Combining neuroimaging and behavior to discriminate children with attention deficit-hyperactivity disorder with and without prenatal alcohol exposure

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作者
Joseph O’Neill
Mary J. O’Connor
Guldamla Kalender
Ronald Ly
Andrea Ng
Andrea Dillon
Katherine L. Narr
Sandra K. Loo
Jeffry R. Alger
Jennifer G. Levitt
机构
[1] Jane & Terry Semel Institute for Neuroscience,Division of Child & Adolescent Psychiatry
[2] University of California Los Angeles,Department of Neurology
[3] University of California Los Angeles,undefined
[4] Neurospectroscopics,undefined
[5] LLC,undefined
[6] Advanced Imaging Research Center,undefined
[7] University of Texas Southwestern Medical Center,undefined
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关键词
Fetal alcohol spectrum disorder; Attention deficit hyperactivity disorder; Magnetic resonance spectroscopy; Diffusion tensor imaging; White matter;
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摘要
In many patients, ostensible idiopathic attention deficit-hyperactivity disorder (ADHD) may actually stem from covert prenatal alcohol exposure (PAE), a treatment-relevant distinction. This study attempted a receiver-operator characteristic (ROC) classification of children with ADHD into those with PAE (ADHD+PAE) and those without (ADHD-PAE) using neurobehavioral instruments alongside magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) of supraventricular brain white matter. Neurobehavioral, MRS, and DTI endpoints had been suggested by prior findings. Participants included children aged 8–13 years, 23 with ADHD+PAE, 19 with familial ADHD-PAE, and 28 typically developing (TD) controls. With area-under-the-curve (AUC) >0.90, the Conners 3 Parent Rating Scale Inattention (CIn) and Hyperactivity/Impulsivity (CHp) scores and the Behavioral Regulation Index (BRI) of the Behavior Rating Inventory of Executive Function (BRIEF2) excellently distinguished the clinical groups from TD, but not from each other (AUC < 0.70). Combinations of MRS glutamate (Glu) and N-acetyl-compounds (NAA) and DTI mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and fractional anisotropy (FA) yielded “good” (AUC > 0.80) discrimination. Neuroimaging combined with CIn and BRI achieved AUC 0.72 and AUC 0.84, respectively. But neuroimaging combined with CHp yielded 14 excellent combinations with AUC ≥ 0.90 (all p < 0.0005), the best being Glu·AD·RD·CHp/(NAA·FA) (AUC 0.92, sensitivity 1.00, specificity 0.82, p < 0.0005). Using Cho in lieu of Glu yielded AUC 0.83. White-matter microstructure and metabolism may assist efforts to discriminate ADHD etiologies and to detect PAE, beyond the ability of commonly used neurobehavioral measures alone.
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页码:69 / 77
页数:8
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