Members of the Department of Radiation Oncology have recently returned from 59th annual meeting of the American Association for Physics in Medicine (AAPM) in Denver, CO, where faculty and staff were presenters or senior authors on over 50 abstracts about current research and clinical innovation.
Continuing a trend from previous years, 35 of the accepted abstracts from Washington University were designated as oral presentations, and 20 as posters (14 ePosters, 6 general posters), an impressive showing at a conference with over 2000 submitted abstracts, fewer than half of which are assigned for oral presentation. In addition, many faculty members led panel groups or participated as instructors for continuing education courses. “We are extremely proud of all accomplishments and recognition at the AAPM annual meeting. The statistics for the Washington University proffered and invited presentations not only show the depth and breadth of our work, but more importantly, the significance and impact that we have in radiation oncology on a national scale,” said Sasa Mutic, PhD, Vice-Chair of Medical Physics and Clinical Strategy, and Director of the Medical Physics Division.
This year’s faculty recognitions include the Farrington-Daniels Award received by Jeffrey Williamson, PhD (read more), and S. Murty Goddu, PhD (top image), who was elected as a fellow of the American Association of Physicists in Medicine. The honor of fellowship is presented to members of the AAPM who are nominated by their peers on the basis of their leadership and dedication to education, research, and clinical service. Tiezhi Zhang, PhD, received a Best in Physics (Therapy) award for his abstract, “A Highly Efficient Linac Design Optimized for 4pi Radiotherapy,” which discusses his recent research into the potential for designing a linear accelerator that can deliver non-coplanar beams both continuously or intermittently. Dao Lam, PhD, a clinical physics assistant, won 3rd place in the AAPM Thoracic Auto-Segmentation Challenge for work he has done developing a machine learning model for CT datasets, a project undertaken during his time as a post-doctoral research associate working with Tianyu Zhao, PhD.