ESTRO 2025 - Abstract Book

S3648

Physics - Quality assurance and auditing

ESTRO 2025

patient safety and clinical efficacy. Future developments of this work will include integrating dosimetric data with image quality metrics for a more comprehensive analysis.

Keywords: CBCT, imaging dose measurements, simulation

References: [1] DIN 6868-161, Image quality assurance in diagnostic X-ray departments – Part 161: Acceptance testing of dental radiographic equipment for digital cone-beam computed tomography, https://dx.doi.org/10.31030/3290546 [2] de Las Heras Gala H, Torresin A, Dasu A, et al, Quality control in cone-beam computed tomography (CBCT) EFOMP ESTRO-IAEA protocol (summary report). Phys Med. 2017 Jul;39:67-72. doi: 10.1016/j.ejmp.2017.05.069. Epub 2017 Jun 9. PMID: 28602688. [3] Rampado O, Giglioli FR, Rossetti V, et al, Evaluation of various approaches for assessing dose indicators and patient organ doses resulting from radiotherapy cone-beam CT. Med Phys. 2016 May;43(5):2515. doi: 10.1118/1.4947129. PMID: 27147362.

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Digital Poster Experiences with automating LINAC QC field delivery with the Elekta iCOM interface in Python Andrew Blackmore 1 , Ruben O Farias 2 1 Medical Physics, GenesisCare, Portsmouth, United Kingdom. 2 Medical Physics, GenesisCare, Chelmsford, United Kingdom Purpose/Objective: Radiotherapy quality control (QC) tasks typically include the delivery of a standardised set of fields, often repetitive with incremental parameter changes (1). Routine tests such as absolute dose output, monitor unit and dose rate linearity, field size verification, and flatness and symmetry at differing gantry angles are prime targets for QC field delivery automation. The clinical R&V system can be used for these tasks, but adds considerable administration overhead, as well as exhibiting reduced performance over time as QC patients build up a detailed delivery history. We present our experience of using an in-house software tool developed in Python to automate the delivery of these tests and reduce inter-operator variations, increase repeatability, and create a simpler, more efficient QC workflow. Material/Methods: Elekta’s iCOM communication application programming interface (API) (2) can be utilised to provide the LINAC with delivery instructions (iCom Fx) and monitor prescribed, set, and run parameters (iCom Vx). Using Ctypes (3), a C library wrapper, we accessed this API in Python. We developed an application known as “PyiCOM” which can send QC fields to the LINAC whilst it is in clinical receive prescription mode. PyiCOM can send single fields or a series of fields akin to a playlist, known as “sequences”. It monitors the LINAC’s state using iCom Vx, and once the field is delivered, sends and confirms the next field to the LINAC using iCom Fx. We conducted QC tests manually using service mode, and then repeated them using PyiCOM. We timed these activities to determine if there was an efficiency gain by automating the deliveries.