Neurobiological origin of spurious brain morphological changes: A quantitative MRI study

Research output: Contribution to journalArticle

Abstract

Abstract in Undetermined
The high gray-white matter contrast and spatial resolution provided by T1-weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1-weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1-weighted images (R1 (=1/T1), R2 *, and PD) in a large cohort of healthy subjects (n = 120, aged 18-87 years). Synthetic T1-weighted images were calculated from these quantitative maps and used to extract morphometry features-gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue-myelination, iron, and water content-on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Details

Authors
  • Sara Lorio
  • Ferath Kherif
  • Anne Ruef
  • Lester Melie-Garcia
  • Richard S. J. Frackowiak
  • John Ashburner
  • Gunther Helms
  • Antoine Lutti
  • Bogdan Draganski
Organisations
External organisations
  • University of Lausanne
  • University College London
  • Max Planck Institute for Human Cognitive and Brain Sciences
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Neurosciences
Original languageEnglish
Pages (from-to)1801-1815
JournalHuman Brain Mapping
Volume37
Issue number5
Early online date2016 Feb 15
Publication statusPublished - 2016
Publication categoryResearch
Peer-reviewedYes