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| Top Lessons from GYN Tumor Board - Part 1 I will discuss lessons learned from the gynecologic oncology tumor board. Melina Pectasides, MD |
| Top Lessons from GYN Tumor Board - Part 2 This session will present lessons learned from gynecologic oncology tumor board. Jeanne M Horowitz, MD |
| MR Innovations Workshop This will be a two part session on ferumoxytol. I will discuss vascular imaging with ferumoxytol, and Dr. Stella Kang from NYU will discuss the cost effectiveness of vascular imaging with ferumoxytol. Jeffrey H Maki, MD, PhD |
| Hepatobiliary Plenary Discuss relevant topics in hepatobiliary pathology. My talk will discuss current immunotherapy guidelines in HCC. Bachir Taouli, MD, MHA |
| Hepatobiliary Plenary - Abbreviated MRI: DCE vs. HBP This is a debate discussing the merits and drawbacks of performing HCC screening using abbreviated MRI with dynamic contrast-enhanced imaging vs. hepatobiliary phase imaging. Mustafa Bashir, MD |
| Are Radiology Journals ready for the AI Revolution? Ali Shah Tejani Dr. Ali Tejani is a diagnostic radiology resident at the University of Texas Southwestern Medical Center, where he founded the Imaging Informatics and Business Intelligence Track (I2BIT). He serves as the Deputy Editor of the Radiology: Artificial Intelligence podcast and member of the journal's Trainee Editorial Board. He is also a member of the RSNA Reporting Informatics Committee and Imaging AI in Practice Demonstration Task Force. His research focuses on understanding bias in AI and integrating natural language processing in practice, among other imaging informatics and AI topics. |
| Cancer AND Pregnancy (workshop): Multidisciplinary approach to Malignancy in Pregnancy Diagnosis and management of PACs are challenging and diagnosis is often delayed as symptoms may overlap with physiologic changes of pregnancy. Management of these patients must balance optimal maternal care with potentially harmful fetal effects. This involves honest, forthright, and sometimes difficult discussions between the care team and the patient throughout the entirety of care. Radiologists play a significant role in timely cancer diagnosis, staging and follow-up during and after pregnancy, accurate determination of gestational age, and in assessing fetal growth and well-being throughout pregnancy. Liina Põder, MD, FSRU Dr. Liina Poder is internationally known as an expert in obstetrical & gynecologic imaging including research instrumental in identifying, defining & refining knowledge about placenta accreta spectrum (PAS) disorders. |
| Incorporating AI in the Radiology curriculum (Workshop) Discussion and workshop on how to train residents and fellows in the use of AI in radiology Garry Gold, MD Stanford Medicine Professor of Radiology and Biomedical Imaging, Chair of Radiology at Stanford University and Fellow of SABI. Ali Shah Tejani Dr. Ali Tejani is a diagnostic radiology resident at the University of Texas Southwestern Medical Center, where he founded the Imaging Informatics and Business Intelligence Track (I2BIT). He serves as the Deputy Editor of the Radiology: Artificial Intelligence podcast and member of the journal's Trainee Editorial Board. He is also a member of the RSNA Reporting Informatics Committee and Imaging AI in Practice Demonstration Task Force. His research focuses on understanding bias in AI and integrating natural language processing in practice, among other imaging informatics and AI topics. |
 | MR Lymphangiography We will review our MR program for the workup and management of patients with lymphedema. Alexander Kagen, MD Dr. Kagen is the Site Chair of Diagnostic, Molecular and Interventional Radiology at Mount Sinai West and Mount Sinai Morningside Hospitals, a position he has held since 2015. He is a recognized authority in the field of Body MRI and Artificial Intelligence, serving on multiple committees, lecturing nationally and internationally, and has multiple peer-reviewed publications and research interests in MR flap planning, MR Lymphangiography and AI/Machine Learning. In addition, Dr. Kagen is a Mount Sinai Innovator and former co-founder and Chief Medical Officer of Nines. Dr. Kagen received his medical degree from the College of Medicine at SUNY Downstate where he also completed his residency, after a medicine internship at Lenox Hill Hospital. He completed a clinical fellowship in Body MRI at Johns Hopkins Hospital in Baltimore, Maryland. |
 | AI tools for clinical and research applications: what’s ready today? The talk will pertain to the clinical application of AI in the world of cardiothoracic radiology. Kiran Batra, MD I am an associate professor at UTSW Medical Center in Department of Radiology. |
| Incorporating AI in the Radiology Curriculum Incorporating AI in the Radiology Curriculum Melina Hosseiny, MD Dr. Hosseiny is a second-year Clinician-Scientist Diagnostic Radiology resident at the University of California San Diego (UCSD). Prior to her Radiology residency, she completed a research fellowship at the University of California Los Angeles (UCLA), where she was the primary investigator for a number of projects focusing on oncologic imaging and artificial intelligence. Dr. Hosseiny received several awards and scholarships from national scientific meetings and radiology societies, including the prestigious RSNA 50K Grant Award for her project on "A Deep Learning-based AI tool for LI-RADS", two SAR Trainee Scholarships, the RSNA Applied Radiology Award 2022, and the ARRS Academic Trainee Award. The results of her works are widely cited and further quoted in scientific media. Dr. Hosseiny serves as a Trainee Editorial Board member for both the RadioGraphics Journal and the Journal of the American College of Radiology (JACR) working closely with Dr. Cooky Menias and Dr. Ruth Carlos. Dr. Hosseiny is the co-vice chair of the Society of Advanced Body Imaging Early Carrier Committee (SABI-ECC), and she also is a committee member of “The Society of Abdominal Radiology" (SAR) Emerging Technologies Commission (ETC) program on the Artificial Intelligence”. Her academic and research interests include abdominal imaging, oncologic imaging, and artificial intelligence. She is passionate about enhancing medical imaging with AI. |
 | Are Radiology Journals Ready for the AI Revolution? (Panel Discussion) A panel discussion on the many facets of AI and how radiology journals may utilize or respond to it. Eric Tamm, MD Eric Tamm is a Professor of Diagnostic Radiology at MD Anderson Cancer Center with academic interests in pancreatic oncology, CT and MR. He is a Fellow of the Society of Advanced Body Imaging (SABI), and of the Society of Abdominal Radiology (SAR). He is also the Editor-in-Chief of the Journal of Computer Assisted Tomography, and a founding co-chair of the Society of Abdominal Radiology’s Disease Focused Panel on Pancreatic Cancer. He has served on committees for multiple societies including the Society of Advanced Body Imaging, Society of Abdominal Radiology, Radiologic Society of North America, and the American Roentgen Ray Society. |
| Updates on Malignant and Premalignant Lesions of Pancreas Provide current updates on genetics and imaging of premalignant and malignant lesions of the pancreas. Srinivasa R Prasad, MD Dr. Prasad is a Professor of Radiology and a board-certified radiologist at MD Anderson Cancer Center. His focus in oncological imaging has included exploring the role of genetics in the pathogenesis of cancers. He has published more than 170 peer-reviewed papers, 13 book chapters, and more than 240 abstracts. He is a dedicated teacher and mentor to trainees. |
| Deep Learning Acceleration in MR, MRI Updates Talk on the basics, current and upcoming role of deep learning image reconstruction in MRI, focussing on abdominal imaging.Barun Bagga, MBBS, MD
Abdominal and Cardiothoracic Radiologist Clinical Assistant Professor, NYU Long Island School of Medicine Director of GI Radiology, NYU Langone Health - Long Island and Long Island Community Hospital |
