Adapt to Setup (AToS): An on-Line Proton Adaptive Strategy for Proton SBRT
Abstract
Purpose
Proton dose distributions can be very sensitive to setup and anatomical variations. Specifically, back tissue correspondence in posterior beam spine SBRT and changes in lung density or pleural effusion in lung SBRT are scenarios in which plan adaption would be beneficial. To this end, we propose a fast adaptive algorithm called AToS (Adapt To Setup), which is intended to compensate for anatomical changes upstream of the target.
Methods
The energies of individual proton spots were adapted to account for changes in the proton’s range due to anatomical differences. Each spot in the adapted plan was tuned to stop in the same position as the original plan. A dosimetric comparison between the original plan, a verification plan on an QA CT (CT-on-Rail in each treatment session), and an adapted plan on the same QA CT was peformed to assess the performance of this technique. Two spine and two lung cases were used for testing.
Results
AToS adaptation time is ~10 seconds per field in Matlab. The resulting adapted DICOM plan files were imported to Eclipse for dose calculation. In spine case #1, the verification plan was considered unacceptable due to excess back tissue. The original plan had CTV_high D95%=100.0% and cord D0.1cc=26.4 Gy, while the verification plan showed inferior CTV_high coverage (D95%=96.2%) and cord sparing (D0.1cc=29.8Gy). The adapted plan restored CTV_high coverage (D95%=100.7%) and cord sparing (D0.1cc=27.01Gy). In lung case #1, the verification plan showed a change in pleural effusion. The original plan had a CTV D95%=99.2%, while the verification plan had a CTV D95%=79.0% . The adapted plan boosted the coverage back to CTV D95%=94.7%.
Conclusion
Dosimetric studies demonstrated the effectiveness of a novel and efficient adaptation strategy for proton SBRT, allowing for reduced patient setup times, higher quality treatments, and a reduction of offline adaptive resources.