Dataset Information

Multimodal MR imaging of brain iron in attention deficit hyperactivity disorder: a noninvasive biomarker that responds to psychostimulant treatment?

ABSTRACT:

Purpose

To comprehensively assess brain iron levels in typically developing control subjects and patients with attention deficit hyperactivity disorder (ADHD) when psychostimulant medication history is accounted for.

Materials and methods

This prospective study was approved by the institutional review board, and informed consent was obtained. Brain iron was indexed noninvasively by using magnetic resonance (MR) imaging relaxation rates (R2, R2*, R2') and magnetic field correlation (MFC) in the globus pallidus, putamen, caudate nucleus, and thalamus for 22 patients with ADHD (12 medication-naïve patients and 10 with a history of psychostimulant treatment) and 27 control subjects (age range, 8-18 years). Serum iron measures were also collected. Subgroup differences were analyzed with data-appropriate omnibus tests followed by post hoc pairwise comparisons; false discovery rate correction was conducted to control for multiple comparisons.

Results

Medication-naïve ADHD patients had significantly lower striatal and thalamic MFC indexes of brain iron than did control subjects (putamen, P = .012; caudate nucleus, P = .008; thalamus, P = .012) and psychostimulant-medicated ADHD patients (putamen, P = .006; caudate nucleus, P = .010; thalamus, P = .021). Conversely, the MFC indexes in medicated patients were comparable to those in control subjects. No significant differences were detected with R2, R2*, R2', or serum measures.

Conclusion

Lower MFC indexes of striatal and thalamic brain iron in medication-naïve ADHD patients and lack of differences in psychostimulant-medicated patients suggest that MFC indexes of brain iron may represent a noninvasive diagnostic biomarker that responds to psychostimulant treatment.

SUBMITTER: Adisetiyo V

PROVIDER: S-EPMC4263268 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Publications

Multimodal MR imaging of brain iron in attention deficit hyperactivity disorder: a noninvasive biomarker that responds to psychostimulant treatment?

Adisetiyo Vitria V Jensen Jens H JH Tabesh Ali A Deardorff Rachael L RL Fieremans Els E Di Martino Adriana A Gray Kevin M KM Castellanos Francisco X FX Helpern Joseph A JA

Radiology 20140617 2

<h4>Purpose</h4>To comprehensively assess brain iron levels in typically developing control subjects and patients with attention deficit hyperactivity disorder (ADHD) when psychostimulant medication history is accounted for.<h4>Materials and methods</h4>This prospective study was approved by the institutional review board, and informed consent was obtained. Brain iron was indexed noninvasively by using magnetic resonance (MR) imaging relaxation rates (R2, R2*, R2') and magnetic field correlation ...[more]

PMID: 24937545

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Project description:Attention-deficit/hyperactivity disorder (ADHD) is one of the most common brain diseases among children. The current criteria of ADHD diagnosis mainly depend on behavior analysis, which is subjective and inconsistent, especially for children. The development of neuroimaging technologies, such as magnetic resonance imaging (MRI), drives the discovery of brain abnormalities in structure and function by analyzing multimodal neuroimages for computer-aided diagnosis of brain diseases. This paper proposes a multimodal machine learning framework that combines the Boruta based feature selection and Multiple Kernel Learning (MKL) to integrate the multimodal features of structural and functional MRIs and Diffusion Tensor Images (DTI) for the diagnosis of early adolescent ADHD. The rich and complementary information of the macrostructural features, microstructural properties, and functional connectivities are integrated at the kernel level, followed by a support vector machine classifier for discriminating ADHD from healthy children. Our experiments were conducted on the comorbidity-free ADHD subjects and covariable-matched healthy children aged 9-10 chosen from the Adolescent Brain and Cognitive Development (ABCD) study. This paper is the first work to combine structural and functional MRIs with DTI for early adolescents of the ABCD study. The results indicate that the kernel-level fusion of multimodal features achieves 0.698 of AUC (area under the receiver operating characteristic curves) and 64.3% of classification accuracy for ADHD diagnosis, showing a significant improvement over the early feature fusion and unimodal features. The abnormal functional connectivity predictors, involving default mode network, attention network, auditory network, and sensorimotor mouth network, thalamus, and cerebellum, as well as the anatomical regions in basal ganglia, are found to encode the most discriminative information, which collaborates with macrostructure and diffusion alterations to boost the performances of disorder diagnosis.

Dataset Information

Multimodal MR imaging of brain iron in attention deficit hyperactivity disorder: a noninvasive biomarker that responds to psychostimulant treatment?

Purpose

Materials and methods

Results

Conclusion

Publications

Multimodal MR imaging of brain iron in attention deficit hyperactivity disorder: a noninvasive biomarker that responds to psychostimulant treatment?

Similar Datasets

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