Research

Olga Tymofiyeva, PhD, along with her colleagues, embarked on the quest of trying to understand of the brain mechanisms that underlie potential smartphone dependence. The full article can be found in Frontiers in Human Neuroscience.

Courtney Lawhn Heath, MD, took the lead on a recent prospective pilot study, published in EJNMMI Research, to determine the feasibility and utility of [68Ga]Ga-PSMA-11 PET/MRI in thyroid cancer patients.

As this history of 2020 is being written, the UC San Francisco Department of Radiology and Biomedical Imaging would like to take a moment to recognize this year’s highlights in service, patient care, research and education as well as the many department members who advocate for racial justice. 

A team of physicians from the UC San Francisco Department of Radiology and Biomedical Imaging and the San Francisco Veterans Affairs Medical Center (SFVAMC) worked on and presented a framework for how to weigh repeatedly negative test results in clinical decision making when there is ongoing concern for COVID-19.

The 17th Annual Imaging Research Symposium was held virtually for the first itme on Wednesday, October 14, 2020. Each year, the symposium is open to all in the UCSF and scientific communities to highlight the breadth and depth of innovative research being done in the department.

Recently, a team of scientists from UCSF Radiology, the UC Berkeley-UCSF Graduate Program in Bioengineering and the UCSF Department of Medicine Division of Cardiology came together to work to improve tradeoffs between a fixed spatial resolution and signal-to-noise ratio (SNR) for hyperpolarized 13 C MRI.

A team from the UCSF Center for Intelligent Imaging (ci2) developed a deep learning pipeline for diagnostic worklist prioritization and generalizability in assessing anterior cruciate ligament (ACL) lesions.

A new study from scientists at UCSF Radiology and Biomedical Imaging uses artificial intelligence (AI) to predict the presence of specific genetic alterations in individual patient's tumors using only non-invasive brain MRI. 

A paper from a team of scientists at the UCSF Ci2 won the 2020 Best Paper Award at Medical Imaging with Deep Learning (MIDL) earlier this month.

A team of scientists set out to assess whole brain and regional patterns of cerebrovascular reactivity (CVR) abnormalities in HIV-infected women using quantitative whole brain arterial spin labeling (ASL).