Physics in medicine and biology最新文献

Neon ion (²⁰Ne) beam radiotherapy was one of the primary particle therapy candidates investigated during the clinical trials beginning in the 1970s at the Lawrence Berkely National Laboratory (LBNL), which shut down in the early 1990s. Currently, therapeutic neon ion beams are available at only one clinical facility worldwide, the National Institutes for Quantum Science and Technology (QST) in Chiba, Japan. Recently, neon ion beams were commissioned at QST Hospital as part of the first clinical multi-ion therapy (MIT) program, which aims to improve clinical outcomes by escalating higher linear energy transfer (LET) radiation in the tumor for treating therapy-resistant disease. With the advancement of high-precision scanning delivery techniques, neon ion treatments in the present day could be delivered more safely and with greater precision compared to the first and only clinical application decades prior at LBNL using passive scattering technology. Despite their promising results, preclinical investigations of neon ions are scarce outside of Japan and further independent studies are needed. Clinically, neon ion therapy may offer benefits in treating certain malignancies by escalating LET in the tumor, but its limited availability and high costs restrict its current use and adoption. Studies have shown that²⁰Ne or multi-ion mixtures (⁴He,¹²C,¹⁶O and/or²⁰Ne) can provide larger degrees of freedom in optimization of dose, LET and relative biological effectiveness, otherwise unattainable with other single ion techniques. Neon ion beams are under investigation in the ongoing MIT clinical trials which will establish their broader applicability. In this review, the technology, physics, radiobiology, and potential clinical applications of neon ion beams are outlined. The status of therapeutic neon ion beams is provided while discussing future research and clinical directions, including technological development of novel particle therapy delivery techniques, such as multi-ion, mini-beam, arc, and ultra-high dose rate.

Objective: The LET trilemma-an inherent conflict between target dose homogeneity, range robustness, and high dose-averaged linear energy transfer (LET_d)-poses a major challenge in treatment optimization. To ensure accurate beam delivery in multi-ion therapy, this study evaluated the effects of range and setup uncertainties on LET_d-optimized treatment plans and explored strategies to overcome this trilemma, framed within the phase I LET_descalation trial for head and neck cancers. Approach: Six head and neck cancer patients representing diverse tumors were selected. Multi-ion therapy plans using carbon-, oxygen-, and neon-ion beams were optimized to achieve a target LET_dof 90 keV/μm (the final LET_dlevel of the phase I trial). These plans were recalculated to incorporate uncertainties arising from stopping power ratio conversion and random daily setup variations across the 16 fractions, and their combined effects on the dose and LET_ddistributions were evaluated. Additionally, to explore strategies to increase plan robustness, five modified plans were evaluated for one patient identified as particularly susceptible to these uncertainties. Main results: Range uncertainty was the dominant contributor to degraded plan quality in multi-ion therapy, substantially outweighing setup uncertainty. A small, centrally located tumor was most susceptible, exhibiting dose inhomogeneity of approximately 11%, while LET_dvariations were approximately 3 keV/μm. The most effective strategy involved replacing the original carbon-oxygen combination with oxygen ions for two beam ports, reducing dose inhomogeneity by more than 7% while maintaining normal tissue sparing adjacent to the target. Significance: Optimization toward achieving higher LET_dmakes treatment plans susceptible to range uncertainty, leading to dose degradation within small, deep-seated tumors. Employing heavier ions is an effective strategy to overcome this challenge, enabling robust target coverage by leveraging their inherently higher LET_dwhile sparing normal tissues. These findings provide a key rationale for ion selection in the design of robust multi-ion therapy.

Objective: To design and validate a single, reconfigurable gamma probe that overcomes the static compromise between spatial resolution and sensitivity in radio-guided surgery, enabling both rapid lesion detection and precise margin delineation. Approach: A dual-layer lead collimator was designed for a LaBr₃(Ce)-SiPM detector. A validated analytical model coupled with a multi-objective genetic algorithm (NSGA-II) was used to explore the theoretical performance limits and identify optimal geometries. A two-phase computational search identified a single, universal geometry that can be intraoperatively switched between a high-sensitivity (HS) mode and a high-resolution (HR) mode by adjusting collimator positions. Main results: The universal design, at a 30 mm distance, achieves a spatial resolution of 6.41 mm FWHM in HR mode and a sensitivity of 1483 cps/MBq in HS mode. The optimization framework identified specialized, distance-specific theoretical designs with resolutions as fine as 3.26 mm FWHM. The underlying detector's energy resolution is sufficient to distinguish between ⁹⁹ᵐTc (140.5 keV) and ¹²³I (159 keV). Significance: This work presents a practical, single-instrument solution that offers surgeons the intraoperative flexibility to prioritize either rapid detection or precise delineation. The developed design methodology provides a robust framework for creating next-generation, application-specific surgical guidance tools. .

Objective.Accurately delineating the visual pathway (VP) is crucial for understanding the human visual system and diagnosing related disorders. Exploring multi-parametric MR imaging data has been identified as an important way to delineate VP. However, due to the complex cross-sequence relationships, existing methods cannot effectively model the complementary information from different MRI sequences. In addition, these existing methods heavily rely on large training data with labels, which is labor-intensive and time-consuming to obtain.Approach.We propose a novel semi-supervised multi-parametric feature decomposition framework for VP delineation. Specifically, a correlation-constrained feature decomposition is designed to handle the complex cross-sequence relationships by capturing the unique characteristics of each MRI sequence and easing the multi-parametric information fusion process. Furthermore, a consistency-based sample enhancement module is developed to address the limited labeled data issue, by generating and promoting meaningful edge information from unlabeled data.Main results.We validate our framework using two public datasets and one in-house multi-shell diffusion MRI dataset. Experimental results demonstrate the superiority of our approach in terms of delineation performance when compared to six state-of-the-art approaches.Significance.Our proposed framework effectively mitigates the challenges of modeling complex cross-sequence relationships and limited labeled data, offering a robust solution for accurate VP delineation. This approach not only enhances the understanding of the human visual system but also holds potential for improving the diagnosis of VP-related disorders.

Objective: Non-contrast cardiac CT (NCCT) offers a low-dose, cost-effective alternative to coronary CT angiography (CCTA) for large-scale coronary artery disease screening. However, automatic segmentation on NCCT is severely hindered by poor vessel visibility and a scarcity of annotated datasets. This study aims to overcome these limitations by developing a method for accurate coronary artery segmentation from NCCT images without requiring manual annotations. Approach. We propose SynCAS (Synthetic-data-driven Coronary Artery Segmentation), a deep learning framework trained entirely on synthetic data. First, we developed a comprehensive generation pipeline to create a diverse, large-scale synthetic NCCT dataset with perfect ground truth, modeling the physics of NCCT imaging. Second, to address the low contrast-to-noise ratio, we introduced an anatomy-informed contrastive learning strategy. Unlike traditional methods, this strategy utilizes voxel-level pseudo-negative samples guided by anatomical priors, enabling the model to effectively distinguish coronary arteries from visually similar background structures and reduce false positives. Main results. The proposed method was evaluated on both a public NCCT dataset and an in-house clinical dataset. Experimental results demonstrate that SynCAS consistently outperforms state-of-the-art unsupervised and domain-adaptation approaches. The model exhibits strong generalization capabilities across different datasets despite being trained without real-world annotations. Significance. SynCAS provides a robust solution for analyzing coronary arteries in non-contrast imaging, potentially facilitating retrospective analysis and large-scale population screening for cardiovascular risk without the radiation dose and contrast agent risks associated with CCTA. Code and model weights will be available at: https://github.com/Advanced-AI-in-Medicine-and-Physics-Lab/SynCAS.git.

Over the past years, we have developed GATE version 10, a major re-implementation of the long-standing Geant4-based Monte Carlo application for particle and radiation transport simulation in medical physics. This release introduces many new features and significant improvements, most notably a Python-based user interface replacing the legacy static input files. The new functionality of GATE version 10 is described in the part 1 companion paper (Sarrutet al2025 arXiv:2507.09842). The development brought significant challenges. In this paper, we present the solutions that we have developed to overcome these challenges. In particular, we present a modular design that robustly manages the core components of a simulation: particle sources, geometry, physics processes, and data acquisition. The architecture consists of integrated C++ and Python codes. This framework allows for the precise, time-aware generation of primary particles, a critical requirement for accurately modeling positron emission tomography, radionuclide therapies, or prompt-gamma timing systems. We present how GATE 10 handles complex Geant4 physics settings while exposing a simple interface to the user. Furthermore, we describe the methodological solutions that facilitate the seamless integration of advanced physics models and variance reduction techniques. The architecture supports sophisticated scoring of physical quantities (such as Linear Energy Transfer and Relative Biological Effectiveness) and is designed for multithreaded execution. The new user interface allows researchers to script complex simulation workflows and directly couple external tools, such as artificial intelligence models for source generation or detector response. By detailing these architectural innovations, we demonstrate how GATE 10 provides a more powerful and flexible tool for research and innovation in medical physics. This paper is not intended to be a developer guide. Its purpose is to share with the research community in-depth explanations of our development effort that made the new GATE 10 possible.

Objective.Treatment planning in proton therapy requires an accurate estimation of stopping power ratio relative to water (SPR) maps. Presently, about 4% of patients submitted to radiotherapy treatments have metallic implants, which are responsible for an incorrect determination of SPRs in prostheses and surrounding regions. This study presents the first application of the proton computed tomography (pCT) technique, able to directly measure SPRs maps, on complex metallic implants.Approach.A homogeneous Ti6Al4V alloy sample, a set of metallic devices used for prostheses and an intra-vertebral titanium alloy implant have been inspected, by means of a prototype pCT system with a 5 × 20 cm²field-of-view (FoV) developed by INFN Firenze (Italy), under a proton beam at Trento Proton Therapy Centre (APSS, Trento, Italy). For comparison, a Multi Layer Ionization Chamber (MLIC) has been used to independently determine the SPR mean value of the Ti6Al4V alloy sample.Main Results.Tomographic reconstructions of all devices and materials have been performed and SPR maps have been obtained. All pCT images and profiles, even of metallic components, are characterized by negligible artifacts. The fine spatial resolution of our pCT system, about 0.7 lp mm^-1, allowed us to resolve details within a millimeter scale. The internal grid of the meshed cage as well as details of the screws' head of the intra-vertebral titanium alloy implant are clearly visible. The SPR of the Ti6Al4V alloy sample measured with pCT, 3.14 ± 0.02, compares well with what was measured by MLIC: 3.17 ± 0.02.Significance.This study presents the first application of the pCT methodology to directly measure SPR maps of complex metal prostheses. The ability of pCT to correctly determine mean SPR values has been experimentally demonstrated. Furthermore, this technique was shown to reconstruct complex metal structures at the millimeter scale with negligible artifacts.

Objective: With every treatment vault being different, the impact of geometrical parameters such as the signal source-to-camera distance on dose proportionality must be evaluated. The aim of this study is to characterize the Cherenkov signal and polarization state as a function of the source-to-camera distance. Our hypothesis is that with increasing distance, the need for angular correction distributions decreases, resulting in acquisition of a polarized Cherenkov signal directly proportional to dose.

Approach: A water tank and a polyvinyltoluene-based plastic scintillator volume were irradiated by a 6 MV beam to respectively produce Cherenkov emissions as well as a control signal. Monte Carlo reference simulations were performed using TOPAS. Acquisitions of the Cherenkov signal were achieved using a cooled CCD camera and a timegated intensified CMOS camera. By fitting a modified Malus Law to the Cherenkov acquisitions, the total Cherenkov signal intensity and its purely polarized component was extracted. Signal source-to-camera distance of 0.5, 1, 2, 3 and 4 m were tested to evaluate this distance's impact on the signal distributions. Projected percent depth dose (PPDD) and projected transverse profiles calculated from the different signal sources were then compared.

Main results: All PPDDs at camera distances of 3 and 4 m agree with Monte Carlo (≤5%) over depths ranging from 1.5 to 16 cm. Cherenkov PPDDs at camera distances of 0.5 and 1 m show significant discrepancies (≥5%) compared to MC because no angular corrections are applied. Over the plateau region of projected transverse profiles, general agreement with MC is achieved. Thirteen of the 17 luminescence-based beam widths show ≤5% differences with MC.

Significance: This study confirms the above-mentioned hypothesis up until the image quality diminishes. For this work's setup, the optimal camera distance for dosimetry using Cherenkov polarized imaging was found to be between 3 and 4 m. .

We present GATE version 10, a major evolution of the open-source Monte Carlo simulation application for medical physics, built on Geant4. This release marks a transformative evolution, featuring a modern Python-based user interface, enhanced multithreading and multiprocessing capabilities, the ability to be embedded as a library within other software, and a streamlined framework for collaborative development. In this Part 1 paper, we outline GATE's position among other Monte Carlo codes, the core principles driving this evolution, and the robust development cycle employed. We also detail the new features and improvements. Part 2 will focus on the architectural innovations and technical challenges. By combining an open, collaborative framework with cutting-edge features, such a Monte Carlo platform supports a wide range of academic and industrial research, solidifying its role as a critical tool for innovation in medical physics.

Objective: To measure beam quality correction factors (kQ) in single-layer scanned proton beams using water calorimetry for three ionization chamber types commonly used in clinical proton dosimetry. Approach. Measurements were performed at two proton therapy centers using clinical proton beams with nominal energies of 150, 220 and 226 MeV, at a reference depth of 4 cm. The kQ-factors were obtained by comparing absorbed dose-to-water determinations from a water calorimeter with ionization chamber readings under identical conditions. Three ionization chamber models were investigated: the IBA FC65-G (cylindrical), PPC05 and PPC40 (plane-parallel). Two independent calorimeter setups were used across three measurement campaigns. Main results. The measured kQ-factors showed strong agreement with current TRS-398 Rev. 1 (2024) recommendations and literature data. For the FC65-G chamber, excellent alignment was observed with previous water calorimetry-based measurements. For the PPC40 chamber, both chambers yielded consistent results within 0.5% of TRS-398 Rev. 1. For the PPC05 chambers, a maximum deviation of 1.4% was observed relative to TRS-398 Rev. 1, and inter-chamber variability was within 0.5%. The use of two calorimeter setups yielded consistent results within 0.2%, supporting their validity. Significance. This study presents new experimental kQ-factors for ionization chambers in single-layer scanned proton beams, contributing to the currently scarce experimental database, providing further validation of the TRS-398 Rev. 1 (2024) recommendations, and supplying benchmark data for future Monte Carlo-based kQ calculations. .