IMAGING AT THE SPEED OF LIGHT – RECONSTRUCTION-FREE RADIONUCLIDE IMAGING

Positron emission tomography (PET) is a widely used medical imaging technique, and like many other tomographic imaging modalities, relies on an image reconstruction step to produce cross-sectional images. Detection and localization of the back-to-back annihilation photons produced by positron-electron annihilation defines the trajectories of these photons, which when combined with tomographic reconstruction algorithms, permits recovery of the spatial distribution of positron-emitting radionuclides.  Time-of-flight information, typically at the level of 200-400 ps in modern PET systems is used to constrain the reconstruction process. Once the time-of-flight resolution is improved by an order of magnitude to ~30 ps, a new regime is encountered where radioactive decay events can be directly localized without the need for tomographic reconstruction. In this presentation we show how prompt Cherenkov luminescence, photodetectors with very fast single photon response times, and deep-learning based timing pickoff algorithms are combined in an ultra-fast radiation detector to achieve a timing resolution of 32 ps, localizing positron-electron annihilation sites to 4.8 mm.  We also show this is sufficient to directly generate a cross-sectional image of positron-emitting radiotracers.

Simon R. Cherry, Ph.D. received his B.Sc.(Hons) in Physics with Astronomy from University College London and a Ph.D. in Medical Physics from the Institute of Cancer Research, University of London. He is currently Professor in the Departments of Biomedical Engineering and Radiology at the University of California, Davis. Dr. Cherry’s research interests focus on the development and application of biomedical imaging systems. Dr. Cherry is a fellow of six professional societies and served as Editor-in-Chief of the journal Physics in Medicine and Biology from 2011-2020. Dr. Cherry was elected as a member of the National Academy of Engineering in 2016 and to the National Academy of Inventors in 2017.

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Meeting ID 924 8593 4875