Overview
This course is designed for physicists and engineers to provide an
introduction to new or emerging MR methods and applications that are
gaining interest. The session provides a description of the underlying
physics principles, image acquisition and reconstruction methods,
pitfalls and challenges associated with quantitative imaging of the
brain beyond the standard measures of apparent diffusion coefficient
(ADC) and fractional anisotropy (FA). The clinical potential of advanced
quantitative measures (such as kurtosis, neurite density, orientation
dispersion, etc.) will be discussed.
Target Audience
Those with an interest in: 1) understanding principles of extracting
more advanced quantitative metrics for brain imaging based in water
diffusion, including the dependance on the diffusion acquisition
methods; 2) understanding the image processing pipeline that is needed
to generate the quantitative parametric maps, and 3) understanding the
clinical relevance and potential of the advanced quantitative measures
in the brain (e.g., assessment of traumatic brain injury, multiple
sclerosis, etc.).
Educational Objectives
Upon completion of this course, participants should be able to:
- Understand and implement the appropriate and optimum image acquisition method in order to acquire quantitative metrics in the brain beyond FA and ADC maps;
- Implement an image processing pipeline to generate advanced brain quantitative metrics (such as kurtosis, neurite density, orientation dispersion, etc.) from diffusion acquisitions; and
- Better understand and appreciate the added information of advanced brain quantitative metrics as it relates to neurological and neuropsychiatric applications in the brain, such as TBI, MS, dementia.
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07:00
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Advanced Brain Quantitative Metrics -- Description, Overview
& Method 
Dmitry S. Novikov1
1Center for Biomedical Imaging, Department of
Radiology, NYU School of Medicine, New York, NY, United
States
I will systematize brain diffusion models and their
assumptions, according to the length scales they are
meant to probe. I will mainly focus on the two major
avenues for probing brain microstructure: (i)
approximating the diffusion signal as a sum of multiple
Gaussian components, with the major challenge being in
the parameter estimation; (ii) lifting the Gaussian
diffusion assumption, corresponding to the
time-dependent effects in diffusion, due to structurally
disordered neuronal tissue geometry at the micrometer
scale. I will also give an outlook on the future
research directions which can open exciting
possibilities for developing markers of pathology.
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07:25
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Advanced Brain Quantitative Metrics - Clinical Potential &
Relevance
Peter Basser1
1NICHD, National Institutes of Health,
Bethesda, MD, United States
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07:50
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Adjournment & Meet the
Teachers |
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