Bashir Lab for Liver Imaging Research
Our laboratory focuses on advanced imaging methodologies in body imaging, especially MRI of the liver. We aim to further our understanding of existing techniques and develop novel imaging methods, in part through a rich group of collaborations with members of the Non-alcoholic Steatohepatitis Clinical Research Network (NASH CRN) and Liver Imaging Reporting and Data System (LI-RADS) committee.
Our past collaborative efforts have led to the development and dissemination of a technique for quantifying hepatic steatosis. Animal and human data have linked features of the individual triglyceride chains to histopathological findings of NASH such as hepatocyte ballooning. This continuing line of research is now focused on characterizing the types of lipid deposited in the liver and in other fat depots throughout the body.
We collaborate with industry partners on clinical trials in non-alcoholic steatohepatitis (NASH) and other liver diseases. Our role is typically to develop the imaging components of these clinical trials, including liver fat quantification, liver volume, adiposity measures, and liver stiffness by MR elastography. We seek to leverage this platform for the development of novel imaging methods relevant to a clinical trial’s patient population.
We seek to evolve our understanding of the features of liver cancer and improve imaging-based methods for the diagnosis and characterization of liver tumors. Using a deep learning approach, we hope to improve on existing imaging methods and diagnostic algorithms to improve the care of patients with liver cancer.
Intravenous contrast agents play a critical role in body imaging, particularly CT and MRI. With the introduction of novel contrast agents, the precise utility and roles of various agents remain poorly defined. We study the diagnostic applications and safety profiles associated with a variety of available agents.
Key Publications
AI methods can be applied to nearly any problem, but can be rife with challenges. We develop scalable workflow tools to reduce effort and improve repeatability for common, time-consuming tasks, and design the tools for efficient ongoing quality control and validation.
Data Science
Image deidentification is essential to protect sensitive patient data when using radiological images for research. We provide DICOM deidentification services for image metadata and burned-in pixel text for researchers at Duke University.
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Bashir Lab for Liver Imaging Research Diversity and Inclusion Statement
At BaLLIR, diversity, inclusion, and equity are central to our core values and impact on research. Our success depends on varied backgrounds, experiences, and perspectives in order to generate better ideas used to solve complex problems in an ever changing and increasingly diverse world. We strive to advance health equity by including individuals from diverse backgrounds to join clinical research. To achieve this success, it is essential that our community feels safe and accepted, the contributions of all people are respected, and all voices are heard.
Duke University Institutional Statement of Commitment to Diversity and Inclusion: https://inclusive.duke.edu/
