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Delayed brain development of Rolandic epilepsy profiled by deep learning-based neuroanatomic imaging.

Qirui ZhangYan HeTaiping QuFang YangYing LinZheng HuXiuli LiQiang XuWei XingValentina GumenyukSteven M StufflebeamHesheng LiuGuangming LuZhiqiang Zhang
Published in: European radiology (2021)
• The children with Rolandic epilepsy showed imaging phenotypes of delayed brain development with increased GM volume and decreased WM volume in the Rolandic regions. • The children with Rolandic epilepsy had a 0.45-year delay of brain-predicted age by comparing with typically developing children, using 3D-CNN-based brain age prediction model. • The delayed brain age was associated with morphometric changes in the Rolandic regions and attentional deficit in Rolandic epilepsy.
Keyphrases
  • resting state
  • white matter
  • young adults
  • deep learning
  • functional connectivity
  • cerebral ischemia
  • high resolution
  • artificial intelligence
  • mass spectrometry
  • subarachnoid hemorrhage