Current Trainees

Muna Aryal Rizal
mentor: Jeremy Dahl and Raag Airan
(2/1/2018 - 1/31/2020)

Muna Aryal earned her MS and PhD in Physics at Boston College in 2014. Her interests focus on developing an ultrasound–based controlled drug design/delivery platform that can positively impact cancer/neurodegenerative patient care. She has been working on an application of early stage medical technology: Focused Ultrasound (FUS) for the treatment of central nervous system diseases in preclinical animal models. She uses this technology to deliver drugs to the brain either by combining with microbubbles to reversibly open the Blood Brain Barrier (BBB) or nanodroplets to locally uncage drug upon sonication. During her Ph.D. thesis and postdoctoral training with Nathan McDannold at Harvard University, she demonstrated that FUS mediated BBB opening allowed sufficient delivery of chemotherapeutics non-invasively to the rat brain tumor to reduce tumor size and increase their survival. During her second postdoctoral fellowship with Dr. Raag Airan at Stanford, she has been using FUS to uncage drug from polymeric-nanodroplets in the brains of rats, and studying the resultant changes in brain function and behavior. However a method is needed to visualize the drug-uncaging event to validate and calibrate the delivered drug dose in a controlled fashion. As a SCIT fellow, she will work with Dr. Jeremy Dahl and Dr. Raag Airan to develop and test the feasibility of passive acoustic imaging (PAI) during FUS drug uncaging from nanodroplets, and determine the spatial and temporal dynamics of the ultrasonic drug uncaging event with respect to its resultant biological effects. Together, this drug delivery phenomenon will be dynamically recorded using the fusion of FUS, PAI, and PET imaging technologies in a large translational animal model. If successful, this effort could yield a closed-loop system for ultrasonic drug delivery, with real time imaging and calibration of the delivered dose that is primed for translation to the clinic immediately.

Linxi Shi
mentors: Brian Hargreaves and Bruce Daniel
(9/1/2017 - 9/5/2019)

Linxi earned her MS in Biomedical Engineering at Worcester Polytechnic Institute in 2010, and PhD in Medical Physics in 2017 from Georgia Institute of Technology. Her research interest is development of quantitative and computational tools to enhance the roles of quantitative imaging in cancer diagnosis and treatment. Her previous research focuses on developing novel artifact correction and reconstruction algorithms for cone beam computer tomography, with concentrations on its application on breast cancer diagnosis and image guided radiation therapy. As a SCIT postdoctoral fellow, she will work with Dr. Brian Hargreaves and use dynamic contrast enhanced MRI with more accurate pharmacokinetic modeling to improve the discrimination of breast cancer.

Hersh Sagreiya
mentors: Daniel Rubin
(7/2/2017 - 6/30/2018 & 9/6/2018 - 9/5/2019)

Hersh earned his BA in Biochemical Sciences at Harvard in 2007, his MD at Stanford in 2012, and completed a residency in Diagnostic Radiology at the University of Pittsburgh in 2017. He previously worked in the laboratory of Dr. Russ Altman at Stanford, doing research in pharmacogenomics and medical informatics. His current two greatest areas of interest are medical imaging informatics and molecular imaging. He is working in the laboratories of Dr. Daniel Rubin and Dr. Juergen Willmann. As part of an RSNA Fellow grant, he will use machine learning and texture analysis to develop a quantitative tool for the early detection of ovarian cancer. This study will specifically use BR55, a novel molecular imaging agent that targets sites of neoangiogenesis. He is interested in additional opportunities to apply deep learning techniques, as well as correlating radiologic and pathologic data.