Background and Purpose: Monte Carlo simulations are increasingly used to derive beam quality correction factors (kQ,Q0) for reference dosimetry in clinical proton and carbon ion beams. Type-B uncertainties represent their dominant source of uncertainty, among which the impact of ionization chamber geometry and material properties on absorbed dose calculations has not been fully quantified yet. Materials and Methods: Seven ionization chamber models have been modelled in Image 1001 , and independent perturbations of the geometrical dimensions, material mass densities and I-values were performed. For each chamber model, the absorbed dose in the sensitive volume was computed for clinical proton and carbon ion beams. The deviations from unperturbed simulations were used to estimate type-B uncertainties. Results: All perturbed configurations showed deviations within three standard uncertainties (type-A) of the reference result. Maximum deviations of 0.4% were observed across the three types of perturbation, independently of beam energy or chamber type. Each source of uncertainty contributed to roughly 0.2% individually, with a combined effect of ∼0.4% on the absorbed dose. Conclusions: The type-B uncertainties associated with ionization chamber modelling do not dominate the overall uncertainty of ionization response functions fQ for clinical proton and carbon ion beams which are the basis of Monte Carlo calculated kQ,Q0 factors.

Nonuniform radiopharmaceutical uptake in kidney tissues leads to substructure-level absorbed dose heterogeneity, confounding the establishment of absorbed dose-effect relationships for nephrotoxicity in radiopharmaceutical therapy. We developed a model to enable nephron-level dosimetry. Methods: A multinephron computational model was developed on the basis of 3-dimensional multiphoton microscopy data, including different nephron types (superficial, midcortical, and juxtamedullary) and their main substructures (glomerulus, proximal tubule [PT], and distal tubule) in kidney tissues. Nephron-level S values were determined using Monte Carlo calculations for several β-- and α-emitting radionuclides. The multinephron dosimetry framework was applied to nonuniform kidney tissue uptake data on 225Ac, located primarily in midcortical and juxtamedullary PTs. Results: A nonuniform substructure activity distribution resulted in pronounced absorbed dose heterogeneities. S values varied substantially among nephron types, with the largest in juxtamedullary substructures. The self-dose to PTs was 7.6-15 times higher than the S value of superficial PTs for the α-emitters considered. The cross dose to juxtamedullary glomeruli was on average 20% higher than to superficial glomeruli. The case study revealed substantial absorbed dose heterogeneity, with the absorbed dose to the different PTs being 40%-73% higher than to their respective glomeruli. Additionally, the contribution of free 213Bi to the total absorbed dose differed from that of 225Ac. Conclusion: The developed multinephron framework enables nephron-level dosimetry, allowing quantification of absorbed dose heterogeneity within renal tissues. Such insights enable establishing critical nephron substructures for nephrotoxicity in radiopharmaceutical therapy, supporting nephroprotective strategies during clinical translation of novel radiopharmaceuticals.

Ring-shaped systems based on CZT are promising for quantitative imaging, but their accuracy may be affected by septal penetration of high-energy photons—given the fixed collimator—and by limitations in scatter correction due to low-energy tailing. This study compares the quantitative performance of a ring-shaped CZT system with that of a conventional dual-head NaI SPECT/CT system (StarGuide™ and NM/CT 870 DR, both GE HealthCare) using the 208 keV photopeak of 177Lu. A NEMA phantom with 3D-printed anthropomorphic inserts, including kidneys and lumbar vertebrae, as well as standard spherical inserts, was filled with activity concentrations mimicking the distribution observed in patients 1 day post-injection of 7.4 GBq of [177Lu]Lu-PSMA-I T. The phantom was scanned repeatedly on both systems (scan duration/bed position: 7 min for StarGuide™ and 20 min for NM/CT 870 DR). Quantitative accuracy and reproducibility were evaluated using the mean error and the coefficient of variation (CV) over repeated measurements, respectively. Additionally, a group of patients treated with [177Lu]Lu-PSMA-I T underwent sequential SPECT/CT on both systems to confirm the phantom-based results. The total activity measured within the phantom deviated from the expected value by means of 13

Objective.In the revised version of the TRS-398 Code of Practice (CoP), Monte Carlo (MC) results were added to existing experimental data to derive the recommended beam quality correction factors (kQ) for ionisation chambers in proton beams. While part of these results were obtained from versions v10.3 and v10.4 of the Geant4 simulation tool, this paper demonstrates that the use of a more recent version, such as v11.2, can affect the value of thekQfactors.Approach.The chamber-specific proton contributions (fQ) of thekQfactors were derived for four ionisation chambers using two different versions of the code, namely Geant4-v.10.3 and Geant4-v11.2. A comparison of the total absorbed dose values is performed, as well as the comparison of the dose contribution for primary and secondary particles.Main results.Larger absorbed dose values per incident particle were derived with Geant4-v11.2 compared to Geant4-v10.3 especially for dose-to-air at high proton beam energies between 150 MeV and 250 MeV, leading to deviations in thekQvalues up to 1%. These deviations are mainly due to a change in the physics of secondary helium ions for which the significant deviations between the Geant4 versions is the most stringent within the entrance window or the shell of the ionisation chambers.Significance.Although significant deviations in the MC calculatedfQvalues were observed between the two Geant4 versions, the dominant uncertainty of theWairvalues currently allows to achieve the agreement at thekQlevel. As these values also agree with the current data presented in the TRS-398 CoP, it is not possible at the moment to discriminate between Geant4-v10.3 and Geant4-v11.2, which are therefore both suitable forkQcalculation.

Objective.This work aims to enhance the current data set of beam quality correction factors (kQ) for light ions used in particle therapy, and to assess the contribution of secondary fragments in the case of helium and carbon ion beams.Approach.A Fano cavity test was performed for proton, helium and carbon ions beforekQvalues were derived for 20 ionisation chambers using Geant4-v11.2. For helium and carbon ions, three fragmentation models were compared (binary intranuclear cascade, intranuclear cascade mode++ and quantum molecular dynamics model), and the influence of secondary particles was investigated through the introduction of new correction factors.Main results.For helium ions, an energy dependency of thekQvalues was observed, in addition to significant deviations between the different fragmentation models, especially at the highest clinical energies. For carbon ions, while no significant deviations were observed between the different beam energies or fragmentation models considered, a slight energy-dependency in addition to deviations up to3%with experimental values were highlighted. The factorisation of thekQfactors showed that the perturbation from secondary ions was smaller than0.9%for helium ions and smaller than0.3%with carbon ions.Significance.This work highlights the need for experimentalkQdata for helium ions, in particular to distinguish between various fragmentation models provided by Geant4. In addition, although in agreement with the IAEA TRS-398 Code of Practice, the discrepancy between Monte Carlo and experimental results subsists for carbon ions. The latter is unlikely to be solved without an intensification of experimental measurement campaigns focussing, in particular, on the derivation and uncertainty reduction of theWairvalues.

Introduction Immunohistochemistry (IHC) plays a crucial role in breast cancer diagnosis, treatment selection, and research. However, manual scoring of IHC whole slide images (WSIs) is time-consuming and suffers from inter- and intra-observer variability. Methods To help address these challenges, we present and publicly release a fully automated, compartment-specific (ie, tumor and stroma) H-scoring framework for IHC analysis. The framework consists of three deep learning modules: tumor–stroma segmentation, nuclei segmentation, and H-score estimation for tumor and stroma. It processes WSIs in minutes, delivering consistent and reproducible H-scores with accuracy comparable to expert pathologists. The modular design also allows flexibility for use in other IHC tasks such as cellularity quantification, and supports configuration options to balance accuracy and computational efficiency. Results Fine-tuned on 87 expert-annotated patches, the framework achieved a Spearman's rank correlation ( ρ ) in internal validation of 0.84 (95% confidence interval [CI]: 0.77–0.89) across 100 expert-annotated WSIs, outperforming state-of-the-art ( ρ = 0.78, 95% CI: 0.68–0.85) and matching the inter-observer variability between two expert pathologists ( ρ = 0.84, 95% CI: 0.63–0.94). In external validation, it achieved 86% accuracy in HER2 classification (0–3+) and a mean absolute error of 21 ± 10 (range: [5–46]) in CD73 scoring, where ground truth H-scores were all 0. Conclusion The framework achieves agreement comparable to that of expert pathologists, underscoring its clinical utility in providing reproducible IHC scores that can reduce diagnostic variability and support consistent treatment decisions. The code is available at https://github.com/YinTuo/AutoIHC .

PURPOSE:Managing chemorefractory metastatic colorectal cancer (mCRC) requires a meticulous equilibrium between the efficacy and toxicity of interventions, a task compounded by the constrained life expectancy of the patient. While existing prognostic tools, such as the Colon Life nomogram, primarily focus on general patient conditions or a single diagnostic modality, they do not fully integrate the potential predictive value of multimodal data. This study aims to develop and validate an Imaging Score, integrating clinical and imaging features derived from whole-body 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography-computed tomography (PET-CT), predicting death probability within 12 weeks from treatment initiation for refractory disease. MATERIALS AND METHODS:The development cohort comprises 254 patients from three clinical trials. Nine clinical variables and six imaging variables were assessed. After optimal subset selection through recursive Feature Elimination with cross-validation, a support vector classifier-trained machine learning model generated the Imaging Score. Validation was performed on a real-life patient cohort (n = 74). Model performance was assessed on discrimination (Harrell C-index) and calibration. RESULTS:Final prognostic features included whole-body metabolically active tumor volume, Eastern Cooperative Oncology Group performance status, visceral fat density, number of metastatic sites, body mass index, maximum standardized distance, and months since diagnosis. The Imaging Score demonstrated robust discriminative ability in both the development (C-index, 0.797) and validation (C-index, 0.714) sets, outperforming the Colon Life nomogram that tended to overestimate 12-week mortality. CONCLUSION:The Imaging Score, integrating 18F-FDG PET-CT imaging with clinical parameters, is an effective prognostic tool for patients with chemorefractory mCRC. This combination of imaging biomarkers with clinical factors improves discrimination, enhancing its potential for clinical decision making, patient stratification for chemorefractory treatments, and trial eligibility.

Objective.In the recent update of the TRS-398 Code of Practice (CoP), Monte Carlo results were incorporated into the derivation of recommended beam quality correction factors for ionisation chambers (IC) in proton beams. While the underlying Monte Carlo simulations implement detailed models only based on the nominal geometries from manufacturer blueprints, this paper considers the potential geometric deviations in plane-parallel IC arising from manufacturing tolerances that can reach 10%.Approach.A representative model of a plane-parallel IC has been designed using the Monte Carlo code GATE/Geant4, from which beam quality correction factors have been derived. Subsequently, the results of a reference geometry are compared to those of perturbed geometries, in which the parameters are modified according to the tolerances specified in a standard.Main results.The comparison between the reference and perturbed geometries reveals no significant differences, as they show an agreement within one standard deviation for all the cases studied, with relative deviations not exceeding 0.5%. From these results, we estimate the maximum added uncertainty from manufacturing tolerances on Monte Carlo calculatedkQfactors to be about 0.7%.Significance.Overall, the current use of nominal dimensions of plane-parallel IC from manufacturer's blueprints remains consistent for beam quality correction factor calculations via Monte Carlo simulations, which therefore support the latest results recommended by the TRS-398 CoP.