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Assessment of longitudinal hippocampal atrophy in the first year after ischemic stroke using automatic segmentation techniques.
Journal article

Assessment of longitudinal hippocampal atrophy in the first year after ischemic stroke using automatic segmentation techniques.

  • Khlif MS The Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
  • Werden E The Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
  • Egorova N The Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia.
  • Boccardi M LANVIE-Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
  • Redolfi A Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
  • Bird L The Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia.
  • Brodtmann A The Florey Institute for Neuroscience and Mental Health, University of Melbourne, Melbourne, Australia; Department of Neurology, Austin Health, Heidelberg, Victoria, Australia.
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  • 2019-11-12
Published in:
  • NeuroImage. Clinical. - 2019
Freesurfer
Hippocampal atrophy
Linear mixed-effect model
Magnetic resonance imaging
Stroke
Aged
Atrophy
Female
Hippocampus
Humans
Image Interpretation, Computer-Assisted
Longitudinal Studies
Magnetic Resonance Imaging
Male
Middle Aged
Neuroimaging
Stroke
English We assessed first-year hippocampal atrophy in stroke patients and healthy controls using manual and automated segmentations: AdaBoost, FIRST (fsl/v5.0.8), FreeSurfer/v5.3 and v6.0, and Subfields (in FreeSurfer/v6.0). We estimated hippocampal volumes in 39 healthy controls and 124 stroke participants at three months, and 38 controls and 113 stroke participants at one year. We used intra-class correlation, concordance, and reduced major axis regression to assess agreement between automated and 'Manual' estimations. A linear mixed-effect model was used to characterize hippocampal atrophy. Overall, hippocampal volumes were reduced by 3.9% in first-ever stroke and 9.2% in recurrent stroke at three months post-stroke, with comparable ipsi-and contra-lesional reductions in first-ever stroke. Mean atrophy rates between time points were 0.5% for controls and 1.0% for stroke patients (0.6% contra-lesionally, 1.4% ipsi-lesionally). Atrophy rates in left and right-hemisphere strokes were comparable. All methods revealed significant volume change in first-ever and ipsi-lesional stroke (p < 0.001). Hippocampal volume estimation was not impacted by hemisphere, study group, or scan time point, but rather, by the interaction between the automated segmentation method and hippocampal size. Compared to Manual, Subfields and FIRST recorded the lowest bias. FreeSurfer/v5.3 overestimated volumes the most for large hippocampi, while FIRST was the most accurate in estimating small volumes. AdaBoost performance was average. Our findings suggest that first-year ipsi-lesional hippocampal atrophy rate especially in first-ever stroke, is greater than atrophy rates in healthy controls and contra-lesional stroke. Subfields and FIRST can complementarily be effective in characterizing the hippocampal atrophy in healthy and stroke cohorts.
Language
  • English
Open access status
gold
Identifiers
Persistent URL
https://sonar.ch/global/documents/271932
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