In the literature: May 2026 highlights

Bentivoglio, Davide, et al. “Femur Fracture Risk Assessment in Patients with Lytic Metastases Using CT-Based Finite Element Models and Bone Crack Simulations Technique: D. Bentivoglio et al.” Annals of Biomedical Engineering (2026): 1-12.

Femoral bone metastases represent a frequent and severe complication in patients with advanced solid tumours. Although fracture risk assessment commonly relies on Mirels’ score, its limited specificity often leads to unnecessary surgical interventions. Patient-specific finite element (FE) models have shown improved accuracy; however, current approaches vary widely in methodology and rarely capture the full fracture process. This study investigates for the first time the application of a linear FE approach based on an incremental element deletion technique to simulate both fracture initiation and propagation in femurs with lytic metastases.

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Turlo, Agnieszka, et al. “Exhaled breath volatiles for asthma diagnosis: discovery and validation in untreated but symptomatic patients.” Scientific Reports (2026).

Approximately 30% of people with a clinical diagnosis of asthma do not have the condition. Exhaled volatile organic compounds (VOCs) hold promise for non-invasive asthma testing; however, discovery of breath biomarkers is confounded by high biological and technical variability. We collected repeated breath samples from symptomatic patients being tested for asthma before starting treatment. Background samples were collected immediately before patient sampling to characterize VOCs present in the preconditioned inspired airstream. VOCs were measured by thermal desorption-gas chromatography-mass spectrometry. Data from two cohorts (n = 62, 53) were processed independently and used as training and validation datasets. VOCs were classified as breath-enriched or ambiguous based on comparison between breath and background abundance using Wilcoxon test and log fold change. Associations between breath VOCs and diagnosis were tested with univariate mixed-effect models and multivariate classification models. Here we show that background has significant effect on breath VOC abundance in 60% of identified compounds. Breath VOCs show high inter-session and inter-patient variability, reflected by increase in multivariate model classification error in cross-validation (37%) and validation (52%) cohorts. Among VOCs positively associated with asthma, 30% are breath-enriched. Ethyl butanoate, 2-methylfuran and 3-methylpentane show consistent discrimination performance across the cohorts. When used in conjunction with clinical tests, these breath VOCs have comparable contribution to asthma prediction accuracy to established clinical diagnostics such as fractional exhaled nitric oxide. Measuring exhaled VOCs could add value to diagnosis of asthma based on routine clinical tests. However, developing measures to limit technical variation in breath analysis is needed to support discovery and clinical translation of such biomarkers.

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Bafna, Mehul, et al. “Automated segmentation of hepatic vessels and lobules in whole-slide images using U-net models.” Frontiers in Bioinformatics 6 (2026): 1713736.

Automated analysis of hepatic vascular structures and lobules within whole-slide histological images is critical for ensuring accurate and timely morphometric evaluations and facilitating advancements in computational liver histology. Nonetheless, the intricate morphology of the tissue, variability in staining techniques, and the requirements for standard high-resolution images present substantial challenges to the precision of segmentation processes. We present a robust deep-learning pipeline using adaptive patch extraction and specialized nnU-Net architectures for segmenting vessels, bile ducts, and lobules in Glutamine Synthetase and Picro-Sirius-Red stained porcine liver sections. Our architecture incorporates a weight-boosted nnU-Net framework with an adaptive, performance-based weight adjustment mechanism to effectively manage class imbalances and improve the detection of smaller vascular structures. The model was trained on four annotated whole-slide images and validated through comprehensive testing on eight additional independent slides. Geometric and intensity-based data transformations enhanced the robustness and generalizability of the segmentation models. Evaluations conducted through five-fold cross-validation, as well as assessments utilizing independent test datasets, resulted in Dice similarity scores: 0.968 for lobules, 0.795 for central veins, 0.895 for hepatic arteries, 0.665 for portal veins, and 0.694 for bile ducts. The developed segmentation pipeline additionally supports comprehensive morphometric analyses of structural parameters, including number and size (diameter, area) of vascular structures, bile ducts, and lobules; for example, the diameter of hepatic arteries ranges between 20-90 µm. These findings underscore the practical relevance of adaptable segmentation frameworks in advancing computational histological analysis of liver tissue.

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Simeoni, Damiano, et al. “Development of an in silico hybrid model for scoliosis correction using Ansys Motion.” Computer Assisted Surgery 31.1 (2026): 2666465.

Surgical techniques for correcting scoliotic deformities are continuously evolving, and computer modeling has become a valuable tool to support surgeons in testing and optimizing spinal instrumentation and corrective strategies. This study introduces a novel hybrid model capable of simultaneously computing rigid-body dynamics during surgical correction and estimating mechanical stresses within deformable structures. The model was developed using Ansys Motion, an integrated simulation environment that enables coupled multibody dynamics and finite element analyses to simulate complex interactions between rigid and flexible bodies. As a case study, spinal correction maneuvers were simulated on a simplified scoliotic spine model with vertebral bodies derived from publicly available CT scan data of a female subject. Simplified surgical instrumentation, representing commercially available systems, was applied to the T2-L1 segment and included a concave rod contoured to the desired sagittal profile. Different implant density patterns and corrective maneuver sequences were also investigated. The simulations of rod rotation followed by translation showed a deformity correction of approximately 39%. This correction was less pronounced when the number of instrumented vertebrae was limited to six or three, where a decrease in the estimated maximum pullout forces at the screw-vertebra interface was also observed. The reduction in forces transmitted by the screws during correction led to a decrease in the mechanical stress experienced by the intervertebral disks, as transmitted through the vertebral bodies. This effect may vary slightly depending on how the corrective maneuvers are performed. The preliminary results are promising and highlight the potential of this simulation tool for modeling the mechanical behavior of spinal deformities.

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Tomek, Jakub, et al. “T-world virtual human cardiomyocyte. II. organ-scale simulations and applications.” Circulation Research 138.10 (2026): e328123.

Mechanistic cardiac simulations are increasingly used in research, pharmaceutical development, and regulatory science, yet most existing human cardiomyocyte models lack the generality required for predictive translation across scales. Our recently developed T-World model overcomes this barrier by reproducing all major cellular arrhythmia mechanisms and showing comprehensive agreement with experimental and clinical data. Here, we aimed to demonstrate the utility of T-World for organ-level and translational research, from ionic mechanisms of arrhythmogenesis to emergent whole-heart physiology.

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