Radiotherapy using diagnostic computed tomography scans: A phantom-based end-to-end evaluation

Abstract

Palliative patients receiving radiotherapy often experience significant pain. Nevertheless, they must be transported for a planning computed tomography (CT) scan and endure additional waiting times because treatment planning is time-consuming. New artificial intelligence (AI)-assisted radiotherapy devices enable simplified workflows. Using cone-beam CT data, an adaptive treatment plan based on the current patient anatomy can be generated within minutes. This study examines how technical innovations can shorten radiation treatment planning using diagnostic images instead of planning CT (pCT) scans. The entire treatment planning chain was evaluated using an Alderson phantom in an end-to-end test with dose measurements for an AI-supported adaptive workflow. Different diagnostic CT acquisitions were used, and the resulting dose calculations were compared with those obtained from a pCT calibrated for radiotherapy. In Report 24, the International Commission on Radiation Units and Measurements (ICRU) specifies a tolerance for radiotherapy dose delivery of ±5% relative to the prescribed dose. To evaluate if an adaptive workflow with diagnostic images on the Varian’s Ethos system (v1.1) meets these requirements, ionization chamber measurements in a phantom were compared to planned doses. Comparison of the results showed that the requirements of ICRU Report 24 were met. When diagnostic CT images were used instead of a dedicated treatment pCT, increased dose deviations of up to 2% were observed, although these remained within the ICRU tolerance. The end-to-end test presented here provides a practical approach to assessing the impact of using diagnostic CT data in adaptive treatment planning. The findings indicate that the observed dose deviations remain within the 5% limit defined by ICRU Report 24.

Keywords

End-to-end study / Ethos / Adaptive radiotherapy / Simulation-free radiation

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