Treffer: A comprehensive investigation of the radiation isocentre spatial variability in linear accelerators: implications for commissioning, QA, and clinical protocols.

Stereotactic ablative radiation therapy and stereotactic radiosurgery (SRS) are modern high precision techniques used for cancer management. Hence, evaluating potential clinical impacts of mischaracterisation of the radiation isocentre (RI) variability at different gantry and collimator angles during commissioning and quality assurance (QA) helps to ensure the robustness of treatment delivery and successful outcomes. This was done using signal edge detection techniques on flattened and flattening filter free (FFF) fields generated by megavoltage (MV) treatment beams. A total of 22,815 MV images of 4 × 16 cm², were captured using an iViewGT™ Perkin Elmer a-Si Electronic Portal Imaging Device at 13 different gantry angles, paired with 13 collimator angles each in 30° intervals. 6 MV, 6 MV FFF, and 18 MV photon treatment modes were used across 8 linacs. The Starshot images were subsequently analysed using custom in-house signal detection software developed in Python. The mean RI variabilities across the entire treatment arc were approximately 0.58 mm, 0.66 mm, and 0.58 mm, for beam energies of 6 MV, 6 MV FFF, and 18 MV respectively, with corresponding standard deviations of 0.18 mm, 0.21 mm, and 0.19 mm, with maximum variabilities occurring at 300°, 0°, and 240° of magnitudes 0.62 mm, 0.71 mm, and 0.62 mm, respectively. Correspondingly, the standard deviations were 0.20 mm, 0.23 mm, and 0.17 mm. The resulting RI variabilities, applied to SRS QA parameters, may breach the 1 mm tolerance. In some clinical scenarios, this may impact treatment plan acceptance with treatment coverage goals outside of acceptable limits. We recommend enhancing commissioning and QA protocols by combining Starshot and Winston–Lutz-style tests to assess the positional deviation of the apparent radiation isocentre from the mechanical isocentre, and the radiation isocentre's maximal variability across a larger range of intermediate angles. This approach helps define reference angles and tailor QA frequency based on individual linac behaviour. [ABSTRACT FROM AUTHOR]

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