Clinical Implementation of Virtual CT for Dose Evaluation Using Raystation: Comparison with In-House Method
Abstract
Purpose
Standard in-house techniques for evaluating anatomical changes during radiation therapy often involve manual contouring, neglecting internal organ motion, deformation, or weight-induced volume loss. These limitations potentially compromise dose precision and decrease clinical throughput. RayStation delivers a commercial platform, employing CBCT-based “Virtual CTs,” to quantify and record dose relative to daily patient anatomy. This investigation establishes an automated, Python-scripted framework using Virtual CTs generated from daily CBCT data for streamlined dose evaluation. We present the clinical validation of Virtual CTs and discuss the integration of these automated scripts into practice.
Methods
We developed an automated script utilizing the RayStation 11B Python API. For 10 patients, Virtual CTs were derived from CBCTs to represent typical institutional anatomical variations. Dose was then recalculated on these Virtual CTs and contrasted with conventional manual evaluation processes. To investigate deformable registration limitations, a separate cohort of 20 breast cancer patients with partial rotation CBCTs was evaluated. Dose distributions were compared against planning CTs using specific PTV metrics (mean, max, D90%, D95%, and D98%). Finally, total workflow durations were measured for both the manual and the automated clinical techniques.
Results
Automated software decreased manual dose assessment time from >60 minutes to roughly 2 minutes. Average and peak dose discrepancies were 0.14% and 1.09%, whereas PTV coverage shifts (D90%, D95%, D98%) stayed under 0.8%. For partial CBCT acquisitions, mean and maximal dose variations remained <1.23%, with coverage deviations falling below 2.6%.
Conclusion
RayStation’s Virtual CT–driven automated system significantly enhanced dose evaluation throughput and precision. This facilitates nearly instantaneous verification while patients remain physically present at the clinic, curtailing wait times and refining clinical judgments. Future phases involve integrating offline adaptive replanning and dose monitoring protocols within daily standard therapeutic practice.