Quantitative MR analysis of caudate abnormalities in pediatric ADHD: Proposal for a diagnostic test

Joan Carles Soliva, Jordi Fauquet, Anna Bielsa, Mariana Rovira, Susanna Carmona, Josep Antoni Ramos-Quiroga, Joseph Hilferty, Antoni Bulbena, Miquel Casas, Oscar Vilarroya

Research output: Contribution to journalArticleResearchpeer-review

24 Citations (Scopus)

Abstract

Most morphometric magnetic resonance imaging (MRI) studies of pediatric attention-deficit/hyperactivity disorder (ADHD) with appropriate sample sizes reveal a decreased right caudate nucleus volume. Recently, our group reported that this decrease is mainly due to a diminished right caudate body volume (rCBV). Here, we hypothesize that, employing either the total bilateral caudate volume (tbCV) or the bilateral caudate body volume (bCBV) as scaling variables, the rCBV/tbCV and rCBV/bCBV ratios could be found diminished and used as a basis of an imaging diagnostic test. Volumetric caudate nucleus data were obtained from a case-control morphometric MRI study with 39 ADHD subjects and 39 handedness- and IQ-matched controls, using a novel semi-automated caudate segmentation procedure. Student t-tests comparing each relevant ratio were conducted between the two samples. After splitting the samples into two groups, a receiving operator characteristic (ROC) analysis was conducted on the training group to determine the optimal cut-off. Its performance was then examined on the test group. The rCBV/bCBV ratio was found to be statistically different. For a value equal or inferior to 0.48, the specificity was 95.00%. We propose using the rCBV/bCBV ratio to assist in the diagnosis of ADHD in children. © 2010 Elsevier Ireland Ltd.
Original languageEnglish
Pages (from-to)238-243
JournalPsychiatry Research - Neuroimaging
Volume182
Issue number3
DOIs
Publication statusPublished - 30 Jun 2010

Keywords

  • Attention-deficit/hyperactivity disorder
  • Caudate nucleus
  • Diagnostic accuracy
  • Diagnostic test
  • Magnetic resonance imaging
  • Receiver operating characteristic analysis

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