Age-specific MRI patterns in pediatric epilepsy: insights from a sudanese cohort and implications for low-resources

Yousif Mohamed1, Abubaker Babiker2, Hind Elamin3

  • 1Facutly of Medicine, University of Khartoum, Khartoum, Sudan. Valyvxly@gmail.com.

BMC Medical Imaging
|July 3, 2026
PubMed

Insights

Magnetic Resonance Imaging (MRI) reveals abnormalities in one-third of pediatric epilepsy cases in Sudan, with findings varying by age. Prioritizing neuroimaging for infants and adolescents can improve diagnosis and resource allocation in low-income settings.

Area of Science:

  • Pediatric Neurology
  • Neuroimaging
  • Global Health

Background:

  • Epilepsy significantly impacts children's quality of life globally.
  • Neuroimaging, especially MRI, is vital for identifying epilepsy causes.
  • Optimizing diagnostic yield in low-resource settings is crucial for pediatric epilepsy management.

Purpose of the Study:

  • To assess the diagnostic value of MRI in Sudanese pediatric epilepsy patients.
  • To identify age-specific patterns in neuroimaging findings.
  • To inform resource allocation for epilepsy diagnosis in low-income countries.

Main Methods:

  • A cross-sectional study included 100 pediatric epilepsy patients (≤17 years).
  • Data collected included age, gender, and MRI findings.
  • Statistical analysis involved Chi-square tests and logistic regression.

Main Results:

  • 31% of patients had abnormal MRI findings; mesial temporal sclerosis was most common.
  • Abnormalities were significantly associated with age (P=0.002), particularly in infants (<1 year) and adolescents (13-17 years).
  • Specific findings like periventricular leukomalacia, atrophy, mesial temporal sclerosis, and tumors showed age-related prevalence.

Conclusions:

  • MRI detects abnormalities in a substantial portion of pediatric epilepsy cases.
  • Age is a key factor influencing MRI findings in pediatric epilepsy.
  • Age-specific MRI protocols and targeted neuroimaging in infants and adolescents can enhance diagnostic efficiency in resource-limited settings.
Abstract

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