Defining and Characterizing GWI Pathobiology Using Longitudinal Brain Imaging Biomarkers of White Matter Integrity and Hemodynamic Response

Abstract

Many Gulf War (GW) veterans experience chronic symptoms of Gulf War Illness (GWI), Although GWI remains a disorder primarily diagnosed by self-report of symptoms, our research has shown important preliminary evidence for brain imaging biomarkers correlated with these symptoms. This study builds on our key Boston Gulf War Illness Consortium (GWIC) multi-modal brain imaging findings in GWI cases that 1) white matter (WM) microstructural alterations on diffusion tensor imaging (DTI) are present and related to behavioral outcomes, 2) functional connectivity alterations are present on fMRI and pCASL, and 3) Brain volumes are reduced in gray matter (GM) and WM pathways. The study objectives are to confirm, validate and further define WM microstructural integrity decrements in multiple imaging modalities (DKI and HARDI). This proposal aims to assess the overlap of WM decrements with cerebral blood alterations (pCASL) in GWI cases vs controls. We hypothesize that GWIC study will be confirmed and perhaps worsened on longitudinal analyses in GWI cases. Lastly, data reduction techniques will be employed to predict GWI case status, identify clinically relevant subgroups and changes in illness presentation over time by utilizing machine learning analytics of DKI, diffusion MRI, pCASL and brain volumetric analyses in this proposed longitudinal dataset.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2020
Accession Number
AD1124996

Entities

People

  • Kimberly Sullivan

Organizations

  • Boston University Medical Campus

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Alzheimer Disease
  • Brain
  • Brain Injuries
  • Cardiovascular Physiological Phenomena
  • Cells
  • Cellular Structures
  • Cerebrovascular Disorders
  • Data Mining
  • Data Reduction
  • Diagnostic Imaging
  • Health Services
  • Information Processing
  • Information Science
  • Machine Learning
  • Medical Personnel
  • Network Science
  • Neuroglia
  • Neuroimaging
  • Supervised Machine Learning
  • Traumatic Stress Disorder

Readers

  • Gulf War Illness and Chronic Multisymptom Illness in Veterans.
  • Medical Imaging.

Technology Areas

  • AI & ML