Log file based dose reconstruction and accumulation for 4D adaptive pencil beam scanned proton therapy in a clinical treatment planning system: Implementation and proof-of-concept

Background and Purpose
Motion induced uncertainties hamper the clinical implementation of pencil beam scanning proton therapy (PBS-PT). Prospective pre-treatment evaluations only provide multi-scenario predictions without giving a clear conclusion for the actual treatment. Therefore, in this proof-of-concept study we present a methodology for a fraction-wise retrospective 4D dose reconstruction and accumulation aiming at the evaluation of treatment quality during and after treatment.
Material and Methods
We implemented an easy-to-use, script-based 4D dose assessment of PBS-PT for patients with moving tumours in a commercially available treatment planning system. This 4D dose accumulation uses treatment delivery log files and breathing pattern records of each fraction as well as weekly repeated 4D-CT scans acquired during the treatment course. The approach was validated experimentally and was executed for an exemplary data set of a lung cancer patient.
Results
The script-based 4D dose reconstruction and accumulation was implemented successfully, requiring minimal user input and a reasonable processing time (around 10 minutes for a fraction dose assessment). An experimental validation using a dynamic CIRS thorax phantom confirmed the precision of the 4D dose reconstruction methodology. In a proof-of-concept study, the accumulation of 33 reconstructed fraction showed a linear increase of D98 values. Projected treatment course D98 values revealed a CTV under dosage after fraction 25. This loss of target coverage was confirmed in a DVH comparison of the nominal, the projected (after 16 fractions) and the accumulated (after 33 fractions) dose distribution.
Conclusions
The presented method allows for the assessment of the conformity between planned and delivered dose as the treatment course progresses. The implemented approach considers the influence of changing patient anatomy and variations in the breathing pattern. This facilitates treatment quality evaluation and supports decisions regarding plan adaptation. In a next step, this approach will be applied to a larger patient cohort to investigate its capability as 4D quality control and decision support tool for treatment adaptation.