URAP

Precision Medicine: developing next-generation data-driven tests for real-time imaging and clinical management of Multiple Sclerosis

Roland Henry, Professor  
UC San Francisco  

Closed. This professor is continuing with Fall 2024 apprentices on this project; no new apprentices needed for Spring 2025.

The ability to quantitatively measure changes to the central nervous system is approaching a crucial milestone for neuro-imaging - the ability to measure change on an individual patient level. The Multiple Sclerosis Center at UCSF, in concert with our partners, has prioritized the development of a panoply of neuro-imaging metric that hope to provide real-time visualization of changes to the central nervous system.

We are currently working on a wide variety of longitudinal metrics that aim to quantitatively characterize the effects of neuro-degenerative processes that are in various stages of development. This spans global volumetric atrophy measures which are in deployment to the clinic, estimating myelin concentration via EPI sequences that are in use in clinical trials, and a host of novel imaging-dervied metrics being actively worked on.

We aim to spend the Fall 2023 and Spring 2024 cycle scaling our brain and spinal global atrophy service, developing sub-structural CNS measures, and validating a host of pathologically sensitive metrics that can image specific analytes sensitive to MS pathology.

The goal of this project is ambitious yet straight forward: build a clinical test that predicts clinical outcomes of our Multiple Sclerosis patients. We work close with neurologists and hope said test could help them better monitor the progress of neuro-degenerative processes.

Role: We offer a dynamic range of opportunities for undergraduates to make contributions to this initiative. This includes, but is not limited to,
* inviting select undergraduates to our weekly processing hackathons and clinical conferences to produce and interpret clinical reports for individual patients
* working with the statistical modeling team to develop novel methods (or enhancements to existing methods) to build new clinical metrics analyzing grey matter pathology, gyrification, mapping brain vasculature, and a host of other clinically relevant features
* one of our most successful undergraduate build a computational pipeline which automated the processing and analysis of thousands of spinal cord volumes that our clinical trials team uses even today!

Successful undergraduates have gone on to publish at national conferences and attend prestigious graduate degree programs.

Qualifications: While there are no hard and fast qualifications, we note we are currently experiencing shortages in folks with computational skills and in core neurobiology knowledge.

We've found in the past folks who already have some core skills in computer science (i.e. basic programming skills, data analysis skills, etc.) find the work more matched to their skillset. We work with Python, Jupyter notebooks, etc. However, we do not mandate those skills and often have found many folks who were able to pick this up quickly.

As the work here will require skills often not covered in undergraduate coursework, however, the most important skill will be a willingness to learn and capacity to work on large multi-disciplinary team.

We spend the first semester on a "low hanging fruit project" and training. This semester will give undergraduates a broad exposure to projects in the center. As such, we usually ask undergraduates to consider a year-long commitment.

Day-to-day supervisor for this project: Amit Akula, Staff Researcher

Hours: 9-11 hrs

Off-Campus Research Site: * As this is a data-intensive project, much of the work can be done remotely at any place with a sufficiently fast internet connection * The day-to-day mentors for the project work at the Sandler Neuroscience Center at UCSF Mission Bay. * For the first semester, we do ask that a half-day (or sometimes a full-day) is spent in person at UCSF Mission Bay

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