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Related Experiment Video

Updated: Mar 3, 2026

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
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Lissencephaly: Expanded imaging and clinical classification.

Nataliya Di Donato1,2, Sara Chiari3, Ghayda M Mirzaa2,4

  • 1Institute for Clinical Genetics, Tu Dresden, Dresden, Germany.

American Journal of Medical Genetics. Part A
|April 26, 2017
PubMed
Summary
This summary is machine-generated.

A new classification system for lissencephaly (LIS) and subcortical band heterotopia (SBH) based on brain imaging patterns helps predict causative genes. A novel severity scale aids in predicting clinical outcomes for LIS patients.

Keywords:
agyriaclassificationlissencephalypachygyriasubcortical band heterotopiatubulinopathy

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Area of Science:

  • Neuroscience
  • Genetics
  • Developmental Biology

Background:

  • Lissencephaly (LIS), or "smooth brain," is a complex cortical malformation characterized by disrupted neuronal migration and abnormal gyral formation.
  • Existing LIS classifications are insufficient due to the discovery of numerous LIS-associated genes (19 identified).
  • Subcortical band heterotopia (SBH) is part of the LIS spectrum, with early classifications focusing on LIS1 and DCX genes.

Purpose of the Study:

  • To develop a new, imaging-based classification system for LIS and SBH to predict causative genes.
  • To create a new scale for predicting clinical severity and outcomes in LIS-SBH patients.
  • To provide tools for improved clinical management, genetic counseling, and genetic testing interpretation for LIS-SBH.

Main Methods:

  • Review of clinical, imaging, and molecular data from 188 LIS-SBH patients diagnosed in the last 5 years.
  • Inclusion of approximately 1,400 archival patient cases and analysis of published reports.
  • Construction of a novel imaging-based classification system with 21 distinct patterns.

Main Results:

  • The new imaging-based classification system identifies 21 recognizable patterns in LIS-SBH.
  • These patterns demonstrate a reliable correlation with the most probable causative genes.
  • A new scale was developed to predict clinical severity and patient outcomes, as imaging patterns did not consistently correlate with clinical outcomes.

Conclusions:

  • The developed imaging-based classification system offers a powerful tool for predicting genetic causes of LIS-SBH.
  • The novel severity scale enhances the prediction of clinical outcomes for individuals with LIS-SBH.
  • These advancements provide crucial support for clinical decision-making, genetic counseling, and genetic testing strategies in LIS-SBH management.