Access to Resources

The Utilization Review Committee (URC) facilitates imaging research

All imaging studies must be reviewed and approved by the URC. The URC monitors the use of RII imaging equipment and helps investigators optimize their imaging protocols to efficiently achieve the goals of their studies.

Don’t worry, it’s easy.

1. Identify your sponsor

Faculty and senior scientists at the RII serve as Sponsors for all imaging projects, providing expert consultation on project planning, data collection, and analysis. Investigators can choose a Sponsor who has the appropriate expertise by browsing RII faculty descriptions here. Contact your sponsor by phone or email to discuss your study.

2. Submit a summary of your project to the RII Utilization Review Committee

Fill out this online form to summarize your project for the URC. Your sponsor can help if you have questions. You should already have received IRB or IACUC approval. After you submit your form, it will be reviewed at the next URC meeting (3rd Friday of each month at 10 am). If you need faster approval, your sponsor may be able to expedite the process for you.

3. Attend the URC meeting to discuss your study

URC discussions are informal and are often very helpful for investigators to receive feedback and ask questions. If you cannot attend the URC meeting, your sponsor can present the study for you.

URC Sponsor List

Peter T. Fox, M.D.
Neuroimaging, neural networks, default networks, human brain mapping, normal mapping, psychiatric disorders; emphasis on novel, analytic methods; Meta-analysis
Imaging methods:  MRI, PET, TMS

Geoffrey Clarke, Ph.D.
Cardiovascular Imaging Physics including magnetic resonance imaging of coronary flow and flow reserve, regional myocardial blood volume, left ventricular function, myocardial perfusion, epicardial fat, and vascular imaging agents
In-vivo magnetic resonance spectroscopy including phosphorus-31 MRS in skeletal muscle, hydrogen-1 MRS of lipids in skeletal muscle, myocardial muscle, and liver
Magnetic resonance imaging physics – design of RF coils, MRI pulse programming; clinical MRI quality control tests & standards
PET of heart and skeletal muscle

Amy Garrett, Ph.D.
Pediatric neuroimaging
Neuroimaging of Psychiatric Interventions in Children and Adults
Functional MRI paradigms for studying emotion processing
Imaging methods: MRI: structural, functional, DTI

Paul Jerabek, Ph.D.
Human or animal research, radiopharmaceutical
Imaging methods: PET

Jack Lancaster, Ph.D.
Image processing – all imaging modalities
Physiological modeling as applied to imaging
Database work in imaging
Brain map database
Nuclear medicine/Physics background
Imaging methods:  MRI & PET

John Li, Ph.D.
MRI physics with intense interest in developing and applying novel MRI methods for the study of various neurological diseases. Experiences using phase imaging, quantitative susceptibility mapping, susceptibility tensor imaging, diffusion tensor imaging, DCE-MRI to study cerebral micro-bleeds, iron deposition, white matter   alterations, blood brain barrier damages in brain development and ageing, multiple sclerosis and traumatic brain injury in both clinical and pre-clinical settings.

Qiang Shen, Ph.D.
Developing and applying magnetic resonance imaging (MRI) to study anatomy, physiology and function of the central nervous system in normal and diseased states in animal models.  Specific interests are: 1) stroke imaging, imaging biomarkers for early detection, longitudinal monitoring, and prediction of tissue fate of ischemic stroke; 2) novel MRI methodologies to dynamically measure blood flow, tissue oxygen tension, blood volume; 3) high-resolution functional MRI techniques for mapping layer-specific and columnar organization.
Imaging methods: anatomical imaging, cASL (blood flow), diffusion tension imaging, functional MRI

Felipe Salinas, Ph.D.
Biomedical Engineering
Computer Modeling
Magnetic Stimulation

Sidath Kumarapperuma, Ph.D.
Chemical Biology
Infectious Disease
Molecular Imaging
Nuclear Medicine/Radiochemistry
Synthetic Chemistry

Habes, Muhammed M.D.
Medical Image Analysis; Age-related brain structural changes; machine learning

Neelamegam, Ramesh Ph.D.
Radiochemistry; neurodegenerative disorders