An Algorithm to Increase Power in Clinical Trials and Automate Radiological Reads

In this webinar, Dr. Roger Gunn presents a domain knowledge based AI algorithm that can quantify the level of amyloid plaques in the human brain using an image based regression of two canonical images that capture non-specific and specific binding of PET amyloid tracers.

The algorithm produces a parameter, amyloid load, that shows increased power over SUVr based methods and its application to automating radiological reads, cross-sectional and longitudinal analysis are presented. Results are presented for the three commonly available amyloid tracers- florbetapir, florbetaben and flutametamol.

Roger Gunn, Ph.D.

Chief Scientific Officer, Neuroscience, Invicro

Roger Gunn is an international expert on imaging for disease understanding and drug development. He has a Ph.D. in Applied Mathematics from Warwick University and has worked across Academia (Imperial College London, Oxford University & McGill University), Industry (GSK & Imanova) and Government Labs (MRC Cyclotron Unit). He has made significant contributions to the development of novel imaging biomarkers, quantitative algorithms and software for a wide range of imaging applications with a focus on the neurosciences. He currently holds professorships at Imperial College London and Oxford University and has 200 publications in the field of imaging.

Webinar Series

An Algorithm to Increase Power in Clinical Trials and Automate Radiological Reads

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