2 research outputs found
Automated Radiotherapy Planning for Patient-Specific Exploration of the Trade-Off Between Tumor Dose Coverage and Predicted Radiation-Induced Toxicity-A Proof of Principle Study for Prostate Cancer
Background: Currently, radiation-oncologists generally evaluate a single treatment plan
for each patient that is possibly adapted by the planner prior to final app
First system for fully-automated multi-criterial treatment planning for a high-magnetic field MR-Linac applied to rectal cancer
Background and purpose: In this study we developed a workflow for fully-automated generation of
deliverable IMRT plans for a 1.5 T MR-Linac (MRL) based on contoured CT scans, and we evaluated
automated MRL planning for rectal cancer.
Methods: The Monte Carlo dose calculation engine used in the clinical MRL TPS (Monaco, Elekta AB,
Stockholm, Sweden), suited for high accuracy dose calculations in a 1.5 T magnetic field, was coupled
to our in-house developed Erasmus-iCycle optimizer. Clinically deliverable plans for 23 rectal cancer
patients were automatically generated in a two-step process, i.e., multi-criterial fluence map optimization with Erasmus-iCycle followed by a conversion into a deliverable IMRT plan in the clinical TPS.
Automatically generated plans (AUTOplans) were compared to plans that were manually generated
with the clinical TPS (MANplans).
Results: With AUTOplanning large reductions in planning time and workload were obtained; 4–6 h
mainly hands-on planning for MANplans vs 1 h of mainly computer computation time for
AUTOplans. For equal target coverage, the bladder and bowel bag Dmean was reduced in the
AUTOplans by 1.3 Gy (6.9%) on average with a maximum reduction of 4.5 Gy (23.8%). Dosimetric measurements at the MRL demonstrated clinically acceptable delivery accuracy for the AUTOplans.
Conclusions: A system for fully automated multi-criterial planning for a 1.5 T MR-Linac was developed
and tested for rectal cancer patients. Automated planning resulted in major reductions in planning
workload and time, while plan quality improved. Negative impact of the high magnetic field on the
dose distributions could be avoided