Comparison of different approaches for automatic plan adaptation in MR-guided radiotherapy
Benjamin Tengler,
Germany
MO-0642
Abstract
Comparison of different approaches for automatic plan adaptation in MR-guided radiotherapy
Authors: Benjamin Tengler1, Markus Hagmüller1, Luise A. Künzel2, Daniel Zips3, Daniela Thorwarth1
1University Hospital and Medical Faculty. Eberhard Karls University Tübingen, Department of Radiation Oncology, Section for Biomedical Physics, Tübingen, Germany; 2University Hospital and Medical Faculty. Eberhard Karls University Tübingen, Department of Radiation Oncology, Section for Biomedical Physics , Tübingen, Germany; 3University Hospital and Medical Faculty. Eberhard Karls University Tübingen, Department of Radiation Oncology, Tübingen, Germany
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Purpose or Objective
MR-guided radiotherapy (MRgRT) provides the
opportunity of daily plan adaptation based on information about the
patient’s current anatomy. Automatic MRgRT planning approaches may
be used to realize fast plan optimization during online adaptation.
The aim of this work was to evaluate the differences in terms of
dosimetric quality comparing automatic online plan adaptation
starting from a reference plan to complete re-optimization both based
on the anatomy of the day.
Material and Methods
Clinical data of ten prostate carcinoma patients
treated with online adaptive MRgRT (20 x 3 Gy) at the 1.5 T MR-Linac
were included into this study. Optimization of the MRgRT plans was
carried out by an automated planning approach using a particle swarm
optimization (PSO). For each treatment fraction, two adapted plans
were optimized using (1) a plan re-optimization with the optimal
planning constraints achieved for the reference PSO plan at baseline
and (2) a completely new automatic PSO planning approach to take the
anatomical variations best possible into account. Method 1 consists
of a fast plan optimization exploring a limited search space defined
by a set of plan constraints determined upfront whereas method 2
allows for unlimited exploitation of plan constraints for optimal
adaptation at the cost of increased calculation times.
The daily dose distributions obtained with the two
automatic planning approaches were evaluated by comparing the
relative adherence to a set of clinically relevant dosimetric
criteria (cf. table 1). The significance of the differences was
considered using a t-test at the 5% significance level.
Results
For the ten patients, a total of 154 adaptive
MRgRT fractions were available for evaluation. On average (range)
method 1 fulfilled 73.8% (67.7-79.3%) of
the dosimetric criteria (cf. figure 1). For
method 2, the mean relative adherence to the dosimetric criteria was
74.1% (69.2-79.3%).
The two methods yielded no significant differences.
Conclusion
This study compared automatic online plan
optimization with a set of baseline plan constraints to a complete
re-optimization. Regarding dosimetric plan criteria, no significant
differences between the two approaches were found. Therefore, daily
plan adaptation with a set of pre-defined planning constraints does
not compromise plan quality even though anatomical variations may
occur.