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@ARTICLE{Hamad:304436,
author = {Y. Hamad$^*$ and F. K. Sari$^*$ and R. Félix-Bautista$^*$
and M. Martišíková$^*$ and A. Mairani and T. Gehrke$^*$},
title = {{LET} measurements in proton and helium-ion beams of
therapeutic energies using a silicon pixel detector towards
a tool for quality assurance.},
journal = {Medical physics},
volume = {52},
number = {9},
issn = {0094-2405},
address = {Hoboken, NJ},
publisher = {Wiley},
reportid = {DKFZ-2025-01849},
pages = {e18085},
year = {2025},
note = {#EA:E040#LA:E040#},
abstract = {As 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.},
keywords = {Silicon / Helium: therapeutic use / Linear Energy Transfer
/ Proton Therapy: instrumentation / Quality Assurance,
Health Care / Quality Control / Radiometry: instrumentation
/ Monte Carlo Method / Relative Biological Effectiveness /
Monte Carlo simulations (Other) / helium‐beam radiotherapy
(Other) / linear energy transfer (Other) / proton therapy
(Other) / relative biological effectiveness (Other) /
silicon pixel Timepix3 detector (Other) / Silicon (NLM
Chemicals) / Helium (NLM Chemicals)},
cin = {E040},
ddc = {610},
cid = {I:(DE-He78)E040-20160331},
pnm = {315 - Bildgebung und Radioonkologie (POF4-315)},
pid = {G:(DE-HGF)POF4-315},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:40905421},
doi = {10.1002/mp.18085},
url = {https://inrepo02.dkfz.de/record/304436},
}