Save the Date: Radiology Research Day! 2022
Save the date for Thursday, March 10, where we’ll have a day of Radiology research fun! Plan to attend the Frontiers of Radiology Research Grand Rounds from 12-1 p.m. followed by Radiology Research Day! 2022 from 2-5 p.m. featuring presentations by our trainees.
Frontiers of Radiology Research Grand Rounds
When: Thursday, March 10, from 12-1 p.m.
Who: Matthew Lungren, M.D., Associate Physician, Department of Radiology at UCSF, Associate Fellow at Stanford Center for Artificial Intelligence in Medicine and Imaging and Adjunct at the Department of Radiology, Duke University.
Abstract: Rapidly expanding Clinical AI applications worldwide have the potential to impact to all areas of medical practice. Medical imaging applications constitute a vast majority of approved clinical AI applications with more than 150 to date. Though healthcare systems are eager to adopt AI solutions, fundamental questions remain regarding governance, decisions on which model to choose, who should make the decision, and more. Further, after deployment, more questions arise: Is the model still working as expected?, What is causing the change?, Is it time to intervene? This talk will cover the latest thinking on medical imaging AI governance, strategies and pitfalls, as well as new research in the area of how to monitor input data and track model performance of models after deployment to ensure they remain safe and effective for our patients
Join via Zoom at https://washington.zoom.us/j/96993522608
If you have any questions, contact Nate Bell at nobell@uw.edu.
Radiology Research Day! 2022
When: Thursday, March 10 from 2-5 p.m.
Join via Zoom at https://washington.zoom.us/j/93249684342
Schedule:
Session 1, moderated by Paul Kinahan
| Time | Presenter | Title |
| 2:00-2:05 pm | Dushyant Sahani | Welcome |
| 2:05-2:20 pm | Guest Speaker | Matt Lungren, MD, Principal for Clinical AI/ML at Amazon Web Services. Affiliate Professor of Radiology UCSF, Duke, Stanford |
| 2:20-2:30 pm | Yun An Chen | Application of Ultrafast MRI to Improve Breast MRI Performance in a Clinical Setting |
| 2:30-2:40 pm | Parisa Forouzan | Multitask learning radiomics on longitudinal imaging to predict survival outcomes following risk-adaptive chemoradiation for non-small cell lung cancer |
| 2:40-2:50 pm | Kara Fitzgerald | One click away: Improving interventional radiology patient educational materials |
| 2:50-3:00 pm | Xin Wang | Bayesian intrinsic groupwise registration via explicit hierarchical disentanglement |
Session 2, moderated by Habib Rahbar
| Time | Presenter | Title |
| 3:05-3:15 pm | Shamus Moran | Should Radiology Residency Interviews Remain Virtual? Results of a Multi-institutional Survey Inform the Debate |
| 3:15-3:25 pm | Avanti Gulhane | [68Ga]-PSMA-11 can clarify equivocal lesions on conventional imaging and change management decisions among men with previously treated prostate cancer |
| 3:25-3:35 pm | Anum Kazerouni | Identification of pre-treatment tumor habitats for the prediction of neoadjuvant therapy response in triple negative breast cancer |
| 3:35-3:45 pm | Yin Guo | Multi-planar, multi-contrast and multi-time point analysis tool (MOCHA) for intracranial vessel wall characterization |
| 3:45-3:55 pm | Cody Rissman | Techniques in educational procedural phantom design and development. |
Session 3, moderated by Karen Ordovas
| Time | Presenter | Title |
| 4:00-4:10 pm | Lisa Johnson | Accuracy of Artificial Intelligence-Based Breast Cancer Risk Prediction Models versus Clinical Risk Models in Women Undergoing Screening Mammography |
| 4:10-4:20 pm | Wesley Surento | Association of Fibroglandular Tissue ADC features on Diffusion-weighted MRI with Breast Cancer Risk |
| 4:20-4:30 pm | Kaiyu Zhang | Can blood flow and artery patency alterations in medium-to-large arteries predict alteration in cognitive function? |
| 4:30-4:40 pm | Janis Lee | Do-It-Yourself Business Intelligence for the Radiologist-Lessons Learned From 10-Year Trends in an Abdominal Imaging Division at a Tertiary Medical Center |
| 4:40-4:50 pm | Charlie Davis | Deep Learning Classification of Spinal Radiograph Sidedness |
| 4:50-5:00 pm | Dushyant Sahani | Closing |