Develops and validates a PHITS model for a LINAC, indicating strong dosimetric accuracy.
Purpose: This study aimed to develop and validate a Particle and Heavy Ion Transport Code (PHITS) model of a 6 MV Elekta Infinity medical linear accelerator (LINAC) using institutional commissioning data from Lorma Cancer Institute Inc. (LCII), La Union, addressing the limited use of PHITS in modeling such systems. Methods: A simplified geometric model of the LINAC head was constructed in PHITS based on published configurations of the Elekta Infinity LINAC, including photon source, flattening filter, primary collimator, and jaws. The model was simulated under reference dosimetry conditions following the IAEA TRS-398 Code of Practice for Absorbed Dose Determination in External Beam Radiotherapy, using a 40 × 40 × 40 cm³ water phantom and a 10 × 10 cm² field size. Photon transport (T-Track) and dose deposition (T-Deposit) were utilized to generate percentage depth dose (PDD) and beam profiles, which were validated against LCII commissioning data under the same setup through regional dose difference analysis. Results: The simulated percentage depth dose (PDD) showed mean dose differences of 4.42% in the build-up region and 1.07% and 0.78% in the fall-off and tail regions, respectively. Cross-plane beam profiles exhibited 3.21% in the penumbra and 1.83% in the flat region, while in-plane profiles showed 3.23% and 1.45%, respectively. These values fall within accepted tolerances of ±3% in low-gradient regions, with larger deviations permitted in steep-gradient regions such as the build-up and penumbra, as recommended by AAPM TG-53 Quality Assurance for Clinical Radiotherapy Treatment Planning. Conclusion: The PHITS-based model demonstrated strong agreement with commissioning data, with all dose differences within ±3% and ±5% in low- and steep-gradient regions, respectively. Ultimately, the model accurately reproduces the key dosimetric characteristics of a 6 MV Elekta Infinity photon beam, highlighting PHITS as a reliable tool for LINAC modeling, local validation, and potential quality assurance applications.
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Suarez et al. (2026) studied this question.
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