The Resource for Quantitative Functional Magnetic Resonance Imaging is an interdepartmental and interdisciplinary Resource combining facilities of the F.M. Kirby Research Center for Functional Brain Imaging at the Kennedy Krieger Institute (KKI), the Center for Imaging Science (CIS) in the School of Engineering at Johns Hopkins University (JHU), and the group for Imaging Biostatistics in the Bloomberg School of Public Health at JHU. This Resource Center is dedicated to using its unique expertise to design novel MRI and MRS data acquisition and processing technology in order to facilitate the biomedical research of a large community of clinicians and neuroscientists in Maryland and throughout the USA, with a special focus on the changing brain throughout our life span, i.e. during neurodevelopment as well as during neurodegeneration. These NIH- funded collaborative projects have a continued need for the development of new quantitative technology to better achieve and further expand the aims in their grants, which focus on topics such as autism, impaired brain development, attention deficit hyperactivity disorder, Alzheimer's disease, multiple sclerosis, schizophrenia, primary progressive aphasia, Huntington's disease and cancer. The F.M. Kirby Center is a leading magnetic resonance technology development center that has 3T and 7T state of the art scanners equipped with parallel imaging capabilities (8, 16, and 32-channel receive coils), and a dual transmit body coil at 3T. The 7T is to be extended with a 8-channel multi-transmit system with a compatible 32-channel coil. CIS is an interdisciplinary research center that brings together a diverse group of scientists whose work rests on theoretical advances in mathematics and statistics, traditional signal and systems processing, and information theory. This Center has an IBM supercomputer that is part of a national supercomputing infrastructure. The Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health has one of the largest groups of biostatisticians focusing on neuroimaging. This Department also boasts a world class computing environment with its high performance computing cluster. Our Resource combines a strong technical environment with unique expertise of the investigators and clinicians in our collaborative projects, who are continuously asking questions to improve technology for their studies in children, the elderly, and subjects with neurological and psychiatric disorders. These needs are reflected in the proposed developments in our four technical research and development (TR&D) projects. TR&D1 focuses on MR spectroscopy (MRS) assessment of tissue changes in metabolite levels; TR&D2 develops MRI methods for detection of glutamate, cerebral blood volume (CBV), flow (CBF), metabolic rate of oxygen (CMRO2), and tissue structure iron and myelin content as reflected in magnetic susceptibility parameters. In TR&D3, new statistical approaches are developed for studying functional connectivity. The methodologies of TR&Ds 1-3 are brought together in TR&D4, where multi-contrast brain atlases are being designed that can be used to study the measured parameters, while taking into account changes in the brain shape. Together with the collaborators we optimize the new approaches to turn them into practical products. The resource provides training in these new acquisition and processing technologies and has a longstanding history of disseminating them to other research centers and hospitals.

Public Health Relevance

The goal of this Biomedical Technology Resource Center, now in its 15th year, is to develop technologies that allow quantitative measurement of MRI biomarkers for tracking changes in brain anatomy, function, metabolism and physiology and to provide reference brain atlases for such markers. These developments are pursued in close collaboration with a group of biomedical and clinical experts, who are studying impaired brain development, neurodegeneration, and disorders in which the shape of the brain has changed or is changing.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Biotechnology Resource Grants (P41)
Project #
5P41EB015909-17
Application #
9353806
Study Section
Special Emphasis Panel (ZEB1)
Program Officer
Liu, Guoying
Project Start
2000-07-01
Project End
2021-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
17
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Hugo W. Moser Research Institute Kennedy Krieger
Department
Type
DUNS #
155342439
City
Baltimore
State
MD
Country
United States
Zip Code
21205
Chen, Lin; Wei, Zhiliang; Chan, Kannie W Y et al. (2018) Protein aggregation linked to Alzheimer's disease revealed by saturation transfer MRI. Neuroimage 188:380-390
Hua, Jun; Blair, Nicholas I S; Paez, Adrian et al. (2018) Altered functional connectivity between sub-regions in the thalamus and cortex in schizophrenia patients measured by resting state BOLD fMRI at 7T. Schizophr Res :
Knutsson, Linda; Xu, Jiadi; Ahlgren, André et al. (2018) CEST, ASL, and magnetization transfer contrast: How similar pulse sequences detect different phenomena. Magn Reson Med 80:1320-1340
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Kamil, Rebecca J; Jacob, Athira; Ratnanather, John Tilak et al. (2018) Vestibular Function and Hippocampal Volume in the Baltimore Longitudinal Study of Aging (BLSA). Otol Neurotol 39:765-771
Liu, Peiying; De Vis, Jill B; Lu, Hanzhang (2018) Cerebrovascular reactivity (CVR) MRI with CO2 challenge: A technical review. Neuroimage :
Hua, Jun; Liu, Peiying; Kim, Tae et al. (2018) MRI techniques to measure arterial and venous cerebral blood volume. Neuroimage :
Li, Yang; Mao, Deng; Li, Zhiqiang et al. (2018) Cardiac-triggered pseudo-continuous arterial-spin-labeling: A cost-effective scheme to further enhance the reliability of arterial-spin-labeling MRI. Magn Reson Med 80:969-975
Wei, Zhiliang; Xu, Jiadi; Liu, Peiying et al. (2018) Quantitative assessment of cerebral venous blood T2 in mouse at 11.7T: Implementation, optimization, and age effect. Magn Reson Med 80:521-528
Li, Wenbo; Xu, Feng; Schär, Michael et al. (2018) Whole-brain arteriography and venography: Using improved velocity-selective saturation pulse trains. Magn Reson Med 79:2014-2023

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