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000304436 1001_ $$0P:(DE-He78)adad5911428cc58640dc07d97728edb8$$aHamad, Yasmin$$b0$$eFirst author$$udkfz
000304436 245__ $$aLET measurements in proton and helium-ion beams of therapeutic energies using a silicon pixel detector towards a tool for quality assurance.
000304436 260__ $$aHoboken, NJ$$bWiley$$c2025
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000304436 520__ $$aAs advanced treatment plans increasingly include optimizing both dose and linear energy transfer (LET), there is a growing demand for tools to measure LET in clinical settings. Although various detection systems have been investigated in this pursuit, the scarcity of detectors capable of providing per-ion data for a fast and streamlined verification of LET distributions remains an issue. Silicon pixel detector technology bridges this gap by enabling rapid tracking of single-ion energy deposition.This study proposes a methodology for assessing LET and relative biological effectiveness (RBE) in mixed radiation fields produced by clinical proton and helium ion beams, using a hybrid silicon pixel detector equipped with a Timepix3 chip.The Timepix3 detector was placed behind PMMA slabs of different thicknesses and exposed to initially monoenergetic proton and helium-ion beams. The detector featured a 300 µm-thick silicon sensor operated in partial depletion. Silicon-based LET spectra were derived from single-ion deposited energy across the sensor and subsequently converted to water-equivalent spectra. Track- and dose-averaged LET (LETt and LETd) were calculated from these spectra. LET measurements were used as input to estimate the RBE via the modified microdosimetric kinetic model (mMKM) assuming an (α/β)γ value of 2 Gy. Measurements were compared with simulations performed using the FLUKA Monte Carlo code. Energy deposition spectra, LETt and LETd values were simulated at various depths in PMMA for the radiation fields used, by considering the contribution from the secondary particles generated in the ion interaction processes as well.Energy deposition spectra were validated against Monte Carlo simulations, showing good agreement in both spectral shapes and positions. However, a depth uncertainty of less than 1 mm and other potential differences between measurements and simulations led to deviations, particularly in the distal region of the Bragg curve. Relative differences of LETd between measurements and simulations were within 3% for protons and 10% for helium ions upstream of the Bragg curves. Notably, larger discrepancies were observed in the distal part of the Bragg curve, with maximum relative differences of 7% for protons and 17% for helium ions. Average differences between RBE predictions from measured and simulated LET spectra were within 1% and 6% for protons and helium, respectively. Nevertheless, for both particle types, most measurements agreed with simulations within 1σ experimental uncertainty across the measured depths, with deviations beyond 1σ generally remaining within 3σ.This study demonstrates the performance of silicon pixel detectors with respect to LET measurements and RBE estimation in clinical proton and helium-ion beams. The streamlined and accessible outline of the proposed methodology supports easy implementation into clinical routines, promising a viable and sound quality assurance tool for particle therapy.
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000304436 650_7 $$2Other$$aMonte Carlo simulations
000304436 650_7 $$2Other$$ahelium‐beam radiotherapy
000304436 650_7 $$2Other$$alinear energy transfer
000304436 650_7 $$2Other$$aproton therapy
000304436 650_7 $$2Other$$arelative biological effectiveness
000304436 650_7 $$2Other$$asilicon pixel Timepix3 detector
000304436 650_7 $$0Z4152N8IUI$$2NLM Chemicals$$aSilicon
000304436 650_7 $$0206GF3GB41$$2NLM Chemicals$$aHelium
000304436 650_2 $$2MeSH$$aSilicon
000304436 650_2 $$2MeSH$$aHelium: therapeutic use
000304436 650_2 $$2MeSH$$aLinear Energy Transfer
000304436 650_2 $$2MeSH$$aProton Therapy: instrumentation
000304436 650_2 $$2MeSH$$aQuality Assurance, Health Care
000304436 650_2 $$2MeSH$$aQuality Control
000304436 650_2 $$2MeSH$$aRadiometry: instrumentation
000304436 650_2 $$2MeSH$$aMonte Carlo Method
000304436 650_2 $$2MeSH$$aRelative Biological Effectiveness
000304436 7001_ $$0P:(DE-He78)39752d4eeb3a8d41207248d20d8a51cf$$aSari, Ferisya Kusuma$$b1$$udkfz
000304436 7001_ $$0P:(DE-HGF)0$$aFélix-Bautista, Renato$$b2
000304436 7001_ $$0P:(DE-He78)dfe82ba00edb8b1609794fbe37bd616f$$aMartišíková, Mária$$b3$$udkfz
000304436 7001_ $$aMairani, Andrea$$b4
000304436 7001_ $$0P:(DE-He78)4af90cacc534bcab08c5a70badbb2d5e$$aGehrke, Tim$$b5$$eLast author$$udkfz
000304436 773__ $$0PERI:(DE-600)1466421-5$$a10.1002/mp.18085$$gVol. 52, no. 9, p. e18085$$n9$$pe18085$$tMedical physics$$v52$$x0094-2405$$y2025
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