The DiBella lab seeks to invent and refine new and better methods for the acquisition, reconstruction, and post-processing of MRI, with particular emphasis on cardiac and stroke applications. Our lab seeks to translate these improvements to clinical studies, and to use the methods to better understand physiology in health and disease. One set of current projects involves development of improved methods for measuring myocardial perfusion and fibrosis with MRI. Methods for higher spatial resolution, greater coverage, and elucidating differences across the cardiac cycle are being developed. We have pulse programmed new simultaneous multi-slice (SMS) and 3D acquisitions on the MRI scanner. Advanced reconstruction methods including constrained reconstruction and deep learning methods are also being developed for cardiac applications. Another project is to develop and evaluate methods for imaging the brain microstructure with diffusion MRI. SPUR students could work on either or both projects.
The stipend for this SPUR project is funded by an American Heart Association grant awarded to Dr. Stavros Drakos, MD, PhD. The stipend for this project is $4,000 instead of $5,000 due to grant funding limitations.
We use custom matlab and python software to process the MRI data and obtain quantitative perfusion values in the heart in ml/min/g of blood flow to tissue, or to obtain maps of white matter fiber orientations in stroke subjects. We need someone to learn this software, process data, and extend the software to do a better job of quantification and to help validate these improvements.
Student Learning Outcomes & Benefits
The applicant will have more and more enhanced research skills, and more insight into cardiovascular research after this relatively brief training period in our laboratory. This should aid them in further refining their career goals and allow them to better map a strategy for reaching their career goals.The applicant will obtain more skills and more enhanced research skills, and more insight into cardiovascular research after this relatively brief training period in our laboratory. This should aid them in further refining their career goals and allow them to better map a strategy for reaching their career goals.
Remote Contingency Plan
In the case that students are required to work remotely for some or all of the Summer 2021 semester, these projects will in large part proceed as outline above, although in person meetings will be replaced with zoom meetings and additional email communications. We have sufficient data already for these projects so that development of analysis methods can proceed. We also have access to large public databases that are relevant to the brain diffusion (stroke) project.
Radiology & Imaging Sciences
School of Medicine
I plan to gauge the applicant’s background and develop a training plan that has them actively involved in one or more of our research projects nearly immediately. They will need skills with matlab or python programming. Attention to detail is also important. As the student becomes capable with certain skills such as programming or human imaging or work with animal studies, they will be given increasing personal responsibility for these studies. Related Training and Course Work: The student will be trained by me or others in the group in the essential skills for whichever project is most appropriate. They will also participate in our monthly “ReCon” (Research Connections) seminar, as well as our Radiology and Imaging Sciences Department seminars for MDs and PhDs, a Deep Learning Journal Club, and our weekly DiBella group meetings. Depending on the project, we also work with cardiologists, neurologists, and radiologists. My group is currently funded by two NIH R01s – (PI DiBella and PI Adluru – Dr. Ganesh Adluru is an assistant professor in our group). These fundings permit support of all studies related to the student’s projects.