Implementation of an AI-Driven Workflow for Daily Dose Reconstruction in Prostate Cancer Radiotherapy
Jessica Prunaretty, Tom Baudouin, Olivier Riou, David Azria, Pascal Fenoglietto · 2026
Read Implementation of an AI-Driven Workflow for Daily Dose Reconstruction in Prostate Cancer Radiotherapy by Jessica Prunaretty, Tom Baudouin, Olivier Riou, David Azria, Pascal Fenoglietto (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13255936.txt.
Description
Jessica Prunaretty and co-authors report a 2026 implementation study of an artificial intelligence workflow that reconstructs the radiation dose prostate cancer patients actually receive each day. Body shape shifts between sessions, so delivered dose can drift from the plan. Their software builds synthetic CT images from daily scans, outlines organs automatically, and recalculates dose.
The team analyzed 800 treatment sessions from 20 patients. Dose to the target volumes stayed consistent with the plan overall. Some sessions, though, delivered higher-than-expected dose to the rectum or bladder. In two patients, the excess traced back to the software misdrawing the bladder's outline. The authors support AI monitoring as a safety net while insisting that expert eyes still verify its work before anyone acts on it.
Catalog record
| CREATOR | Jessica Prunaretty, Tom Baudouin, Olivier Riou, David Azria, Pascal Fenoglietto |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 23 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |