologic differences
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mTBI and DTI
Functional imaging method
Invasive Costly
Structural imaging method
Non-Invasive Less Costly
PET DTI
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DTI Studies with differences between mTBI and Healthy
Control Groups Bazarian et al. 2007
Benson et al. 2007
Kraus et al. 2007
Niogi et al. 2008
Rutgers et al. 2008
Wilde et al. 2008
MacDonald et al. 2011
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DTI as a Clinical Tool
Goals for: Diagnosis: Assist in the identification of
diagnostic markers Monitoring: Following the course of
progressive diseases (i.e., MS, Alzheimer’s Disease)
Treatment: identifying sites of disease-related
abnormalities to guide treatment Tracking the effects of treatment over time
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Blast Injury Outcomes (BIO) Study
mTBI + PTSD vs. Control Group
Chapman Lab
Fractional AnisotropyTapetum_LT
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Blast Injury Outcomes (BIO) Study
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Blast Injury Outcomes (BIO) Study
Preliminary Analysis, 2010
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Type 2 Diabetes Mellitus Study
DM2 + Obese vs. Obese Groups
Chapman Lab
Fractional AnisotropyFornix
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mTBI and Obesity StudyObese only vs. Control Group
Mehos & Chapman
Axial DiffusivityCingulate Gyrus_LT
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mTBI and Obesity StudyObese only vs. Control Group
Mehos & Chapman
Axial DiffusivityGenu of CC_LT
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Volumetric Analysis
A method to compare the volume of specific brain regions between patients or groups
Athinoula A. Martinos Center for Biomedical Imaging
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Volumetric Analysis
High anatomic validity (gold standard)
Extensive use of algorithms/atlas templates reduce anatomic validity
Manually Drawn Methods
Automated Methods
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Volumetric Analysis
Time-intensive Inter-rater
reliability concerns
Allows high throughput & efficient workflow
Eliminates multiple rater effects
Manually Drawn Methods
Automated Methods
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Volumetric Analysis
Automatic technique relies on distinguishing gray matter, white matter, and CSF
T1-weighted MRI images have good contrast between these types of tissue
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Automated Volumetric Analysis
Automated tools for reconstruction of the brain’s cortical surface from structural MRI data
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Automated Volumetric Analysis
Uses an algorithm to: Strip away skull and
facial tissue Find border between
the gray matter and subcortical white matter
Find border between the gray matter and the pia.
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Automated Volumetric Analysis
Registers image to atlas template
automatically parcels brain into regions based on: Atlas template Anatomic
properties of the subject brain.
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Clinical Use of Volumetric Analysis Automated programs accept standard
clinical MRI images and produce objective results independent of rater effects.
The automatically parcellated brain regions are each measured for total volume.
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Clinical Use of Volumetric Analysis These amounts can be averaged into
groups and group differences can be computed.
Volumetric differences are seen in many disease conditions such as Alzheimer’s, epilepsy, and depression
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DTI and Volumetric Analysis
Potential to improve quality of care for Veterans
Close to Translation Line
Impact Clinical Practice
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Contact Us
EMAIL: [email protected] or [email protected]
VISIT OUR WEBSITE: www.warrelatedillness.va.gov/dc/
