title: Inborn errors of metabolism: combining clinical and radiologic clues to solve the mystery.
abstract: OBJECTIVE
  Inborn errors of metabolism in children can be challenging to interpret because of the similarity of their appearances on imaging. There are important clues to the diagnosis based on clinical history, head circumference (e.g., macrocephaly), geographic distribution of lesions (e.g., subcortical vs deep white matter or frontal vs parietooccipital), and other imaging features (e.g., contrast enhancement, calcification, cysts, and cortical dysplasia).
  
  
  CONCLUSIONS
  In this article, we present an algorithm-based approach to diagnosing pediatric metabolic disease with a discussion of key imaging features.
authors.affiliation: 1 Department of Radiology, Division of Neuroradiology, University of Michigan Health System, B2-A209, 1500 E Medical Center Dr, Ann Arbor, MI 48109.
authors.forename: Mohannad
authors.initials: M
authors.lastname: Ibrahim
authors.forename: Hemant A
authors.initials: HA
authors.lastname: Parmar
authors.forename: Nickoleta
authors.initials: N
authors.lastname: Hoefling
authors.forename: Ashok
authors.initials: A
authors.lastname: Srinivasan
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D020739:Brain Diseases, Metabolic, Inborn / Q000175:diagnosis*; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D009413:Nerve Fibers, Myelinated / Q000473:pathology*
keywords: imaging white matter disease; inborn errors of metabolism; inherited white matter disease; pediatric white matter disease