title: Brain morphometric analysis predicts decline of intelligence quotient in children with sickle cell disease: A preliminary study.
abstract: OBJECTIVE
  For children with sickle cell disease (SCD) and at low risk category of stroke, we aim to build a predictive model to differentiate those with decline of intelligence-quotient (IQ) from counterparts without decline, based on structural magnetic-resonance (MR) imaging volumetric analysis.
  
  
  METHODS
  This preliminary prospective cohort study included 25 children with SCD, homozygous for hemoglobin S, with no history of stroke and transcranial Doppler mean velocities below 170cm/s at baseline. We administered the Kaufman Brief Intelligence Test (K-BIT) to each child at yearly intervals for 2-4 years. Each child underwent MR examination within 30 days of the baseline K-BIT evaluation date. We calculated K-BIT change rates, and used rate of change in K-BIT to classify children into two groups: a decline group and a non-decline group. We then generated predictive models to predict K-BIT decline/non-decline based on regional gray-matter (GM) volumes computed from structural MR images.
  
  
  RESULTS
  We identified six structures (the left median cingulate gyrus, the right middle occipital gyrus, the left inferior occipital gyrus, the right fusiform gyrus, the right middle temporal gyrus, the right inferior temporal gyrus) that, when assessed for volume at baseline, are jointly predictive of whether a child would suffer subsequent K-BIT decline. Based on these six regional GM volumes and the baseline K-BIT, we built a prognostic model using the K*algorithm. The accuracy, sensitivity and specificity were 0.84, 0.78 and 0.86, respectively.
  
  
  CONCLUSIONS
  GM volumetric analysis predicts subsequent IQ decline for children with SCD.
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA. Electronic address: rchen@umm.edu.
authors.forename: Rong
authors.initials: R
authors.lastname: Chen
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA. Electronic address: jkrejza@me.com.
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Krejza
authors.affiliation: Department of Neurology, Medical University of Silesia, Katowice, Poland.
authors.forename: Michal
authors.initials: M
authors.lastname: Arkuszewski
authors.affiliation: Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, USA; Department of Radiology, The Raymond and Ruth Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA.
authors.forename: Robert A
authors.initials: RA
authors.lastname: Zimmerman
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA.
authors.forename: Edward H
authors.initials: EH
authors.lastname: Herskovits
authors.affiliation: Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, USA.
authors.forename: Elias R
authors.initials: ER
authors.lastname: Melhem
mesh_terms: D000755:Anemia, Sickle Cell / Q000473:pathology*; D001921:Brain / Q000473:pathology*; D016022:Case-Control Studies; D002648:Child; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007360:Intelligence; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D010865:Pilot Projects; D011379:Prognosis; D011446:Prospective Studies; D012959:Socioeconomic Factors
keywords: Biomarker; Cognitive decline; Magnetic resonance; Predictive modeling; Sickle cell disease