Physics in medicine and biology最新文献

Objective: Adaptive radiotherapy (ART) requires robust end-to-end (E2E) testing tools capable of reproducing organ deformation, physiological motion, and multimodal imaging properties. The TAM-ARa (ThoracicAnthropomorphic Phantom withMotion forAdaptiveRadiotherapy) is a dynamic anthropomorphic phantom developed to validation and quality assurance of online ART workflows. Approach:The phantom was constructed with anatomically realistic bone, lung, and abdominal organ models fabricated from tissue equivalent materials. Modular components allowed simulation of interfractional and intrafractional anatomical variations, including ventilator driven respiratory motion, abdominal deformation, and variable gastric filling. CT, CBCT, and 3T MRI scans were acquired to assess imaging performance. Two E2E tests of an online adaptive IMRT workflow for liver tumors were performed on a Varian Ethos (ETHOS, Varian, USA) system. Multiple deformation scenarios were investigated, including a static reference configuration, two abdominal and one thoracic deformation for ionization chamber (IC) dosimetry, and a static plus abdominal deformation scenarios for radiochromic film dosimetry. Main results:The TAM-ARa phantom demonstrated realistic radiological characteristics, with CT Hounsfield units and MRI relaxation times closely matching reported in vivo values. The modular design allowed reproducible and controlled abdominal deformations, while setup and dosimeter placement were completed within minutes. In E2E tests for adaptive IMRT of liver tumors, excellent agreement was achieved between measured and planned dose after the treatment plan was adapted. IC E2E measurements showed that online adaptation consistently restored accurate dose delivery under deformation, reducing deviations to below 3%. Independent film measurements confirmed sub-millimeter geometric accuracy and full planning target volume coverage after adaptation, demonstrating effective compensation of deformation-induced errors. Significance:The TAM-ARa phantom provides a versatile and reproducible platform for multimodal E2E testing and validation of online ART workflows. Employing its realistic anatomical design, modular structure, and motion capabilities, TAM-ARa was successfully applied for E2E tests to validate a workflow for adaptive IMRT of liver tumors.

Objective. We are developing a high-resolution, high-sensitivity breast-dedicated PET scanner that can image the distribution of multiple tracers simultaneously, referred to as multiplexed PET (mPET). This requires the detector to have high intrinsic spatial resolution and detection efficiency, as well as resolve photon depth-of-interaction (DOI).Approach. The detector array design comprises a novel trapezoidal shape configuration with scintillation crystal rod elements of different lengths to enable adequate intrinsic detection efficiency for prompt gamma ray photons (>511 keV) in addition to 511 keV photons, which is also practical to fabricate and assemble. The LYSO element lengths range from 5 mm to 35 mm, with a 1.28 mm pitch, read out by a multi-pixel photon counter (MPPC) array with a 3 mm pixel size. A light-sharing approach, combined with unpolished crystal surfaces and top-side light guides, enables DOI encoding. A prototype detector module was experimentally evaluated for flood image/crystal element separation, energy, DOI, and detector timing resolution. Measurements were performed under both side-irradiation and top-irradiation setups to assess the detector's performance across different interaction positions.Main results. The prototype detector flood image successfully resolved crystal elements even for 35 mm length crystals. DOI resolutions in full width at half maximum measured 4-6 mm for crystal lengths ranging from 10 mm to 30 mm and 7-8 mm for the 35 mm crystal length. Energy resolutions varied from 13% to 28%, with degradation observed at positions farther from the MPPC array plane. Detector time resolution values ranged from 330 ps to 660 ps.Significance.This work introduces a novel, single-ended readout, DOI-capable detector design that optimizes sensitivity while maintaining high spatial resolution for a breast-dedicatedmPET system, utilizing a unique trapezoidal crystal array and light-sharing DOI encoding designs. Additionally, this design offers a scalable approach that can be adapted to other high-performance PET systems.

Objective.The skeleton contains the red bone marrow (RBM) and the endosteum, tissues linked to radiation-induced leukemia and bone cancer, making their consideration essential in radiation dosimetry. Although adult skeletal dosimetry has advanced with 3D images such asμCT images, the scarcity of comparable pediatric images prevents pediatric skeletal dosimetry from achieving a similar level. This study aims to develop 3D image-based detailed pediatric skeletal models that, while grounded in adultμCT images, incorporate the anatomical features of the developing pediatric skeleton.Approach.Target skeletal values were established from extensive anatomical literature and International Commission on Radiological Protection publications, including skeletal tissue mass, cellularity factor, trabecular bone volume fraction, and trabecular number. Guided by these values, trabecular bone models converted from adultμCT images were refined, a 50μm endosteal layer was defined, yellow bone marrow (YBM) was incorporated as adipocytes, and remaining regions were assigned as RBM. All modeling steps were performed automatically using our C++-based bone modeling program.Main results.A total of 246 pediatric skeletal models were developed in a high-quality mesh format across six age and sex groups (sex-averaged newborn, 1 year-old, 5 year-old, and 10 year-old, and sex-specific 15 year-old male and female), with each group comprising 41 models. These models represent trabecular bone and RBM/YBM in both the shallow and deep marrow, and all matched their target values within 2%. For selected cases, PHITS Monte Carlo simulations were used to calculate specific absorbed fractions, which increased with decreasing age due to differences in target mass and the combined effects of the anatomical factors incorporated in this study.Significance.This study provides the first comprehensive set of 3D image-based pediatric skeletal models for skeletal dosimetry. These models, together with the dosimetric datasets derived from them, are expected to provide an anatomically robust foundation for improving the accuracy and reliability of pediatric skeletal dosimetry.

Objective Previous MR guided radiation therapy (MRgRT) radiofrequency coil arrays have been limited to one to two rows of coils in the head-foot direction because of the desire to place radiation-opaque coil circuitry outside the window through which the radiation beam travels. However, such layouts limit parallel imaging undersampling in the head-foot direction. We recently demonstrated a three-row array with a remote coil circuit that improved parallel imaging performance, while preserving the signal-to-noise ratio (SNR) and the radiolucent window. Here we evaluate a four-row prototype design to determine if further parallel imaging advantages could be realized. Approach We built remote circuits that allowed radio-opaque components to be placed outside the field of view through which the radiation beam is expected to travel. The circuit consisted of a phase shifter to cancel the phase introduced by the radiolucent coaxial link between the circuit and coil, followed by standard components for tuning, matching, detuning, and preamplifier decoupling. Measurements were performed on an abdominal phantom to compare single-channel coils with remote or local circuits, followed by tests on a 16-channel four-row array. Main results The four-row array maintained SNR comparable to two-and three-row designs while supporting 3× head-foot acceleration (minimum reciprocal g-factor = 0.74) and 2×3 multi-directional acceleration (minimum reciprocal g-factor = 0.72), capabilities which were not achievable with previous designs. Significance These results demonstrate the technical feasibility of four-row designs, which may benefit MRgRT applications that require high SNR and temporal-resolution.

Background and purpose.Image-guided intracavitary/interstitial brachytherapy is standard for locally advanced cervical cancer (LACC), yet the lack of pre-implantation planning often leads to suboptimal catheter placement and dose distribution. A template-guided, multi-criteria optimization-based pre-implantation planning system was thus proposed, which integrates dosimetric, radiobiological, and geometric objectives.Materials and methods.The developed system employs an improved wish-list optimization strategy featuring a tighten-relax mechanism with hybrid constraints to enhance robustness and resolve conflicts from impractical wish-lists. It incorporates dose-volume indices, the generalized equivalent uniform dose, and a novel total conformity index, while supporting oblique catheter insertions for improved dose conformation. Dosimetric performance was benchmarked against clinical approved plans in 40 LACC cases, focusing on target coverage, conformity, and organ-at-risk sparing.Results.Compared to the catheter configurations in clinically approved plans, the proposed method resulted in catheter displacement exceeding 5 mm in 11 out of 40 LACC cases and catheter angular deviation greater than 10°in 7 cases. Correspondingly, the proportion of new plans meeting theD₉₀> 100% criterion was 100% with template guidance versus 92.5% without, both significantly higher than the 82.5% achieved by original clinical plans. The method also increasedV₉₀andV₁₀₀by 3.4% and 4.9% (bothp< 0.001), improved dose conformity from 0.59 to 0.61 (p< 0.001), while maintaining OARD_2ccwithin clinical limits.Conclusion.The proposed pre-implantation planning method reduces reliance on operator experience and offers a robust, automated solution for high-conformity brachytherapy.

Objective: Radiotherapy (RT) requires accurate and consistent patient positioning to ensure precise radiation delivery and minimize unnecessary exposure to healthy tissues. Conventional workflows rely heavily on clinicians' experience and repeated CT-based registration, leading to inefficiency, patient discomfort, and potential alignment inconsistencies. This work aims to develop an automatic, robust, and low-cost posture offset detection method that overcomes these limitations.

Approach: We propose a prompt-guided incremental fine-tuning model built upon a large-scale image segmentation backbone. The system captures real-time 2D images from a single RGB camera and automatically generates adaptive prompt points based on individual body shapes and postures, improving segmentation robustness and reducing environmental interference. An incremental fine-tuning strategy enables continuous adaptation to newly collected patient images throughout the treatment cycle. Furthermore, a multi-level offset analysis framework is introduced, integrating contour-level, keypoint-level, and pixel-level estimations to identify, localize, and quantify posture deviations across multiple granularities. The system is deployed clinically to collect real RT data and construct a dedicated validation dataset.

Main results: Extensive experiments on real clinical data show that the proposed method achieves accurate, fast, and stable posture offset detection. It substantially improves positioning consistency and efficiency compared with conventional workflows. Ablation studies further demonstrate the effectiveness and necessity of each module within the framework.

Significance: This study provides a practical and low-cost solution for RT positioning, reducing clinician workload and patient burden while improving treatment accuracy. It demonstrates the potential of prompt-guided incremental adaptation and multi-level offset analysis in real RT environments, offering a promising direction for intelligent, automated radiotherapy positioning systems.

Objective.As part of treatment planning for radiotherapy, the organs at risk (OARs) are delineated on the patient's CT scan. This work aims to develop a method to measure variability in OAR delineations and detect errors.Approach.A normative modelling approach was implemented by training a variational autoencoder (VAE) on a dataset of images and delineations to model the "acceptable" variability distribution. The trained VAE was then used to reconstruct unseen cases. Disagreements between input and reconstructed delineations highlighted regions where the input deviated from the training distribution. This approach was validated by evaluating the reconstructions of spinal cord and brainstem delineations where common clinical errors had been introduced.Main results.Results showed that the model successfully detected errors, even when only a few voxels or slices were added or removed. Distance to agreement maps were generated to quantify the magnitude of the disagreements in misclassified regions. These results were further validated by manually evaluating some of the test cases.Significance.This tool has the potential of assisting clinicians in reviewing and validating OAR delineations.

Objective: Particle therapy relies on up-to-date knowledge of the stopping power of the patient tissues to deliver the prescribed dose distribution. The stopping power describes the average particle motion, which is encoded in the distribution of prompt-gamma photon emissions in time and space. We reconstruct the spatiotemporal emission distribution from multi-detector Prompt Gamma Timing (PGT) data. Solving this inverse problem relies on an accurate model of the prompt-gamma transport and detection including explicitly the dependencies on the times of emission and detection.

Approach: Our previous work relied on Monte-Carlo (MC) based system models. The tradeoff between computational resources and statistical noise in the system model prohibits studies of new detector arrangements and beam scanning scenarios. Therefore, we propose here an analytical system model to speed up recalculations for new beam positions and to avoid statistical noise in the model.

Main results: We evaluated the model for the MERLINO multi-detector-PGT prototype. Comparisons between the analytical model and a MC-based reference showed excellent agreement for single-detector setups. When several detectors were placed close together and partially obstructed each other, intercrystal scatter led to differences of up to 10 % between the analytical and MC-based model. Nevertheless, when evaluating the performance in reconstructing the spatiotemporal distribution and estimating the stopping power, no significant difference between the models was observed. Hence, the procedure proved robust against the small inaccuracies of the model for the tested scenarios.

Significance: The model calculation time was reduced by factor of 1500, now enabling many new studies for PGT-based systems.

Objective: Boron Neutron Capture Therapy is a cancer radiotherapy that uses the selective uptake of boron compounds by tumor cells, followed by neutron irradiation. Conventional dosimetry generally assumes a homogeneous boron distribution within tissues, yet evidence indicates intracellular heterogeneity. This work aims to improve the Photon Isoeffective Dose model (PID) for Glioblastoma Multiforme (GBM) by incorporating subcellular-scale effects: (i) a correction factor for the stochastic nature of energy deposition due to intracellular boron localization, and (ii) the treatment of the nucleus-to-cytoplasm boron concentration ratio as a stochastic variable.

Approach: The boron-10 microdistribution in U-87 glioblastoma cells was quantified for the first time through neutron autoradiography, revealing preferential accumulation in the nucleus. Following these experimental data, the nucleus-to-cytoplasm boron concentration ratio was described by a lognormal random variable, consistent with biological uptake processes. The correction factor was applied to the dosimetry of U-87 radiobiological data. Then, updated radiobiological parameters and subcellular-scale effects were integrated into the PID formalism and applied to a clinical case of GBM.

Main results: The outcome was a Microdosimetric Photon Isoeffective Dose Model, which extends conventional PID by explicitly including intracellular boron heterogeneity. Applied to U-87 data, proposed corrections revealed a 47% reduction in the Compound Biological Effectiveness factor compared to conventional calculations, showing that neglecting subcellular distribution substantially overestimates the boron dose. For the clinical case, the total dose and 1-year Progression-Free Survival (PFS) differed only by 4% and 3%, respectively, compared to conventional dosimetry. However, perturbation analyses indicated that under higher intracellular heterogeneity, plausible in vivo, the deviations could become substantial (up to 22% in dose and 68% in PFS).

Significance: These findings highlight the relevance of subcellular-scale modeling. The proposed Microdosimetric Model, grounded on experimentally derived microdosimetric corrections, provides a robust framework to improve both the accuracy and the personalization of BNCT treatment planning.

Objective. Targeted radionuclide therapy using alpha-particle-emitting radiopharmaceuticals (alpha-RPT) is increasingly recognized as an effective, safe and economically viable clinical treatment. However, it is restricted to few cancer types, and to metastatic or unresectable tumors as a palliative treatment. Broader implementation of alpha-RPT across cancer types and earlier disease stages is hampered by limitations of current clinical dosimetry. Alpha-RPT administration regimens rely on fixed protocols for intermittent radioactivity (RT) administration, without dynamic adjustments. This study provides a computational proof-of-concept of continuous dynamic-discretized RT administration strategy for alpha-RPT inspired by black hole (BH)-like dynamics.Approach.BHs can exhibit impressive forms of convergence, stability and robustness, ensuring a trapped region, in which matter cannot escape from it. When extrapolated to cancer therapy, the tumor is analogically considered as a mass inside a BH, in which the BH center represents the cancer remission, and the alpha-RPT administration acts as the gravitational attraction pulling the tumor mass towards the center (where a complete remission is reached). Using a recently validated mathematical model of Actinium-225 alpha-RPT in a Murine breast cancer model, we were able to predict geometro-radiopharmacokinetics and tumor dynamics for different number of tumor cells, discretization intervals, and a wide variation range of tumor parameters.Main results.Our results show that BH-like RT administration can significantly reduce total administered RT and treatment duration compared with current clinical practice based on intermittent administration, while maintaining therapeutic efficacy, even under highly uncertain tumor dynamics. Reductions in treatment duration up to 48.8% were obtained, as well as reductions in maximum/average RT administration up to 54.3%/81.1%.Significance. These findings suggest that adaptive control strategies may overcome key limitations of current alpha-RPT protocols, allowing dynamically adjusted RT administration according to tumor state data obtained from biomarker data and/or theranostic imaging. This strategy holds the potential to refine clinical protocols and expand alpha-RPT beyond its current limitations, establishing the 'biological BH' as a new high-impact foundation for spreading alpha emitting RPT to primary cancers and multiple cancer types.