1 CME Credit
Abdominal Radiology, Uro-gynaecological
On-demand Webinar
Algorithmic approach to characterisation of adnexal masses on MRI
Already have an account?

Topics Covered
To jump to a specific chapter, click on the chapter title once the video is playing.
00:00 - Introduction to Characterization of Adnexal Masses on MRI
00:46 - Objectives of MRI Characterization and Initial Considerations
02:00 - Imaging Modalities: Ultrasound vs MRI
03:38 - MRI Protocols for Adnexal Masses
06:09 - Interpretation of Diffusion and Enhancement in MRI
10:02 - Characterization Methodology: Lesion Origin and MRI Features
15:53 - Case Studies and Practical Applications
39:02 - Analysis of Common Adnexal Masses and Differential Diagnosis
47:41 - Specific Tumor Types in Young Patients
51:02 - Advanced MRI Features in Adnexal Mass Characterization
58:06 - Final Thoughts on MRI Use and Case Reviews
Lecturers
Evis Sala
Italy, Rome
Evis Sala is Professor of Radiology and Director of the Radiology Training Program at Università Cattolica del Sacro Cuore, and Chair of Diagnostic Imaging and Radiotherapy at Fondazione Policlinico Universitario Agostino Gemelli IRCCS in Rome. She previously held senior roles at the University of Cambridge, Memorial Sloan Kettering Cancer Center, and Weill Cornell Medical College. Her research focuses on integrating quantitative imaging with multi-omics and AI for cancer characterization. Dr. Sala has received multiple honors, including RSNA Honored Educator Awards, Fellowship of ISMRM, and honorary memberships from RSNA and the Japanese Society of Radiology.
Evis Sala is Professor of Radiology and Director of the Radiology Training Program at Università Cattolica del Sacro Cuore, and Chair of Diagnostic Imaging and Radiotherapy at Fondazione Policlinico Universitario Agostino Gemelli IRCCS in Rome. She previously held senior roles at the University of Cambridge, Memorial Sloan Kettering Cancer Center, and Weill Cornell Medical College. Her research focuses on integrating quantitative imaging with multi-omics and AI for cancer characterization. Dr. Sala has received multiple honors, including RSNA Honored Educator Awards, Fellowship of ISMRM, and honorary memberships from RSNA and the Japanese Society of Radiology.