Role of Artificial Intelligence in Theranostics: Toward Routine Personalized Radiopharmaceutical Therapies
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Date
2021-10
Authors
Brosch-Lenz, Julia
Yousefirizi, Fereshteh
Zukotynski, Katherine
Beauregard, Jean-Mathieu
Gaudet, Vincent C.
Saboury, Babak
Rahmim, Arman
Uribe, Carlos F.
Advisor
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
KEY POINTS
AI has shown promising applications in quantitative imaging required for dosimetry.
Segmentation of organs and tumors, the most time consuming task in the dosimetry workflow, can
be automated using AI.
Using the theranostic approach, AI models that predict absorbed dose and therapy outcomes
might play a key role in personalizing RPTs.
AI has significant potential to improve accuracy and reduce times for routine implementation of patient-specific dosimetry in RPTs.
Description
The final publication is available at Elsevier via https://doi.org/10.1016/j.cpet.2021.06.002. © 2021. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
theranostics, radiopharmaceutical therapies, dosimetry, artificial intelligence, outcome prediction, segmentation, registration, quantitative imaging