In this grant application, we propose to develop clinicaly feasible methods for the acquisition and analysis of advanced diffusion magnetic resonance imaging (dMRI) of pediatric patients and apply it to study micro and macro level pathology in attention-deficit hyperactivity-disorder (ADHD). Advanced dMRI techniques can provide details about the layout of white matter pathways in the brain, that are not possible using the current clinical standard of diffusion tensor imaging (DTI). However, these advanced protocols require long scan times and any motion during this time results in artifacts and loss of signal. As a result, dMRI acquisition of children becomes a challenging task, particularly if they are hyperactive (as in ADHD). In this grant application, we propose several novel algorithms for fast acquisition and reconstruction of advanced dMRI protocols. In particular, we will use our multi-slice acquisition protocol (as opposed to the standard single-slice acquisition) along with a scheme to recover dMRI signals from very few measurements. This will dramatically reduce scan time and make it possible to obtain advanced dMRI scans of pediatric patients (in a clinic). We will validate our methods on several test subjects and then apply them to the study of children and adolescents with ADHD. In particular, we will analyze global connectivity properties of the anatomical neural networks in ADHD along with local diffusion based microstructural properties that may be affected due to pathology. Thus, the improvements suggested in this proposal will bring advanced dMRI protocols to the clinic and allow us to quantify micro and macro level abnormalities in patients with any type of psychiatric or neurological disorder.

Public Health Relevance

Diffusion magnetic resonance imaging is an in-vivo technique to map the neural connectivity of the brain, which allows the study of various brain disorders. In this grant application, we propose to develop clinically feasible methods for the acquisition and analysis of advanced diffusion magnetic resonance imaging (dMRI) of pediatric patients and apply it to study micro and macro level pathology in attention-deficit hyperactivity-disorder (ADHD). The proposed technology will reduce the scan time dramatically, making it possible to use advanced dMRI in the clinic on pediatric population.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
3R01MH097979-03S1
Application #
9110623
Study Section
Neuroscience and Ophthalmic Imaging Technologies Study Section (NOIT)
Program Officer
Friedman-Hill, Stacia
Project Start
2012-09-18
Project End
2015-11-30
Budget Start
2015-08-01
Budget End
2015-11-30
Support Year
3
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
Zhang, Fan; Wu, Weining; Ning, Lipeng et al. (2018) Suprathreshold fiber cluster statistics: Leveraging white matter geometry to enhance tractography statistical analysis. Neuroimage 171:341-354
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Zhang, Fan; Savadjiev, Peter; Cai, Weidong et al. (2018) Whole brain white matter connectivity analysis using machine learning: An application to autism. Neuroimage 172:826-837
Ning, Lipeng; Rathi, Yogesh (2018) A Dynamic Regression Approach for Frequency-Domain Partial Coherence and Causality Analysis of Functional Brain Networks. IEEE Trans Med Imaging 37:1957-1969
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Hamoda, Hesham M; Makhlouf, A T; Fitzsimmons, J et al. (2018) Abnormalities in thalamo-cortical connections in patients with first-episode schizophrenia: a two-tensor tractography study. Brain Imaging Behav :

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