Predicting brain age for veterans with traumatic brain injuries and healthy controls: an exploratory analysis.

Journal: Frontiers in aging neuroscience
Published Date: Jan 1, 2025

Abstract

BACKGROUND: Traumatic brain injury (TBI) is associated with increased dementia risk. This may be driven by underlying biological changes resulting from the injury. Machine learning algorithms can use structural MRIs to give a predicted brain age (pBA). When the estimated age is greater than the chronological age (CA), this is called the brain age gap (BAg). We analyzed this outcome in men and women with and without TBI.

Authors

  • John P Coetzee
    Rehabilitation Service, VA Palo Alto Health Care System, Palo Alto, CA, United States.
  • Xiaojian Kang
    Rehabilitation Service, VA Palo Alto Health Care System, Palo Alto, CA, United States.
  • Victoria Liou-Johnson
    Rehabilitation Service, VA Palo Alto Health Care System, Palo Alto, CA, United States.
  • Ines Luttenbacher
    Department of Psychology, University of Amsterdam, Amsterdam, Netherlands.
  • Srija Seenivasan
    Uniformed Services University of the Health Sciences, Bethesda, MA, United States.
  • Elika Eshghi
    Icahn School of Medicine at Mount Sinai, New York, NY, United States.
  • Daya Grewal
    Department of Psychology, Palo Alto University, Palo Alto, CA, United States.
  • Siddhi Shah
    Rehabilitation Service, VA Palo Alto Health Care System, Palo Alto, CA, United States.
  • Frank Hillary
    Department of Psychology, Pennsylvania State University, University Park, PA, United States.
  • Emily L Dennis
    Department of Neurology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
  • Maheen M Adamson
    10624Stanford University School of Medicine, Palo Alto, CA, USA.

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