Our goal is to provide novel, clinically feasible, and precise diffusion magnetic resonance imaging (dMRI) tech- nologies for investigation of the in-vivo human brain's cellular microstructure in early psychosis. Psychotic dis- orders are devastating brain diseases that include a range of symptoms such as delusions, hallucinations, and thought disorder. A better understanding of the etiology of psychosis can lead to improved diagnosis and treatment. dMRI is a noninvasive imaging method that has identified unique microstructural abnormalities in psychosis. However, as many pathological processes have been proposed to co-exist in psychosis, there is a need for more specific measures derived from dMRI. Current state-of-the-art dMRI encodes (measures) diffusion along a single direction using a technique called single diffusion encoding. We propose q-space trajectory imaging (QTI), a new dMRI method that dynamically changes the measurement orientation during acquisition to better characterize the true complexity of water molecule motion. The novel QTI sequences that we propose allow measurement of microstructural properties of the in-vivo human brain that are invisible using today's scanning methods. These microstructural properties are mathematically expressed in terms of variability in size (CMD), shape (C), and orientation (Cc), extracted from a model representing a mixture of distinct neuronal tissue microenvironments, such as neurites, cellular domains and extracellular spaces. To achieve our goals we propose the following three aims.
In Aim 1, we will develop experimental foundations for novel dMRI. We will investigate QTI methodologies to better characterize important pathological features expected in psychosis. We will extend the QTI framework to enable microstructural models and properties that explicitly account for restricted, non-Gaussian, and time-dependent diffusion. The successful endpoint of this aim will provide measures and models for the extraction of new microstructural properties related to psychosis from QTI.
In Aim 2, we will develop novel dMRI sequences and standards. We propose to develop robust and fast QTI pulse sequences and scan protocols, with representation of the acquisition parameters in DICOM. The successful endpoint of this aim will be novel, robust, and fast acquisitions (under 15 minutes), enabling QTI for clinical studies.
In Aim 3, we propose to study QTI-based microstructure measures in 24 early psychosis pa- tients and 24 matched controls to disentangle pathologies that co-exist in psychosis, such as neurodegenera- tive and neuroinflammatory processes. We expect that upon successful completion of the proposed project, we will have developed novel dMRI to provide increased sensitivity and specificity for the study of the in-vivo human brain's cellular microstructure.

Public Health Relevance

The overall goal is to develop in vivo diffusion magnetic resonance imaging (dMRI) to study brain pathology in early psychosis. We propose to develop novel dMRI pulse sequences and computational analysis methods for improved characterization of brain tissue microstructure. By developing a range of new measures with greater sensitivity and specificity to the nature of tissue structure and pathology in the human brain, we expect to provide a clearer understanding of the pathophysiology underlying early psychosis.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH074794-13
Application #
9765400
Study Section
Neuroscience and Ophthalmic Imaging Technologies Study Section (NOIT)
Program Officer
Wijtenburg, Andrea
Project Start
2007-02-15
Project End
2022-05-31
Budget Start
2019-06-01
Budget End
2020-05-31
Support Year
13
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Ning, Lipeng; Nilsson, Markus; Lasi?, Samo et al. (2018) Cumulant expansions for measuring water exchange using diffusion MRI. J Chem Phys 148:074109
Albi, Angela; Meola, Antonio; Zhang, Fan et al. (2018) Image Registration to Compensate for EPI Distortion in Patients with Brain Tumors: An Evaluation of Tract-Specific Effects. J Neuroimaging 28:173-182
Özarslan, Evren; Yolcu, Cem; Herberthson, Magnus et al. (2018) Influence of the size and curvedness of neural projections on the orientationally averaged diffusion MR signal. Front Phys 6:
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
McCarthy-Jones, Simon; Oestreich, Lena K L; Lyall, Amanda E et al. (2018) Childhood adversity associated with white matter alteration in the corpus callosum, corona radiata, and uncinate fasciculus of psychiatrically healthy adults. Brain Imaging Behav 12:449-458
Lyall, A E; Pasternak, O; Robinson, D G et al. (2018) Greater extracellular free-water in first-episode psychosis predicts better neurocognitive functioning. Mol Psychiatry 23:701-707
Seitz, Johanna; Rathi, Yogesh; Lyall, Amanda et al. (2018) Alteration of gray matter microstructure in schizophrenia. Brain Imaging Behav 12:54-63
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
Saito, Yukiko; Kubicki, Marek; Koerte, Inga et al. (2018) Impaired white matter connectivity between regions containing mirror neurons, and relationship to negative symptoms and social cognition, in patients with first-episode schizophrenia. Brain Imaging Behav 12:229-237

Showing the most recent 10 out of 163 publications