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 human anatomy, an unlimited number of models can be created. 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 learning and model observer methods mean that it is possible to conduct virtual clinical trials (VCT) using simulated images, together with simulations of medical displays, human optical perception and cognition. The logistics of conducting VCTs 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 draft standard outlining methods for conducting VCTs, 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 VCTs to encourage those new to the field to adopt VCT methods and to aid those already conducting VCTs. The course will have applicability to VCTs 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 importance of conducting VCTs - describe the roles and methods for conducting VCTs - identify the necessary constituent software components for conducting VCTs - name the standards relevant for conducting VCTs, including DICOM, ASME, IEEE, AAPM, etc. - explain the underlying statistical considerations for conducting VCTs - illustrate the usage of VCTs through examples 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. Ehsan Samei is a tenured professor and chief imaging physicist at Duke University Health System. As the author of over 300 referred papers, he is passionate about bridging the gap between scientific scholarship and clinical practice through virtual clinical trials and clinically-relevant imaging metrics, such that they could enable optimum quantitative use of imaging, realization of translational research, and clinical processes that are based on evidence. Ehsan Abadi is an assistant professor at Duke University in the departments of Radiology and Electrical & Computer Engineering. His research focuses are on quantitative imaging and optimization, CT imaging, lung diseases, human modeling, and imaging simulation. He actively contributes to developments of human models and scanner-specific simulation platforms of imaging systems Event: SPIE Medical Imaging 2022 Course Held: 22 February 2022