European Journal of Nuclear Medicine and Molecular Imaging

Background: Prostate-specific membrane antigen (PSMA) PET/CT is central to prostate cancer staging and theranostic workflows. To our knowledge, no direct within-patient comparison of [18F]FC303 ([18F]Florastamin) and [68Ga]Ga-PSMA-11 has been reported. We performed a preliminary paired method-comparison study under non-harmonized acquisition protocols. Patients and Methods: Twenty patients with histologically confirmed prostate cancer underwent [68Ga]Ga-PSMA-11 PET/CT (185 +/- 37 MBq, 60 +/- 10 min) followed by [18F]FC303 PET/CT (370 +/- 37 MBq, 105 +/- 15 min) on the same PET/CT system within each patient (median interval, 29.5 days). Index targets were anatomically matched to the biopsied or surgically sampled lesion or target region. The primary malignant set included 18 histologically malignant targets; two histology-negative or indeterminate targets were included only in sensitivity analysis. Fixed [68Ga]Ga-PSMA-11-first scan order and the 45-min uptake-time difference were central interpretive constraints. Results: Across five predefined reference organs, [18F]FC303 showed lower SUVmean than [68Ga]Ga-PSMA-11 (all Benjamini-Hochberg-adjusted p < 0.001; [68Ga]/[18F]FC303 geometric mean ratio [GMR], 1.29-3.89). In the primary malignant set, [18F]FC303 lesion SUVmax was lower than [68Ga]Ga-PSMA-11 (median, 11.3 vs 18.1; paired median difference, -5.50; 95% CI, -6.85 to -2.90; Wilcoxon p = 8.4 x 10-4), with strong rank correlation (Spearman {rho} = 0.90). Passing-Bablok regression yielded {beta} = 1.13 (95% CI, 1.04-1.45), and log-Bland-Altman GMR (FC303/[68Ga]) was 0.75, consistent with proportional non-interchangeability. Tumor-to-liver and tumor-to-mediastinum ratios did not differ significantly (GMR, 1.17 [95% CI, 0.94-1.45] and 0.96 [0.80-1.15], respectively); the study was not powered for equivalence. The n = 20 sensitivity analysis showed consistent directionality. Conclusions: Under non-harmonized acquisition conditions, [18F]FC303 showed lower physiologic reference-organ SUVmean and malignant target-region SUVmax than [68Ga]Ga-PSMA-11, whereas tumor-to-liver and tumor-to-mediastinum ratios were not significantly different. Absolute SUVs were not interchangeable; [68Ga]Ga-PSMA-11-derived SUV thresholds should not be directly transferred to [18F]FC303 without tracer-specific calibration.

Background: Meningiomas are the most common primary intracranial tumors in adults, and volumetric assessment increasingly guides surveillance and treatment decisions. Automated segmentation could enable standardized volumetry but requires robust validation. Purpose: To develop a fully automated three-dimensional deep learning model for meningioma segmentation on multiparametric MRI, and to evaluate segmentation accuracy, external generalizability, failure modes, radiologist-rated clinical plausibility, and workflow feasibility. Methods: From 2024 to 2026, this retrospective study trained a custom 3D nnU-Net residual encoder model. Expert segmentations covered enhancing tumor (ET), tumor core (TC), and whole tumor (WT). Dice similarity coefficient (DSC) was the primary metric. External validation used an independent single-institution dataset (n = 310 intracranial cases) with incomplete MRI protocols. Failure modes, model equity, and inference time were assessed. A blinded multi-rater study (10 radiologists; 510 cases) rated TC segmentations using a 0-10 Likert scale, analyzed with linear mixed-effects models. Results: Model training used the BraTS Meningioma 2023 dataset (n = 1000; mean age 60.2 {+/-} 14.5; 705 female). In cross-validation, mean DSC was 0.939 for ET, 0.937 for TC, and 0.921 for WT. In external validation, mean DSC was 0.872 for TC and 0.842 for WT, despite heterogeneous protocols and incomplete sequences. Predicted TC volumes correlated strongly with reference volumes in cross-validation (r = 0.995) and external validation (r = 0.971). Most common failure modes were skull base and intraosseous tumors with performance equitable across demographic subgroups. Mean inference time was 1.2 seconds. In blinded evaluation (1120 ratings), model segmentations received higher scores than reference annotations (+0.32 BraTS; +1.38 external validation). Conclusion: A fully automated deep-learning model achieved high meningioma segmentation accuracy across multi-institutional training data and external clinical imaging. In a blinded study, model segmentation quality exceeded reference annotations, and 1.2-second inference supported workflow integration. Prospective evaluation is warranted before routine deployment.

BackgroundRealistic PET/CT phantoms are essential for system evaluation, protocol optimization, and validation of advanced reconstruction methods. However, existing phantoms are often limited by simplified geometries, spatially uniform activity patterns, and complex preparation procedures. PurposeTo develop and evaluate PixelPrintPET, a 3D printing-based method for fabricating anatomically realistic PET/CT phantoms with spatially heterogeneous radiotracer distributions and a single-solution filling workflow that avoids physical compartmentalization. MethodsPixelPrintPET generates voxel-based printing instructions that encode spatially varying infill, which is realized during printing through modulation of filament extrusion, enabling heterogeneous activity distributions without compartmentalization of radioactivity at different activity concentrations. Calibration phantoms and anatomically structured phantoms were designed and printed using high-flow polylactic acid (PLA), with anatomical inputs derived from either digital atlas-based models or patient imaging data. The printed phantoms were subsequently filled by immersion in a radioactive solution, allowing activity distribution to be controlled by the internal porous structure. A bottom-up filling procedure with reduced surface tension was developed to ensure uniform infiltration and minimize air entrapment. Phantoms were imaged on the PennPET Explorer PET/CT system, and quantitative performance was evaluated using contrast recovery coefficient (CRC), target-to-background ratio (TBR), and comparisons with simulated or patient-derived reference data. ResultsA strong linear relationship between infill ratio and normalized signal (R2 = 0.998) was demonstrated by the calibration phantom, enabling reliable mapping between structure and activity. Additionally, air entrapment was minimized to less than 1% of the total phantom volume. In the contrast recovery phantom, CRC values were consistent with measurements using traditional phantoms. The brain phantom reproduced atlas-derived contrast patterns, with gray-to-white matter differences within 5% after accounting for resolution and other system effects. The patient-based thorax phantom showed high reproducibility across repeated scans, with differences within 3%, and closely matched the input patient image with regional differences within 10% in all regions except the lung. ConclusionsPixelPrintPET enables the fabrication of realistic, reproducible, and versatile PET/CT phantoms with a voxel-level control of the activity distribution. This approach provides a practical solution for generating patient-specific and application-specific phantoms, with the potential to accelerate system validation, protocol development, and clinical translation of advanced PET/CT technologies.

Whole-body SPECT bone scintigraphy reflects skeletal metabolic activity throughout the body and plays an indispensable role in the screening, treatment evaluation, and prognostic assessment of bone metastases in tumors. However, the automatic detection and segmentation of hypermetabolic bone lesions remain challenging due to low contrast, limited spatial resolution, and complex lesion distributions. In this study, we proposed Bone-Segnet, a dual-view guided automatic segmentation network for hypermetabolic bone lesions that integrated multi-scale feature modeling, global context modeling, and view-conditioned modulation. Pixel-level annotated anterior and posterior whole-body bone scintigraphy images were used for model training and prediction. The proposed network enhanced the recognition of low-contrast and small-scale lesions through small-lesion enhancement and multi-scale contextual modeling. A Transformer module was further introduced to strengthen global feature representation, while cross-view collaborative modeling was achieved by incorporating the complementary characteristics of anterior and posterior imaging. Experimental results demonstrated that the proposed method outperformed existing approaches across multiple evaluation metrics, with the Dice score improving from 0.7440 to 0.8750, indicating a substantial improvement in segmentation performance. Further quantitative analysis based on the segmentation results revealed significant differences among disease types in lesion count, pixel burden, and spatial distribution patterns, reflecting the heterogeneity of disease-related skeletal metabolic activity. Overall, the proposed method improved automatic lesion segmentation performance and enabled quantitative analysis of lesion burden and spatial distribution patterns, providing objective data support for the assessment of related diseases. Index Terms--Whole-body SPECT, bone lesion segmentation, dual-view modeling, quantitative analysis.

Assessment of pathologic complete response (pCR) following neoadjuvant chemotherapy (NAC) remains an unmet clinical need in breast cancer. Fibroblast activation protein inhibitor (FAPI) PET targets the tumor microenvironment and may therefore enhance response evaluation after NAC. This study aimed to compare the performance of [68Ga]Ga-FAPI-04 PET, [18F]FDG PET, and contrast-enhanced MRI for predicting pathologic response after NAC in breast cancer, with separate analyses for primary breast lesions and axillary lymph nodes. MethodsIn this prospective single-center diagnostic accuracy study, women with biopsy-confirmed stage II-III breast cancer underwent baseline and post-therapy [68Ga]Ga-FAPI-04 PET/MRI, [18F]FDG PET/CT, and contrast-enhanced MRI before surgery. Quantitative PET parameters were evaluated for primary tumors and axillary lymph nodes. pCR was defined as ypT0/isN0. Significant variables identified in univariable analyses were further explored using least absolute shrinkage and selection operator (LASSO) analysis, and receiver-operating-characteristic (ROC) analysis was performed to assess diagnostic performance. Fibroblast activation protein expression was also assessed by immunohistochemistry in paired pre- and post-therapy tumor specimens from a subset of patients. ResultsTwenty-four patients completed the study protocol, yielding 25 primary lesions and 44 metastatic lymph nodes across 27 axillary compartments. Overall patient-level pCR was achieved in 13 of 24 patients (54.17%). The lesion-level pCR rate was 60.00% (15/25) for primary breast lesions, and the node-level pCR rate was 72.73% (32/44) for axillary lymph nodes. For primary tumor response, post-therapy [68Ga]Ga-FAPI-04 SUVmax showed the highest diagnostic performance (AUC, 0.84; sensitivity, 80.00%; specificity, 80.00%; accuracy, 80.00%), whereas the optimal [18F]FDG parameter was {Delta} TBR% (AUC, 0.747). For nodal response, post-therapy [68Ga]Ga-FAPI-04 SULmean showed the highest diagnostic performance (AUC, 0.89; sensitivity, 91.67%; specificity, 81.25%; accuracy, 84.09%) and was significantly different from the best [18F]FDG parameter ({Delta} SULmax%, AUC, 0.669) on DeLong testing (P < 0.05). MRI achieved AUCs of 0.733 for primary lesions and 0.770 for lymph nodes. Stromal FAP expression positively correlated with [68Ga]Ga-FAPI-04 SUVmax and was markedly reduced in lesions achieving pCR. ConclusionPost-therapy [68Ga]Ga-FAPI-04 PET may serve as a promising adjunctive imaging biomarker for predicting pathologic response after NAC in breast cancer, particularly for axillary nodal assessment. These findings suggest that FAPI PET may provide clinically relevant information for preoperative evaluation of residual disease burden, potentially contributing to more individualized surgical planning and treatment decision-making.

IntroductionMagnetic resonance imaging (MRI) is central to neurological care, yet access remains profoundly inequitable in low- and middle-income countries, especially in rural health facilities where high costs and fragile electricity supply limit services. Ultra-low-field (ULF) portable MRI offers a way to expand access, but deployment in weak-grid settings requires robust affordable power. We characterized the power needs of a 0.064T portable ULF MRI system and assessed the feasibility of a solar-powered MRI-capable facility in a rural Zimbabwean clinic, which we believe to be the first of its kind in the world. MethodsWe measured the power draw of an ultra-low-field MRI session from a portable photovoltaic (PV) battery kit in the UK, quantifying scan, standby and energy use. We then monitored a PV-battery micro-grid supplying a protected circuit at an MRI-capable clinic in Shurugwi, Zimbabwe. Inverter telemetry was used to derive PV generation, load, battery state of charge (SoC) and grid import for working days in October-November 2025, spanning the end of the dry season and onset of the rainy season. ResultsIn the portable configuration, a 64-minute MRI session consumed [~]0.21 kWh, with standby demand of [~]1.44 kWh per 24 hours. In clinic, mean PV generation was 9.10 kWh (SD=1.34) and load 9.91 kWh, with zero recorded grid import and minimum daily SoC typically [&ge;]60%, including during the early rainy season. ConclusionAn affordable PV-battery micro-grid can reliably support ULF MRI and associated research power loads in a rural, weak-grid clinic, offering a reproducible blueprint to narrow diagnostic equity gaps in resource-limited settings.

Background: Amyloid-beta PET provides critical biomarker data for Alzheimer's disease diagnosis and anti-amyloid therapy evaluation, yet low spatial resolution and partial volume effects result in decreased interpretability, particularly in cases with low or borderline cortical amyloid burden. While quantitative metrics (SUVr, Centiloid) aid in interpretation of amyloid burden, disagreement between visual reads and quantitative burden does occur, further blurring the line between positive or negative scans. We evaluated whether a vendor-neutral MR-guided PET denoising and resolution enhancement method (MRG) that uses Bowsher regularization improves image interpretability and reader performance while preserving established quantitative biomarkers across multiple amyloid tracers, leading to increased concordance among visual reads and quantitative metrics. Methods: Standard (STN) and MRG PET images were compared for four tracers ([18F]AV-45 ([18F]florbetapir, FBP), [18F]florbetaben (FBB), [18F]flutemetamol (FMM), and [11C]Pittsburgh compound-B (PiB) collectively from 24 MRI and 33 PET scanners. Quantitative equivalence was assessed by comparing Standardized Uptake Value ratio (SUVr) and Centiloid scores. In three of the four tracers (FBP, FBB, FMM), visual-quantitative concordance (AUC) and reader performance were evaluated in a blinded multi-reader study by four highly experienced brain PET readers who assessed image quality, artifact severity, reader confidence, and binary amyloid positivity. Results: Across all tracers, MRG preserved quantitative SUVr and Centiloid metrics relative to STN (R2 >0.90 for all tracers) without introducing bias to the SUVr metric. Concordance between visual reads and quantitative burden measures significantly improved with MRG. In the multi-reader study, MRG resulted in significantly higher image quality, lower artifact burden, and greater reader confidence compared to STN (p < 0.0001). Reader accuracy increased from 0.89 to 0.94, and the false-negative rate decreased from 0.08 to 0.04. Crucially, improvements in reader confidence, accuracy, and the reduction in false negative reads were most pronounced in cases with low amyloid burden near the threshold of visual positivity. Conclusions: MRG denoising and resolution enhancement improved perceived image quality, reader confidence, and accuracy for amyloid PET while preserving standard quantitative behavior across tracers. By improving cortical definition in visually challenging low-burden cases without disrupting established SUVr/Centiloid behavior, MRG may reduce visual-quantitative discordance and support more confident amyloid PET interpretation near the threshold of positivity.

Colony stimulating factor 1 receptor (CSF1R) is a tyrosine kinase receptor that is expressed exclusively in microglia within the CNS. Its endogenous ligands, colony stimulating factor-1 (CSF1) and interleukin-34 (IL-34), are released from neurons, positioning CSF1R as a key mediator receptor of neuron-glia communication. CSF1R is considered not only a potential drug target, but also a biomarker of neuroinflammation. From that perspective, selective radioligands for neuroimaging are of great interest for imaging neuroinflammation and determining drug occupancy. In this study, we have validated the binding characteristics of a CSF1R inhibitor, 4-((5-MethOxy-6-((5-methoxypyridin-2-yl)methoxy)pyridin-3-yl)methyl)-2-(1-methyl-1H-pyrazol-4-yl)pyrimidine (5-MOP) as a novel CSF1R radioligand, by performing in vitro saturation binding experiments in human and murine tissues. 5-MOP was found to be selective for CSF1R among a broad range of kinases. Autoradiography revealed that [3H]5-MOP binds with high affinity (KD = 9.8 nM) to a single saturable binding site in human meningioma tissues, and this binding was displaced with known CSF1R inhibitors, including CPPC, sCSF1inh and GW-2580. In contrast, CPPC, which has been extensively used as a CSF1R radioligand showed substantial cross-reactivity to other brain kinases, including Trk A/B/C, and [3H]CPPC could only be displaced with CPPC itself, not by other ligands, including 5-MOP. These results identify [3H]5-MOP as the most selective radioligand currently available, enabling accurate detection of drug occupancy and activated microglia. Significance of the studyThis study identifies and validates a novel selective radioligand that binds CSF1R with high selectivity and low nanomolar affinity. Because CSF1R is selectively expressed in activated microglia, this radioligand could be useful for detecting neuroinflammatory activity.

Digital health technologies (DHT) offer a promising solution to the timely identification of early Alzheimer's disease (eAD) to enable early treatment. This study evaluated the feasibility, acceptability, adherence, reliability, and preliminary clinical and content validity of the novel AD Digital Assessment Suite (AD-DAS). 123 individuals (32 healthy controls (HC), 31 amyloid-PET negative (SCDn), 30 amyloid-PET positive (SCDp) with subjective cognitive decline, and 30 early AD (eAD)) participated. AD-DAS was remotely deployed for 28 days. Remote testing was feasible (97.6% completers), acceptable (>85% ''good''), and associated with high adherence (96%). Metrics showed moderate to excellent test-retest reliability (ICC 0.53-0.91), associations with clinical comparators (adjusted R2 0.01-0.24), differentiated eAD from other known groups (absolute log odds differences 0.6-3.28), and correlated with brain atrophy in expected regions. Episodic and working memory AD-DAS metrics differentiated SCDp from SCDn participants. These preliminary findings suggest that AD-DAS may be a promising tool for detecting cognitive impairments in early AD stages.

Intratumoral (i.t.) delivery of nanoparticles (NPs) is widely used to achieve high local NP concentrations. However, the temporal fate of i.t.-injected NPs remains poorly understood. We present a quantitative approach using whole-body magnetic particle imaging (MPI) to track magnetic NPs (MNPs) following i.t. injection. Using fiducial-calibrated imaging, we quantified MNP mass over time in subcutaneous 4T1 breast tumors. Longitudinal imaging revealed progressive loss of i.t. MNP content and heterogeneous systemic redistribution across animals despite standardized delivery conditions. Ex vivo MPI confirmed off-target accumulation primarily in the liver and spleen, consistent with reticuloendothelial clearance pathways. Histological analysis demonstrated spatially heterogeneous i.t. MNP deposition, potentially associated with local vascular features and tumor microenvironmental heterogeneity that may influence i.t. MNP retention or MNP clearance from the tumor. These findings highlight the importance of quantitative longitudinal whole-body MPI for understanding the fate of MNPs for informing localized nanotherapy.

Background: Traditional bone scintigraphy for detecting malignant bone metastases is limited by suboptimal accuracy and radiation exposure. Whole-body magnetic resonance imaging (WB-MRI), while an alternative, requires lengthy scan times and high patient compliance. Purpose: To develop a novel, rapid whole body bone screening (WB-RBS) MRI protocol and evaluate its diagnostic performance for bone metastasis detection. Materials and Methods: Patients with pathologically confirmed malignancies and healthy controls were prospectively enrolled. All participants underwent WB-RBS (acquisition time: about 10 min); patients additionally underwent WB-MRI (about 70 min). Three radiologists, blinded to clinical data, independently evaluated the images for bone metastases. A consensus expert diagnosis served as the reference standard to calculate the diagnostic performance of WB-RBS. Specificity was further assessed in the healthy control group. Results: Seventy patients and 19 healthy controls were included. WB-RBS demonstrated excellent inter-reader agreement at the patient level. Compared with the reference standard, WB-RBS achieved an accuracy of 77.1%-91.4% at the patient level and a slightly lower accuracy (70.6%-82.5%) at the lesion level. At diagnostic confidence thresholds 1-3, the correlations between WB-RBS ratings and the reference standard were statistically significant for both patient- and lesion-level analyses. Conclusion: WB-RBS showed favorable inter-reader agreement and high accuracy for bone metastasis screening at the patient level, while substantially reducing scan time and cost. Its rapid, radiation-free nature and high accessibility offer distinct clinical advantages, supporting its potential as an alternative screening tool to conventional bone scintigraphy.

The poor prognosis of brain tumors, including IDH-wild-type glioblastoma (GB), as well as brain and leptomeningeal metastases, is partly related to the blood-brain barrier (BBB), which limits the delivery of hydrophilic anticancer drugs to the tumor site and surrounding brain parenchyma. Early studies using vital dyes demonstrated that intracranial injection could bypass the BBB in cats. We confirmed that, in guinea pigs, the vital dye Bleu Patente V diffused efficiently into the brain after a bolus intracranial injection, whereas the brain remained unstained after intravenous administration. Similarly, brain concentrations of the hydrophilic anticancer drug gemcitabine were significantly higher following intracranial injection than after intravenous administration. Consistent with these findings, Bleu Patente penetrated deeply into the cerebral cortex of sheep after a 24-hour intraventricular infusion. At the end of a 24-hour intraventricular infusion of 20 mg gemcitabine in sheep, mean gemcitabine concentrations reached 1,415 {micro}g/L in cerebrospinal fluid and 850 {micro}g/kg in brain tissue. These concentrations exceeded the IC90 values of gemcitabine for A172, U87-MG, and U118-MG human glioblastoma cell lines, as determined in vitro after 24 hours of incubation. We hypothesize that Bleu Patente dye and gemcitabine circumvent the blood-brain barrier (BBB) by utilizing the glymphatic system. Tolerance of a single 24-hour intraventricular infusion of gemcitabine at doses of 5, 10, and 20 mg was good. Taken together, these encouraging preclinical results support the resumption of Phase I clinical trials evaluating intraventricular infusion of gemcitabine in patients with refractory primary or secondary brain tumors.

Human salivary stem/progenitor cell (hS/PC)-loaded hyaluronic acid (HA)-based hydrogels, termed 3D-salivary tissue constructs (3D-ST), hold great promise for restoring salivary gland function post-radiation injury. Here, we developed a next-generation 3D-ST using heparin-modified HA and bioactive peptide-modified hydrogels. This new formulation enables controlled pre-loading and localized presentation of heparin-binding growth factors prior to surgical implantation, providing opportunities to enhance in vivo hS/PC bioactivity. To model clinically relevant radiation injury, we established an athymic rat model subjected to computed tomography (CT)-guided fractionated radiation, resulting in hallmark features of radiation-induced salivary dysfunction. Over 60-days post-irradiation, glands exhibited progressive loss of acini, increased fibrosis, and disruption of endothelial, neuronal, and myoepithelial compartments. Within this injured environment, a surgical pocket was created to precisely implant 3D-STs to assess graft performance. Fluorescent labeling of the 3D-STs enabled longitudinal tracking post-implantation. Over 14 days, implanted 3D-STs remained structurally stable within irradiated glands, and hS/PCs remained viable without evidence of local inflammatory responses. Compared to non-injured glands, the irradiated microenvironment suppressed hS/PC proliferation and phenotype, indicating alterations in the irradiated local tissue negatively impact hS/PC bioactivity. In addition, host neurovascular migration into the 3D-ST was majorly restricted in irradiated glands, providing new opportunities to enhance biointegration. Overall, this work establishes a reproducible preclinical framework for assessing hydrogel biocompatibility and stability, cell bioactivity, and host-graft biointegration prior to scale up into preclinical large animal models. This study has successfully established a tractable approach for improving 3D-ST formulations to enhance hS/PC expansion, differentiation, and biointegration following implantation into radiation-injured beds.

Manganese neurotoxicity, arising from environmental overexposure or inherited transporter disorders due to pathogenic variants in SLC30A10 and SLC39A14, leads to manganism, a debilitating Parkinsonian movement disorder. Alhtough chelation therapy can partially reverse neuropathology, current clinical practice relies on intravenous CaNa2EDTA, which is burdensome and poorly suited for long-term use. Consequently, there remains a significant unmet need for more effective, orally bioavailable chelators. This study aimed to establish and validate a pipeline for identifying and assessing novel ligands that attenuate manganese neurotoxicity and support preclinical translational development. Based on the structural features of manganese-based MRI contrast agents, we selected two chelators, N-picolyl-N,N',N'-trans-1,2-cyclohexylenediaminetriacetic acid (H3PyC3A) and ethylenediaminetetraacetic acid-benzothiazole aniline (H4EDTA-BTA), and their methyl ester derivatives, Me3PyC3A and Me4EDTA-BTA. These were evaluated in vivo using zebrafish (slc39a14U801/U801) and mouse (Slc30a10KO/KO) models of manganese overload. H3PyC3A and Me3PyC3A demonstrated greater manganese-mobilizing efficacy than CaNa2EDTA, improving locomotor behavior in slc39a14U801/U801 zebrafish. In Slc30a10KO/KO mice, intravenous administration confirmed selective in vivo chelation of excess manganese over physiological concentrations of zinc and copper. Although oral bioavailability was low (<1%), long-term oral administration of H3PyC3A modestly reduced liver and brain Mn accumulation, suggesting an added benefit of oral administration via gastrointestinal chelation. This integrated in vitro to in vivo pipeline provides a robust and scaleable approach for the development of next-generation Mn chelators. Slc39a14U801 loss-of-function zebrafish enable high throughput identification of candidate compounds while Slc30a10KO/KO mice offer a clinically relevant disease model for pharmacokinetic profiling and proof-of-concept validation.

Antibody-based therapeutics have revolutionized disease treatment, and recent advances in messenger RNA (mRNA) technologies have opened new opportunities for their intracellular production. In particular, in vitro-transcribed mRNA encapsulated in lipid nanoparticles (LNPs) enables targeted delivery to specific cells, where it can enable the synthesis of therapeutic antibodies with prolonged half-lives in a cost-effective manner. Despite rapidly growing experimental data, a modeling framework that integrates mRNA delivery, intracellular expression kinetics, and whole-body antibody disposition remains unavailable. To address this gap, we extended a Physiologically Based Pharmacokinetic model with a novel multiscale layer describing mRNA trafficking, cellular uptake, translation, and degradation. The integrated model was calibrated and validated using five datasets of mRNA-based cancer therapeutics, demonstrating strong predictive performance for the biodistribution of mRNA-encoded antibodies. The newly introduced mRNA layer, while minimally parameterized, effectively represents complex intracellular and systemic processes, enabling quantitative investigation of antibody biodistribution, optimization of dose scheduling, and providing an initial framework for future exploration of how LNP-mRNA formulation influences delivery and pharmacokinetics.

BackgroundPrevious studies evaluated large language model (LLM) performance on the American Society of Nuclear Cardiology (ASNC) Board Preparation Exam. Without domain-specific context, the best model (GPT-4o) achieved 63.1%, below the estimated 65% passing threshold and the 78% mean score of human fellows-in-training (FITs). Providing textbook context improved GPT-4o to 73.8% on text-only questions, but still fell short of human trainees. Whether next-generation LLMs with retrieval-augmented generation (RAG) can exceed this gap is unknown. MethodsClaude Opus 4.7 and GPT-5.5 were administered all 168 questions (141 text-only, 27 image-based) from the 2023 ASNC Board Preparation Exam across 5 iterations each, using RAG with a nuclear cardiology textbook, companion atlas, and ASNC clinical guidelines. Claude used local FAISS-based semantic retrieval; GPT-5.5 used Azures cloud-hosted vector store. Performance was compared to prior LLM results and 13 human FITs. ResultsAcross 5 iterations, Claude Opus 4.7 achieved a mean accuracy of 86.3% {+/-} 1.4% (text 88.8%, image 73.3%). GPT-5.5 achieved 86.7% {+/-} 2.2% (text 88.5%, image 77.0%) but refused a mean of 12.2 questions (7.3%) per iteration due to safety filters. Both models surpassed the human FIT mean (78.0%) and the estimated passing threshold. Compared to GPT-4o without context (63.1%), this represents a 23-percentage-point improvement in 18 months. ConclusionNext-generation LLMs with RAG now surpass average human trainee performance on nuclear cardiology board preparation questions, suggesting significant potential as educational tools and knowledge-reference aids in cardiovascular imaging. Condensed AbstractAcross 5 iterations each, Claude Opus 4.7 and GPT-5.5 with retrieval-augmented generation achieved mean accuracies of 86.3% and 86.7% on the 2023 ASNC Board Preparation Exam (168 questions), both surpassing the mean human fellow-in-training score of 78%. GPT-5.5 refused a mean of 12.2 questions (7.3%) per iteration due to safety filters. These results represent a 23-percentage-point improvement over the best prior LLM without context (63.1%), demonstrating that RAG-enhanced LLMs have reached human-level proficiency in nuclear cardiology knowledge. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/26352768v2_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@5f2465org.highwire.dtl.DTLVardef@4e80d3org.highwire.dtl.DTLVardef@1ebbb93org.highwire.dtl.DTLVardef@167d3c1_HPS_FORMAT_FIGEXP M_FIG C_FIG Overview of the three-study research arc evaluating LLM performance on the 2023 ASNC Board Preparation Exam. Study 1 (2024) tested four LLMs without context (best: GPT-4o, 63.1%). Study 2 (2025) added textbook context to GPT-4o (73.8%). Study 3 (2026, current) evaluated Claude Opus 4.7 and GPT-5.5 with retrieval-augmented generation across 5 iterations each (mean 86.3% and 86.7%, respectively), both surpassing the human fellow-in-training mean of 78%. Right panel shows the performance scale with key thresholds.

Osteosarcoma (OS) is the most prevalent primary bone malignancy in children and adolescents; however, therapeutic outcomes remain suboptimal due to tumor heterogeneity, chemoresistance, and inadequate immune activation. Doxorubicin (Dox), the standard therapy that induces immunogenic cell death, has its efficacy compromised by the immunosuppressive tumor microenvironment (TME). While interleukin-12 (IL-12) can activate and recruit various immune cells, making it an attractive combination partner, its systemic delivery is severely limited by dose-limiting toxicity. We have previously reported that intravenous injection of A3 collagen binding domain (CBD) of von Willebrand Factor preferentially accumulates into the TME of various tumor models enriched in collagen I and III. Furthermore, CBD-fused IL-12 (CBD-IL-12) demonstrated superior therapeutic effects against various cancer models compared to unmodified IL-12 due to its collagen-targeted delivery and the resulting tumor-localized inflammation. Given that the OS TME also exhibits higher collagen I and III expression compared to normal bone, we hypothesized that a CBD-IL-12 fusion protein could showcase potent anti-tumor efficacy in OS via tumor-specific accumulation. Here, we demonstrated that CBD-IL-12 exhibited 4-fold enhanced tumor accumulation compared to unmodified IL-12 and increased cytotoxic T cell infiltration by 2.2-fold within the immune-cold microenvironment in a mouse model of OS. The combination of CBD-IL-12 with Dox significantly prolonged median survival in two independent murine OS models. This coordinated approach utilizing Dox coupled with precision-targeted IL-12 immunotherapy represents a clinically translatable strategy that overcomes the inherent limitations of single-agent treatments for OS. HighlightO_LICollagen-targeted IL-12 increases tumor accumulation in osteosarcoma. C_LIO_LIThe collagen-targeted IL-12 synergizes with doxorubicin in osteosarcoma models. C_LIO_LICombination therapy enhances T cell differentiation and activates innate immunity. C_LI

(1) Background: Brain cancer is the ninth leading cause of cancer death in the US, with approximately 76,000 newly diagnosed cases annually. Studies show that at time of diagnosis, up to six-months post-treatment, 50%-80% of brain cancer survivors (BCS) report cognitive dysfunction. Mild cognitive impairment (MCI) has gained increasing attention as a persistent disability experienced by up to 75% of all BCS, which affects memory, concentration, executive function, etc. Studies show cognitive training with computerized gaming as improving cognitive function for patients with stroke, dementia, and Parkinsons. It is of significant clinical interest to develop innovative interventions that reduce MCI. Aim: To improve cognitive performance of BCS suffering with MCI by evaluating the feasibility, acceptability and effect of a Virtual Reality Cognitive Rehabilitation Training (VR-CRT) platform during four weeks of cognitive training. (2) Methods: We employed a quasi-experimental pretest/posttest non-randomized/non-blinded single-arm design for 4 weeks, with an experimental group (n=6, after attrition) using VR-CRT. Participants were selected based on convenience sampling using the electronic medical record to identify qualified patients, guided by inclusion/exclusion criteria. Feasibility was defined by retention as >80%, with usability testing using the System Usability Scale (SUS) and NASA-TLX surveys. The Hopkins Verbal Learning Test (HVLT), Controlled Oral Word Association (COWA) test, and Trail Making A-B (TM-A/B) test were used to measure cognitive performance, comparing baseline to post week-four. (3) Results: The feasibility criteria of >80% was met. All SUS and NASA scores were in the higher index, suggesting a high degree of usability, with low workload demand. For effect, the COWA findings showed a significant improvement (41.38%), with a paired sample T-Test confirming that the participants COWA scores improved significantly from pre- to post-intervention (p = 0.03), indicating enhanced verbal fluency and executive functioning after intervention. HVLT (combined) showed improvements of 18.75% for Form A and 11.32% for Form B, which also showed a significant improvement (p = .04) in the retention discrimination index from pre- to post-test. The TM-A/B test showed an improvement (25.97%), suggesting that the participants spent less time completing both parts A and B, but was not statistically significant. (4) Conclusion: This study fulfilled our aim to demonstrate modest to significant cognitive improvement using VR-CRT with brain cancer patients with MCI. Despite the small sample size, we believe the use of virtual reality will lead to important advances for patients with MCI, particularly the frontal lobe brain region, expressed in executive function.

Background: Growing evidence suggests that urinary {beta}-amyloid precursor protein (A{beta}PP) fragments can serve as an early screening biomarker for mild cognitive impairment and dementia. However, in reality, older adults, regardless of the presence of cognitive decline, often suffer from multiple age-related conditions and are on multiple medications. How these comorbidities and treatments affect the performance of early diagnostic biomarkers remains unclear. Methods : This study further validated the sensitivity, specificity, and clinical value of the Qankorey (R) urinary {beta}-amyloid protein detection kit in early dementia screening through a randomized community screening (n=51187) conducted in Changsha, and a multicenter case-control study conducted at Yuquan Hospital (Tsinghua University), Tiantan Hospital (Capital Medical University), Beijing Friendship Hospital, Zibo 148 Hospital (Shandong), and the Third People's Hospital of Yunnan Province. The multicenter case-control study included 898 participants, comprising 266 healthy, age-matched controls without any comorbidities, 167 patients with mild cognitive impairment/Alzheimer's disease (MCI/AD), and 465 non-AD patients with various comorbidities and age-related diseases. Results: The kit showed a significant age-dependent positive rate in both men and women in Changsha, increasing from 6.29% to 15.40%. The number of weakly positive/positive/negative individuals in the healthy group, non-AD group, and MCI/AD group were 8/12/246 (positive rate 7.52%), 41/16/409 (12.23%), and 77/44/46 (72.46%), respectively, with a Kappa value of 0.669, indicating that the method performed well in the clinical diagnosis of MCI/AD, consistent with previously published results. Among the 8 weakly positive healthy subjects, 6 were found to have brain abnormalities by MRI/CT examination. Comorbidity analysis showed that memory decline was the most significant risk factor (P=9.6 x 10^-23, Fisher's exact test), followed by dizziness (P=1.3 x 10^-14;) , hyperlipidemia (P=3.2 x 10^-12) , history of stroke (P=0.0011), and hypertension (P=0.0058). Treatment analysis showed that cardiovascular drugs and antithrombotic drugs significantly reduced the risk of dementia (P values were 0.0061 and 0.0081, respectively), followed by hypoglycemic drugs (P=0.0358). For AD patients, those receiving only memantine showed a slightly lower positive test rate (P=0.0532). Conclusion: Our findings confirm the diagnostic value of urinary {beta}-amyloid protein detection in MCI and AD-related dementia. Furthermore, this kit can be used in practical clinical applications to assess the risk of cognitive decline and treatment efficacy across various diseases.

Computed tomography is the largest contributor to population radiation dose from medical imaging, yet no diagnostic reference levels (DRLs) have been published from Kosovo or the Western Balkans. This retrospective audit analyzed all CT examinations performed on a 128- slice scanner at the University Clinical Centre of Kosovo between January and March 2026. After exclusions, 1,535 acquisitions from 1,092 patients across nine examination categories were analyzed. Local DRLs were defined as the 75th percentile and compared against German (BfS 2022) and Turkish (Kahraman et al., 2024) reference values. Head CT (n = 590) demonstrated CTDIvol 4.7% below the BfS DRL yet scan length 98.5% above the orientation value (median 25.8 vs 13 cm). Abdomen-pelvis CTDIvol matched the BfS reference while scan length exceeded it by 28%. Coronary CTA showed CTDIvol +377%, consistent with retrospective ECG gating. Excess scan length, not CTDIvol, is the major driver of elevated dose at this institution. The identified excesses are correctable through technologist landmarking training, protocol review, and enabling iterative reconstruction.