Evidence map›Paper›PMID 42223107›Full record

ArticleJournal of applied clinical medical physics2026

Experimental verification of the proton range using heterogeneous animal tissue.

Andrew J Boria, Chia-Ho Hua, Thomas E Merchant, Chin-Cheng Chen

Abstract read
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Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Andrew J BoriaDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
Chia-Ho HuaDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
Thomas E MerchantDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.
Chin-Cheng ChenDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProton beam therapy offers comparable tumor control to conventional photon therapy while reducing radiation-related toxicity due to its finite range and minimal exit dose beyond the Bragg peak. However, the accuracy of proton dose delivery is highly dependent on precise knowledge of tissue stopping power along the beam path. Small deviations in tissue composition or density can result in clinically meaningful proton range errors, potentially compromising target coverage and normal tissue sparing. A primary contributor to this uncertainty is the conversion of computed tomography (CT) Hounsfield Units (HU) to relative stopping power using a bilinear calibration curve, which provides only an approximation of patient tissue properties. Although robustness optimization strategies in modern spot-scanning proton therapy help mitigate the dosimetric impact of range uncertainty, uncertainties in HU-to-stopping-power calibration remain a fundamental limitation of CT-based proton treatment planning. Consequently, there is an ongoing need for practical, efficient methods to verify and validate bilinear calibration curves under clinical conditions, ensuring accurate modeling of proton range and distal dose falloff while maintaining compatibility with routine quality assurance workflows. PURPOSE: To present an end-to-end test for verifying proton range calculations derived from a recently established CT bilinear calibration curve, using animal tissues and standard QA tools. This study provides a robust framework for preclinical verification of proton dose calculations in complex, heterogeneous tissues and supports the safe delivery of proton therapy.

methodsA CT calibration curve (mass density vs. Hounsfield units) was generated for the RayStation Treatment Planning System 2023B (RaySearch Laboratories, Stockholm, Sweden) using a stoichiometric method. A 20×20×10 cm

resultsMeasured and calculated range parameters showed excellent agreement across all tissue configurations. Regarding R80, for the first three scenarios, percentage differences were noticeably minimal: 0.24% (MC) and 0.16% (PBCS) for a water-equivalent thickness (WET) of 18.3 cm (muscle/adipose); 0.47% (MC) and 0.47% (PBCS) for 10.7 cm (muscle/adipose) plus 3.5 cm (bone); and 0.65% (MC) and 0.56% (PBCS) for 9.4 cm (muscle/adipose) plus 4.7 cm (bone). Even in the most challenging configuration, with 3 cm of lateral heterogeneity (bone intersecting muscle+adipose) plus 14.3 cm of muscle/adipose, differences remained low at 1.21% (MC) and 1.08% (PBCS).

conclusionsThis end-to-end method provides an effective approach for verifying proton range calculations in heterogeneous tissues, supporting accurate and robust treatment planning. This approach is especially valuable when implementing proton treatment planning systems, providing increased confidence in the reliability of proton therapy delivery.

Indexed as

Organs at RiskPhantoms, ImagingProton TherapyQuality Assurance, Health CareRadiotherapy Planning, Computer-AssistedAlgorithmsAnimalsCalibrationHumansImage Processing, Computer-AssistedMonte Carlo MethodRadiotherapy DosageTomography, X-Ray Computedanimal tissueprotonproton rangeradiation oncologyradiotherapyrange uncertainty

Identifiers

PMID42223107
PMCPMC13240389

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.