講座名稱：3D Ultrasound for Image-guided Interventions and point-of-care diagnostics

講座人：Aaron Fenster 院士

講座時間：12月14日21:00

地點：騰訊會議直播

講座人介紹：

Dr. Fenster is a Scientist at the Robarts Research Institute, founder and past Director of the Imaging Research Laboratories (IRL) at the Robarts Research Institute. He is a Professor and Chair of the Division of Imaging Sciences of the Department of Medical Imaging at Western University, Canada. In addition, he is the founder and past Director of the interdisciplinary graduate Program in Biomedical Engineering and past Director for the Biomedical Imaging Research Centre at The Western University. In 2007 he became the Director of the Imaging Program at the Ontario Institute for Cancer Research (OICR). In 2010 he became the Founder, Acting CEO and Centre Director of the Centre for Imaging Technology Commercialization (CIMTEC) – a federally funded Centre of Excellence in Commercialization and Research. Currently, he is its CEO. In 2020 he was honoured by being named to the Order of Ontario and in 2022 he was elected to the Royal Society of Canada.

Fenster’s laboratory has been pioneering the development of 3D ultrasound imaging and image-guided mechatronic interventional systems with some successfully translated into clinical use and to companies (14 licenses). Most recently, his lab has developed 3DUS image-guided interventional systems for prostate biopsy and brachytherapy, breast brachytherapy, and focal liver tumor ablation. Successfully translated applications include: 3D transrectal US/MR prostate biopsy, cryosurgery, brachytherapy and breast biopsy, 3DUS applications for carotid imaging for sensitive monitoring of carotid atherosclerosis and quantification of disease burden; and 3DUS imaging of preterm infants’ brains to assess post hemorrhagic ventricle dilation.

Thus far, Fenster's lab has generated 386 peer-reviewed manuscripts, 654 conference proceedings, 5 books, and 42 book chapters, with 53 patents and 14 licenses that have been issued. To date, Dr. Fenster has directly supervised 36 PhD, 26 Masters, and 17 postdoctoral fellows. Over the years, he has received ~$24 Million in funding as a principal investigator from major funding agencies such as CIHR, NCE, NSERC, ORF, and OICR.

講座內容：

Conventional 2D ultrasound (2D US) is used extensively for a wide variety of diagnostic and interventional procedures. However, some procedures require 3D images to allow better appreciation of the anatomy and provide a means for registration with images from other modalities. Thus, the use of 3D US has increased over the past 2 decades with innovations from research laboratories and ultrasound system manufacturers. Some of these systems make use of 3D tracking devices (optical and electromagnetic) to allow free-hand scanning of the anatomy while 2D US images are acquired into a computer together with pose information. These systems have been used for a variety of clinical applications; however, they require additional equipment and control of the environment, making them more expensive and at times complicated to set up. Some ultrasound system manufacturers are supplying 3D US probes, which make use of mechanical scanning of the US transducer inside a probe housing or via a 2D piezoelectric array. These systems are convenient as they are integrated into the US system; however, they are bulky, have a limited field of view, and are limited to the manufacturer’s US system.

Our research has been focused on developing 3D US scanning devices that overcome the limitations of conventional US imaging methods. We have been developing and fabricating various mechanical external motorized fixtures that move a conventional US probe in specific patterns and used them in systems for image-guided prostate biopsy prostate, prostate and gynecologic brachytherapy, and focal liver tumour ablation. As well, we developed 3D US-based system for point of care diagnostic application such as whole breast imaging, carotid plaque quantification, and hand and knee osteoarthritis.

Our approach allows scanning the desired anatomy in a consistent manner, imaging a large volume, integration of any manufacturer’s 2D US probe into our fixtures, and integration of machine learning methods for rapid diagnosis and guidance. This approach provides a means of using US images with any US system with a small additional cost and minimal environmental constraints.

主辦單位：人工智能學院