Virtual Clinical Trials: An In-depth Tutorial

Level: Intermediate Length: 4 hours Format: In-Person Lecture Intended Audience: Clinicians, scientists, and administrators from academia, industry and government interested in adopting or gaining further knowledge of VCT methods. Description: In 2014, it was estimated that there were just 450 anatomic phantoms in the world. Today, based on advanced models of breast anatomy, an infinite number of models exist. As such, it is possible to simulate individuals and specific pathologies from the population of all humans with increasingly higher accuracy. This, together with advanced models of image simulation, image processing and image reconstruction, means that we can create arbitrarily large databases of simulated images. At the same time, advances in machine observer methods mean that it is possible to conduct virtual clinical trials (VCT) using the simulated images, together with simulations of medical displays, human optical perception and cognition. The logistics of conducting VCT with thousands of patients is similar to the logistics of organizing the data from clinical trials of similar size. As such, we have developed a standards document outlining methods for conducting VCT, storing VCT results (intermediate and final), and communicating these image data and associate metadata between VCT components. In this course, we will use our experience in conducting large-scale VCT to encourage those new to the field to adopt VCT methods and to aid those already conducting VCT. The course will have applicability to VCT for designing new medical imaging equipment and methods, to use VCT data for prototyping and/or complementing the conduct of real clinical trials, and for preparing VCT data for regulatory approvals of new systems and methods. Learning Outcomes: This course will enable you to: - describe the roles and methods for conducting VCT - identify the necessary constituent software components for conducting VCT - name the standards relevant for conducting VCT, including DICOM, ASME, IEEE, AAPM, etc. - construct and Design examples of VCTs to illustrate there usage - demonstrate existing use cases - explain the underlying statistical considerations for conducting VCT Instructor(s): Andrew D. A. Maidment has 30 years of experience in breast cancer research, with specific training and expertise in development of digital x-ray detectors and 3D breast x-ray imaging. Dr. Maidment has been conducting research into VCT for nearly 20 years, has extensive grant funding in VCTs, and has published extensively in this field. As an Associate Professor in Radiology at the University of Pennsylvania, he has extensive teaching experience. Predrag R. Bakic has more than 20 years experience in breast cancer research, with specific training and expertise in developing and conducting VCT. Dr. Bakic's PhD thesis was on the topic of breast anatomy models for imaging simulation. Bruno Barufaldi received his Ph.D. from the University of Sao Paolo in 2016. For the last 2 years, he has been active in the field of VCT, designing much of the pipeline software used in the OpenVCT suite of software. Event: SPIE Medical Imaging 2020 Course Held: 18 February 2020