Physics in medicine and biology最新文献

Objective: Bismuth germanate (BGO) has regained attention as a promising material for hybrid Cherenkov/scintillation time-of-flight positron emission tomography (TOF-PET). While excellent timing performance has been demonstrated in single-crystal studies using prompt Cherenkov photons, practical pixelated detector modules introduce appreciable inter-crystal scattering (InterCS) events that can degrade timing accuracy. The objective of this work was to experimentally investigate the impact ofInterCSon Cherenkov-based timing in pixelated BGO detectors and to identify optimal timestamp selection strategies. Approach: A dual-pixel BGO detector was constructed and coupled to a segmented SiPM readout to enable spatially resolved energy and timing measurements. Events were classified into full-energy deposition (FED; primary crystal 511 keV absorption),InterCS, and penetration categories using energy-weighted positioning. This experimental classification was validated using GATE simulations, which further revealed that intra-crystal scattering (IntraCS) accounted for more than 25% of the events experimentally classified asFED. Multiple timestamp selection strategies were evaluated, and prompt photon statistics were quantified by integrating the first 1 ns of the timing waveform. Main results: ForInterCSevents, selecting the earlier of the two timestamps yielded a coincidence timing resolution of 221 ps FWHM (831 ps FWTM) measured in coincidence with a LYSO:(Ce, Mg) reference detector, compared to 184 ps FWHM (603 ps FWTM) forFEDevents. Energy-based timestamp selection was found to be suboptimal. Prompt photon analysis showed a measurable reduction in early photon yield forInterCSevents, with an average of 4.73 detected photons in the first 1 ns, compared to 5.76 forFEDevents. Significance: These results demonstrate that inter-crystal scattering introduces systematic timing degradation in pixelated BGO Cherenkov TOF-PET detectors through energy redistribution and reduced prompt photon statistics. The findings highlight the necessity of time-aware, per-pixel timestamp selection strategies to preserve optimal timing performance in realistic BGO-based TOF-PET systems operating in the presence of Compton scattering. .

Objective.Non-contrast cardiac computed tomography (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 (CAS) from NCCT images without requiring manual annotations.Approach.We propose synthetic-data-driven CAS(SynCAS), 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.

Objective. Fast and precise delivery of ion-beam therapy is essential for improving clinical throughput and intrafractional motion management, yet synchrotron-based systems require multiple energy layers for depth dose coverage, resulting in delays on the order of minutes. To eliminate energy layer switching times, a fast Monte Carlo (MC)-based workflow for patient-specific 3D range modulators was developed to enable monoenergetic, conformal carbon irradiation at clinically viable speeds. To mirror realistic clinical use, the dosimetric impact of setup and RM geometry deviations from simulated models were assessed.Approach. The workflow begins with spot extraction from clinical intensity modulated particle therapy (IMPT) plans, followed by RM geometry optimization, fast MC dose verification using MonteRay, and 3D printing final geometries. Experimental validations were performed for spread-out Bragg peaks (SOBPs) in water, and two targets in an anthropomorphic head phantom: (1) in a homogeneous brain region and (2) across a heterogeneous bone-soft tissue interface. Robustness against realistic setup and printing errors were assessed in the heterogeneous case.Main results. Each RM geometry was optimized in under one minute and the RM-based plans achieved dose distributions comparable to IMPT with similar target coverage and homogeneity. Simulated and measured depth dose profiles for SOBP plans agreed within 1.2% local deviation in the target. In the head phantom, measured 2D dose maps achieved local gamma pass rates >99% (2%/2 mm, 10% threshold) in both uniform and anatomically complex settings. Plans were robust to setup deviations up to 1 mm, and manufacturing deviations up to 100µm.Significance. This rapid, clinically feasible workflow enables conformal, monoenergetic carbon ion delivery with dosimetric quality comparable to IMPT even in heterogenous scenarios. The substantially reduced treatment delivery time facilitates motion mitigation and higher patient throughput, and may also provide a technical basis for exploring FLASH regimes in synchrotron-based ion beam facilities.

Objective.Barium and iodinated contrast media are ubiquitous with upper gastrointestinal (UGI) series examinations performed on paediatric patients. The present study quantifies the impact of contrast media on organ absorbed and detriment-weighted doses for UGI examinations.Approach.A paediatric radiologist and a medical physicist created reference imaging fields for four complete UGI series examinations encompassing the newborn and 1-year-old female for both normal and abnormal disease states. Monte Carlo radiation transport simulations were performed for these four cases, with and without contrast media, using the international commission on radiological protection's voxel-based reference computational phantoms.Main results.Estimates of detriment-weighted dose and absorbed doses to the colon, heart wall, kidneys, lungs, small intestine wall, spleen, stomach wall, thymus, thyroid, and remainder tissues are reported. For fields with contrast media the organ absorbed doses and detriment-weighted dose decreased by up to 50% and 26%, respectively, with the dose for the complete examination, i.e. not per field, decreasing by up to 26% for organs impacted by the presence of contrast media.Significance.Overall, relative doses were shown to decrease for simulations that included contrast media due to selective absorption of the x-ray beam by the contrast media. This study, however, did not investigate the effects of the automatic brightness control which could result in organ absorbed doses increasing due to compensation by the fluoroscopy machine when contrast media is present in the field.

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. ThekQ-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 measuredkQ-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 experimentalkQ-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-basedkQcalculations.

Objective.High-energy proton irradiation of²³²Th produces both²²⁵Ac and its precursor²²⁵Ra, the latter being underexplored despite its potential applicability at relevant facilities. This study aims to provide a theoretical basis for²³²Th-based²²⁵Ra production by modeling the associated yields and radioisotopic impurity levels.Approach.Production yields of²²⁵Ra and levels of²²⁸Ra impurity were calculated using Monte Carlo simulations for proton energies of 100-800 MeV, total²³²Th target thicknesses of 0.125-8 mm, and an irradiation time of 15 d. A theoretical model was developed for predicting the cumulative yield of²²⁵Ac eluates from a²²⁵Ra yield. The levels of²²⁸Ra-derived²²⁸Ac impurity in²²⁵Ac eluates and the postelution decay times required to suppress²²⁸Ac to acceptable thresholds were modeled and computed.Main results.The calculated²²⁵Ra yields at the end of bombardment for a 15 d irradiation ranged from 2.3 ± 0.3 MBq µA^-1at 100 MeV to 563.1 ± 12.3 MBq µA^-1at 700 MeV. Increases in²²⁵Ra yield were most pronounced when the proton energy was raised from 100 to 200 MeV, with diminishing returns at higher energies. The cumulative yield of²²⁵Ac eluates was about 29.1% of a²²⁵Ra yield under combined conditions of hypothetical and empirical settings. Postelution times of at least 25.1-30.1 h should be allowed to reduce²²⁸Ac impurity levels to below 0.1%.Significance.The developed models provide a quantitative basis for evaluating and optimizing²²⁵Ra production via proton irradiation of²³²Th. This study quantitatively predicted the presence of²²⁸Ac in²²⁵Ac eluates under various conditions and showed how²²⁸Ac can be suppressed by introducing minimal postelution decay times.

A comprehensive understanding of the energy-dependent stochastic risks associated with neutron exposure is crucial to develop robust radioprotection systems. However, the scarcity of experimental data presents significant challenges in this domain. Track-structure Monte Carlo (TSMC) simulations with DNA models have demonstrated their potential to further our fundamental understanding of neutron-induced stochastic risks. To date, most TSMC studies on the relative biological effectiveness (RBE) of neutrons have focused on various types of DNA damage clusters defined using base pair distances. In this study, we extend these methodologies by incorporating the simulation of non-homologous end joining DNA repair in order to evaluate the RBE of neutrons for misrepairs. To achieve this, we adapted our previously published Monte Carlo DNA damage simulation pipeline, which combines condensed-history and TSMC methods, to support the standard DNA damage data format. This adaptation enabled seamless integration of neutron-induced DNA damage results with the DNA mechanistic repair simulator toolkit. Additionally, we developed a clustering algorithm that reproduces pre-repair endpoints studied in prior works, as well as novel damage clusters based on Euclidean distances. The neutron RBE for misrepairs obtained in this study exhibits a qualitatively similar shape as the RBE obtained for previously reported pre-repair endpoints. However, it peaks higher, reaching a maximum RBE value of 23(1) at a neutron energy of 0.5 MeV. Furthermore, we found that misrepair outcomes were better reproduced using the pre-repair endpoint defined with the Euclidean distance between double-strand breaks rather than with previously published pre-repair endpoints based on base-pair distances. The optimal maximal Euclidean distances were 18 nm for 0.5 MeV neutrons and 60 nm for 250 keV photons. Although this may indicate that Euclidean-distance-based clustering more accurately reflects the DNA damage configurations that lead to misrepairs, the fact that neutrons and photons require different distances raises doubts on whether a single, universal pre-repair endpoint can used as a stand-in for larger-scale aberrations across all radiation qualities.

Objective.ultra-high dose-per-pulse (UHDP) dosimetry remains a key challenge in FLASH radiotherapy. Conventional ionization chambers (ICs) experience large general recombination losses under UHDP due to the high charge densities that are enhanced by severe electric field perturbation. A novel IC design, the ALLS chamber, has been proposed to overcome these limitations by using a low-pressure noble gas, eliminating ion recombination and enabling an analytical description of charge collection up to 40 Gy/pulse with argon at 1 hPa pressure as active medium. However, designing such an IC requires meeting both dosimetric and mechanical constraints for low-pressure operation. Since the actual requirements for FLASH dosimetry involve dose per pulse up to 10 Gy, pressures in range from 1 hPa up to 100 hPa could be applied.Approach.To explore possible configurations in terms of filling gas, pressure and bias electric field to measure a certain dose per pulse, a Python-based numerical simulation was developed to model charge transport in noble gases. The IC response was evaluated in terms of charge collection efficiency (CCE) by varying the dose per pulse, the bias field, the filling gas and its pressure. The aim is to explore suitable experimental conditions in which the response of the IC is stable for a given range of dose per pulse.Main results.Simulations identified helium and nitrogen as best candidates to be used as filling gas of an ALLS-like IC, capable of measuring up to 15 Gy/pulse at 50 and 10 hPa, respectively, while keeping the relative deviations of CCE respect to unity below 1%.Significance.These results support the feasibility of designing ICs for UHDP beams using moderate depressurization, offering a promising path toward the realization of robust, accurate detectors for FLASH reference dosimetry.

Objective: Develop a spatially resolved probabilistic framework that explicitly models localization uncer- tainty to map along-core tissue-class sampling probabilities Pi(z) for MR-informed, US-guided transperineal prostate biopsies, yielding millimetre-scale DIL-sampling descriptors for planning, quality assurance, and biology-related research. We also outline an exploratory linkage to core-level pathology; formal clinical vali- dation remains future work. Approach: Using retrospectively analysed data from 15 HDR-brachytherapy patients enrolled on a prospec- tive trial, we linked 51 TRUS biopsy tracks to mpMRI DICOM structure sets with 26 DILs contoured. Procedural localization uncertainty was modelled as independent rigid translations for each structure type, sampled from zero-mean Gaussians (SDs 1.25-2.2 mm) and propagated via a 10,000-trial Monte Carlo method to obtain Pi(z) and nominal labels Bi(z). Core-level DIL sampling metrics (⟨PD⟩, max PD) were reported per core and at cohort level. Main results: Continuous along-core probability maps that propagate sampling-location and delineation uncertainties go beyond a nominal along-core hit/miss trace, capturing lesion-enriched sub-segments pre- dicted by the mpMRI derived structure set, transition-band width, and benign prostatic stretches. Across cores, median DIL-sampling descriptors were ⟨PD⟩ ≈ 0.24 and max PD ≈ 0.48; urethral and rectal sampling probabilities were near zero, consistent with safe practice. Significance: The framework converts measured localization uncertainty into interpretable, millimetre-scale tissue sampling metrics. These descriptors can inform pre-procedure plan checks and biopsy pre-planning and, where localization is available, intra-procedural estimates of expected DIL sampling. At the clinic level they offer QA summaries by tracking DIL-sampling metrics such as ⟨PD⟩ and max PD across cores, patients, and operators, and they provide spatially contextualized covariates/weights for downstream assays (e.g., Raman spectroscopy, genomics). Model assumptions (rigid, Gaussian, independent sources) are stated explicitly, with a presented clear path to validation against pathology. These descriptors pertain to sampling of mpMRI-defined DILs and are not, by themselves, malignancy classifiers.

Objective.The range determination uncertainty (σest) based on positron emission tomography (PET) imaging, which stems from the Poisson statistics of the detected signal, can be theoretically predicted using Fisher information. This study aims to experimentally validate a Fisher information-based predictive framework that optimizes the irradiation dose and measurement time required for reliable range verification in PET-guided online adaptive proton therapy.Approach.First, we defined a precision criterion of1.5σest<2mmfor reliable range verification. Then, using polyethylene, water, and a head and neck phantom, we determined the minimum measurement time-calculated in 2 s increments-required to satisfy this criterion at given irradiation doses (0.5 Gy and 0.1 Gy) based on Fisher information. For each condition, 5000 PET images were generated from the measurement datasets, and the maximum likelihood estimation method was independently applied to each to determine the standard deviation of the measured range (σmeas). Finally, the values ofσmeaswere compared with those ofσestto validate the predictive framework.Main results.The values ofσmeasandσestshowed consistent agreement (within approximately 0.5 mm), regardless of target properties, dose levels, and measurement times. Furthermore, the measured range uncertainty satisfied the pre-defined precision criterion of1.5σmeas<2mmunder almost all of the tested conditions.Significance.This study provides the first experimental validation of the Fisher information-based predictive framework for PET-based range verification. The findings offer a rationale for integrating this framework into PET-guided online adaptive proton therapy, which will potentially enable reliable range verification with the minimum pre-irradiation dose and measurement time.