Changes in cerebral blood flow (CBF) reflect changes in regional brain function and provide the physiological basis for most functional brain imaging. Magnetic resonance imaging (MRI) is currently the most versatile tool for brain imaging, and provides detailed information about both structure and function within the same modality. Arterial spin labeled (ASL) perfusion MRI uses magnetically labeled endogenous arterial blood as a quantitative flow tracer to measure CBF noninvasively using standard MRI hardware. Over a decade of research in human applications of ASL perfusion MRI in our laboratories and elsewhere have demonstrated that clinically significant changes in regional CBF can be detected in a broad range of neurological and psychiatric disorders including stroke, epilepsy, degenerative diseases, addiction, and mood disorders as well as with functional activation using sensorimotor or cognitive tasks. ASL has been shown to provide comparable CBF values and test-retest stability to other modalities, but is uniquely acquired completely noninvasively and concurrently with structural MRI. While BOLD contrast is currently the most widely used approach for functional MRI (fMRI) during task activation, BOLD reflects a complex and incompletely characterized interaction between biophysical and physiological processes with minimal capability of assessing resting brain function. Assessment of resting brain function is critical for clinical studies involving pharmacological interventions or pathophysiological changes, and for characterizing functional brain phenotypes. ASL perfusion MRI can noninvasively quantify CBF both at rest and with task activation. Furthermore, because ASL perfusion MRI measures a purely biological parameter (blood flow in ml/g/min), it provides a stable and reproducible measure of regional brain function that is independent of scanner effects, and therefore suitable for multisite or longitudinal studies where scanner platforms may vary. Numerous methodological enhancements now provide much higher quality ASL perfusion MRI data than was previously available. However, access to cutting-edge ASL methodology is currently limited to a few labs with specific expertise in ASL implementation. This project will implement and validate state-of-the-art ASL pulse sequences for the two most common scanner platforms, GE and Siemens, which comprise the majority of deployed scanners. The resulting sequences will capitalize on several recent methodological developments including high field strength, multicoil receiver arrays, parallel imaging, background suppression, T2*- insensitive imaging, and improved labeling schemes. Key parameters affecting quantification of CBF using ASL will also be assessed, and software tools for quality assurance and quantification of ASL perfusion MRI will be developed. The resulting pulse sequences and software will be made available to the research community as research products. Once the key acquisition and analysis parameters are defined, these approaches should also be readily adapted to other hardware platforms.Imaging provides new insights into human brain structure and function and is critical for further understanding brain disorders and their treatment. This project will develop software for obtaining and quantifying human brain function noninvasively using magnetic resonance imaging (MRI). The resulting technology will be made available to the biomedical community as a research product.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH080729-03
Application #
7848154
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Freund, Michelle
Project Start
2007-09-27
Project End
2012-05-31
Budget Start
2010-06-01
Budget End
2012-05-31
Support Year
3
Fiscal Year
2010
Total Cost
$404,075
Indirect Cost
Name
University of Pennsylvania
Department
Neurology
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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Zhao, Li; Dai, Weiying; Soman, Salil et al. (2017) Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images. IEEE Trans Med Imaging 36:487-496
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