• Matthias W Wagner, Andrea Poretti, Jane E Benson, and Thierry A G M Huisman.
• Section of Pediatric Neuroradiology, Division of Pediatric Radiology, Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, Baltimore, MD.
• J Neuroimaging. 2017 Mar 1; 27 (2): 162-209.

AbstractGenetic skeletal disorders (GSDs) are a heterogeneous group characterized by an intrinsic abnormality in growth and (re-)modeling of cartilage and bone. A large subgroup of GSDs has additional involvement of other structures/organs beside the skeleton, such as the central nervous system (CNS). CNS abnormalities have an important role in long-term prognosis of children with GSDs and should consequently not be missed. Sensitive and specific identification of CNS lesions while evaluating a child with a GSD requires a detailed knowledge of the possible associated CNS abnormalities. Here, we provide a pattern-recognition approach for neuroimaging findings in GSDs guided by the obvious skeletal manifestations of GSD. In particular, we summarize which CNS findings should be ruled out with each GSD. The diseases (n = 180) are classified based on the skeletal involvement (1. abnormal metaphysis or epiphysis, 2. abnormal size/number of bones, 3. abnormal shape of bones and joints, and 4. abnormal dynamic or structural changes). For each disease, skeletal involvement was defined in accordance with Online Mendelian Inheritance in Man. Morphological CNS involvement has been described based on extensive literature search. Selected examples will be shown based on prevalence of the diseases and significance of the CNS involvement. CNS involvement is common in GSDs. A wide spectrum of morphological abnormalities is associated with GSDs. Early diagnosis of CNS involvement is important in the management of children with GSDs. This pattern-recognition approach aims to assist and guide physicians in the diagnostic work-up of CNS involvement in children with GSDs and their management.Copyright © 2016 by the American Society of Neuroimaging.

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