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David A. Hovda

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

2 papers
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2

YNICL Journal 2019 Journal Article

pH-weighted molecular MRI in human traumatic brain injury (TBI) using amine proton chemical exchange saturation transfer echoplanar imaging (CEST EPI)

  • Benjamin M. Ellingson
  • Jingwen Yao
  • Catalina Raymond
  • Ararat Chakhoyan
  • Kasra Khatibi
  • Noriko Salamon
  • J. Pablo Villablanca
  • Ina Wanner

Cerebral acidosis is a consequence of secondary injury mechanisms following traumatic brain injury (TBI), including excitotoxicity and ischemia, with potentially significant clinical implications. However, there remains an unmet clinical need for technology for non-invasive, high resolution pH imaging of human TBI for studying metabolic changes following injury. The current study examined 17 patients with TBI and 20 healthy controls using amine chemical exchange saturation transfer echoplanar imaging (CEST EPI), a novel pH-weighted molecular MR imaging technique, on a clinical 3T MR scanner. Results showed significantly elevated pH-weighted image contrast (MTRasym at 3 ppm) in areas of T2 hyperintensity or edema (P < 0. 0001), and a strong negative correlation with Glasgow Coma Scale (GCS) at the time of the MRI exam (R 2 = 0. 4777, P = 0. 0021), Glasgow Outcome Scale - Extended (GOSE) at 6 months from injury (R 2 = 0. 5334, P = 0. 0107), and a non-linear correlation with the time from injury to MRI exam (R 2 = 0. 6317, P = 0. 0004). This evidence suggests clinical feasibility and potential value of pH-weighted amine CEST EPI as a high-resolution imaging tool for identifying tissue most at risk for long-term damage due to cerebral acidosis.

YNICL Journal 2012 Journal Article

Neuroimaging of structural pathology and connectomics in traumatic brain injury: Toward personalized outcome prediction

  • Andrei Irimia
  • Bo Wang
  • Stephen R. Aylward
  • Marcel W. Prastawa
  • Danielle F. Pace
  • Guido Gerig
  • David A. Hovda
  • Ron Kikinis

Recent contributions to the body of knowledge on traumatic brain injury (TBI) favor the view that multimodal neuroimaging using structural and functional magnetic resonance imaging (MRI and fMRI, respectively) as well as diffusion tensor imaging (DTI) has excellent potential to identify novel biomarkers and predictors of TBI outcome. This is particularly the case when such methods are appropriately combined with volumetric/morphometric analysis of brain structures and with the exploration of TBI-related changes in brain network properties at the level of the connectome. In this context, our present review summarizes recent developments on the roles of these two techniques in the search for novel structural neuroimaging biomarkers that have TBI outcome prognostication value. The themes being explored cover notable trends in this area of research, including (1) the role of advanced MRI processing methods in the analysis of structural pathology, (2) the use of brain connectomics and network analysis to identify outcome biomarkers, and (3) the application of multivariate statistics to predict outcome using neuroimaging metrics. The goal of the review is to draw the community's attention to these recent advances on TBI outcome prediction methods and to encourage the development of new methodologies whereby structural neuroimaging can be used to identify biomarkers of TBI outcome.

v2026.09.13