On the Use of Artificial Intelligence for Dosimetry of Radiopharmaceutical Therapies.
| Autor: | Brosch-Lenz JF; Department of Nuclear Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany., Delker A; Department of Nuclear Medicine, LMU University Hospital, Munich, Germany., Schmidt F; Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Tuebingen, Germany.; Department of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Tuebingen, Germany., Tran-Gia J; Department of Nuclear Medicine, University Hospital Wuerzburg, Wuerzburg, Germany. |
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| Jazyk: | angličtina |
| Zdroj: | Nuklearmedizin. Nuclear medicine [Nuklearmedizin] 2023 Dec; Vol. 62 (6), pp. 379-388. Date of Electronic Publication: 2023 Oct 12. |
| DOI: | 10.1055/a-2179-6872 |
| Abstrakt: | Routine clinical dosimetry along with radiopharmaceutical therapies is key for future treatment personalization. However, dosimetry is considered complex and time-consuming with various challenges amongst the required steps within the dosimetry workflow. The general workflow for image-based dosimetry consists of quantitative imaging, the segmentation of organs and tumors, fitting of the time-activity-curves, and the conversion to absorbed dose. This work reviews the potential and advantages of the use of artificial intelligence to improve speed and accuracy of every single step of the dosimetry workflow. Competing Interests: The authors declare that they have no conflict of interest. (Thieme. All rights reserved.) |
| Databáze: | MEDLINE |
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