Computer Methods in Biomechanics and Biomedical Engineering最新文献

{"title":"Coexistence of horizontal bone loss and dehiscence with the bundle and conventional fiber post: a finite element analysis.","authors":"Deniz Yanık, Nurullah Türker, Ahmet Mert Nalbantoğlu","doi":"10.1080/10255842.2024.2423266","DOIUrl":"10.1080/10255842.2024.2423266","url":null,"abstract":"<p><p>Horizontal bone loss (HBL) and dehiscence are common supportive tissue defects. This study evaluated the stress distribution in the presence of HBL or dehiscence and two types of fiber posts. Twelve premolars that were endodontically treated (Model-E), restored with conventional (Model-C), and bundle (Model-B) post were modeled. Bone defects were created as control (Model-1), with 4 mm (Model-4) and 8 mm (Model-8) HBL, and dehiscence involving two-thirds of the root (Model-D). HBL was included in all aspects of the models, while dehiscence was confined to the buccal aspect. The models were subjected to a 200 N force, and von Mises stress was analyzed. Model-B1 showed higher stress than Model-C1 but was more homogeneous. In Model-D, the stress was limited to the area without bone and only occurred at the buccal aspect. The highest stress was observed in Model-B8. The presence of a post caused a 2-5.8 times increase in stress. When the crown-root ratio was 1:0.8, stress was in the coronal two-thirds of the root, while at a ratio of 1:0.3, stress was distributed throughout the entire root. Bundle post with 8 mm HBL increased the stress 5.8 times. HBL resulted in stress extending beyond the marginal bone, while dehiscence did not.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1007-1022"},"PeriodicalIF":1.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of constitutive law for 3d-printed bioresorbable thermosensitive polymer to design medical devices for soft tissue reconstruction.","authors":"Xuan-Tien Kévin Trinh, Pauline Lecomte-Grosbras, Jean-François Witz, Olivier Mayeur, Shengheng Cao, Jaime Destouesse, François Lesaffre, Michel Cosson, Tien-Tuan Dao","doi":"10.1080/10255842.2024.2427114","DOIUrl":"10.1080/10255842.2024.2427114","url":null,"abstract":"<p><p>Breast cancer concerns 1 in 8 women in the world and is followed in 40% of cases by a mastectomy. Only 14% of women receive reconstructive surgery because of unfavorable clinical issues. The need of innovative tissue engineering devices leads Lattice Medical company to bring a new 3D-printed device, allowing the regeneration of soft tissue in order to replace the withdrawn breast. The implant, based on TEC (tissue engineering chamber) and fat-flat surgical technique, is constituted with bioresorbable thermosensitive materials to be fully absorbed by the body in several months, once the regeneration process is completed. In this industrial context, we need to assess some properties for predictive simulation: the TEC mechanical and biological properties over time, its sensitivity to implantation in the body temperature, its batch raw material variability and its structural 3D-printed behavior. This would lead to a more enlightened numerical design and topological optimization work. To do so, mechanical testing are conducted to gather necessaries information for fully border the behaviour of the material and eventually the impact of the process on the final prosthesis. Then, the G'sell Law is chosen to model the mechanical behaviour of the material taking into account all particularities of this medical case. Finally, the behaviour law is used in Finite Element Method (FEM) in a compression simulation to compare with experimental results which find good similarity in the mechanical response.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1118-1129"},"PeriodicalIF":1.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142649477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical effect of taper position in abutment hole and screw taper angles on implant system and peri-implant tissue: a finite element analysis.","authors":"Hu Hou, Jianguo Zhang, Song Huang, Fengling Hu, Youcheng Yu, Liang Song","doi":"10.1080/10255842.2024.2423253","DOIUrl":"10.1080/10255842.2024.2423253","url":null,"abstract":"<p><strong>Purpose: </strong>The study aimed to investigate the mechanical effects of the taper position in the abutment hole and the screw taper angles on the implant system and peri-implant tissue using finite element analysis.</p><p><strong>Methods: </strong>Four taper positions (L1, L2, L3, L4) in the abutment hole were established using 3D software and five screw taper angles (30°, 60°, 90°, 120°, 180°) were set.</p><p><strong>Result: </strong>Taper position significantly affects the stresses in the implant system. The 30° and 180° angles (L4 position) showed less stress than other angles.</p><p><strong>Conclusion: </strong>Elevated taper position and reasonable taper angle are beneficial in reducing the stress in the implant system.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"998-1006"},"PeriodicalIF":1.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the active ingredients and mechanisms of Liujunzi decoction in treating hepatitis B: a study based on network pharmacology, molecular docking, and molecular dynamics simulations.","authors":"Qing Ma, Wenjun Li, Wenying Wu, Mei Sun","doi":"10.1080/10255842.2024.2427117","DOIUrl":"10.1080/10255842.2024.2427117","url":null,"abstract":"<p><p>Liujunzi decoction (LJZD) is commonly used to treat hepatitis B virus (HBV), though its active ingredients and mechanisms are not fully known. This study identified core targets and active components of LJZD for treating hepatitis B (HB) through network pharmacology, molecular docking, and molecular dynamics simulation. Screening from databases yielded 533 active components, 2619 targets for LJZD, and 2910 for HB, with 891 intersecting targets. STRING and CytoHubba analyses identified AR and VDR as core targets, with key pathways including PI3K-Akt and MAPK. The findings clarify LJZD's multicomponent, multitarget mechanisms, supporting its clinical application for HB treatment.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1145-1169"},"PeriodicalIF":1.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reduction of material groups for vertebral bone finite element simulation: cross comparison of grouping methods.","authors":"Daniel Strack, Nithin Manohar Rayudu, Jan S Kirschke, Thomas Baum, Karupppasamy Subburaj","doi":"10.1080/10255842.2024.2422901","DOIUrl":"10.1080/10255842.2024.2422901","url":null,"abstract":"<p><p>In patient-specific biomechanical modeling, the process of image-to-mesh-material mapping is important, and various strategies have been explored for assigning the number of groups of unique material properties to the mesh. This study aims to cross-compare different grouping strategies to identify the minimum number of unique groups necessary for accurately calculating the fracture load of vertebral bones. We analyzed 12 vertebral specimens by experimentally determining the biomechanical fracture load and acquiring corresponding CT scans. After geometry extraction and meshing, we applied commonly used fixed-value strategies for reducing the number of unique groups, such as Modulus Gaping and Percentual Thresholding. Additionally, we introduced a patient-specific adaptive grouping method based on K-means clustering, which allowed us to maintain a consistent number of groups of unique material properties across the study. A total of 204 simulations were performed, achieving a potential 98% reduction in the number of individual material parameters while maintaining a strong correlation with experimental results when utilizing Percentual Thresholding or Adaptive Clustering, compared to Modulus Gaping. The findings demonstrate the feasibility of significantly reducing simulation complexity while maintaining the accuracy of patient-specific models that strongly correlate with experimental results. This reduction enables efficient processing of patient-specific biomechanical models derived from image data, offering potential benefits for clinicians, particularly in resource-constrained settings.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"941-951"},"PeriodicalIF":1.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of physics-informed neural networks for ground reaction force estimation in human gait.","authors":"Sekar Anup Chander, Siddharth Garg, Vhatkar Dattatraya Shivling, Ashish Singla","doi":"10.1080/10255842.2026.2645662","DOIUrl":"https://doi.org/10.1080/10255842.2026.2645662","url":null,"abstract":"<p><p>Ground reaction force (GRF) estimation during gait is essential for analyzing human locomotion. Though several conventional machine learning models have been proposed for GRF estimation, their dependence on data often limits generalizability and prediction accuracy. To address these limitations, the present study explores the feasibility of Physics-Informed Neural Networks (PINNs) for GRF estimation. The developed PINN model was evaluated visually using plots and quantitatively using Root Mean Square Error (RMSE). Results indicate that applying PINN led to a significant RMSE reduction across all subjects, with improvements ranging from 67% to 89%, thereby highlighting the effectiveness of the proposed approach.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-13"},"PeriodicalIF":1.6,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel way to represent weekly blood sugar data to increase user understanding and control.","authors":"Peter J Kyberd, Alix Chadwell, Matthew Lee, Farooq Othman Farooq Al Safi","doi":"10.1080/10255842.2026.2645166","DOIUrl":"https://doi.org/10.1080/10255842.2026.2645166","url":null,"abstract":"<p><strong>Background: </strong>Tight control of blood glucose is associated with good health. This is easier to achieve with continuous glucose monitoring. However, patients need to be able to interpret the data without reference to experts. Simplifying the visual display, can simplify decisions. Appropriate display of data can lead to improved control and health.</p><p><strong>Methods: </strong>A novel method to display data: Mapping time series data onto a spiral - one day is a single turn, a week is seven. The colour of the line is related to the blood sugar level.</p><p><strong>Results: </strong>Plots which are simpler and easier to interpret.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-5"},"PeriodicalIF":1.6,"publicationDate":"2026-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling and estimation of ablation catheter contact force under blood flow disturbance.","authors":"Yifan Liang, Zhi Hu, Lin Sun, Hanping Zhu","doi":"10.1080/10255842.2026.2642808","DOIUrl":"https://doi.org/10.1080/10255842.2026.2642808","url":null,"abstract":"<p><p>Real-time, accurate estimation of catheter tip-atrial tissue contact force (CF) is essential for safe, effective robot-assisted radiofrequency catheter ablation (RFCA). Conventional models often neglect intracardiac hemodynamics or reduce them to steady flow, missing cardiac-cycle velocity variations and pulsatile disturbances, thus causing large errors. This study proposes a CF estimation framework using cubic Bezier splines for catheter morphology, a sinusoidal velocity model for pulsatile blood flow, and a quasi-static Euler-Bernoulli beam moment equilibrium with distributed hydrodynamic loads. CF is inversely estimated via least-squares and the Moore-Penrose pseudoinverse. FE and in-vitro results show improved dynamic-condition accuracy and physiologically relevant intraoperative feedback.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-14"},"PeriodicalIF":1.6,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147522685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing drug synergy in malignant diseases with deep architecture optimization algorithms.","authors":"Pooja Rani, Kamlesh Dutta, Vijay Kumar","doi":"10.1080/10255842.2026.2646310","DOIUrl":"https://doi.org/10.1080/10255842.2026.2646310","url":null,"abstract":"<p><p>Malignant diseases remain one of the leading causes of death globally. Drug synergy has emerged as an effective approach for treating malignancy, offering improved therapeutic outcomes. Although techniques like clinical trials and high-throughput drug screening are commonly used to discover promising synergistic drug pairs, but they are time consuming and expensive. With the evolution of artificial intelligence, deep learning models are increasingly being applied to identify synergistic drug combinations. These models rely heavily on large-scale datasets, where size of dataset and hyperparameter selection play a pivotal role in the performance of model. However, determining the optimal hyperparameters for drug synergy models is a complex and time-intensive task, typically involving multiple iterative experiments. As a result, there is growing attention on optimizing hyperparameters for these models. This study emphasizes the role of hyperparameter optimization algorithms (HOAs) in evaluating how different optimization strategies and hyperparameter choices influence model effectiveness. By optimizing the hyperparameters, we achieved good accuracy in predicting drug synergy. Our findings highlight that the effectiveness of hyperparameter optimization is highly task- and dataset-dependent.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-18"},"PeriodicalIF":1.6,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147516383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced biomechanical assessment of mitral valve prosthesis using fluid-structure interaction modeling.","authors":"Niki Babaghorbani, Kamran Hassani, Sattar Jedari Salami, Shahrokh Shojei, Pedram Tehrani","doi":"10.1080/10255842.2026.2648677","DOIUrl":"https://doi.org/10.1080/10255842.2026.2648677","url":null,"abstract":"<p><strong>Background and objective: </strong>Mitral valve disease, particularly mitral regurgitation (MR), is among the most common valvular heart diseases, often requiring prosthetic valve replacement to restore normal hemodynamics and preserve myocardial function. Despite advances in prosthetic technologies, predicting patient-informed biomechanical performance remains challenging due to complex blood-structure interactions. This study aimed to develop a patient-informed fluid-structure interaction (FSI) model to evaluate the biomechanical and hemodynamic performance of a mechanical mitral valve prosthesis.</p><p><strong>Methods: </strong>A patient-informed FSI model of the left ventricle (LV) and mitral valve prosthesis was developed and validated using echocardiographic data and numerical simulations. The model analyzed the behavior of a St. Jude mechanical mitral valve implanted in a 46-year-old male patient and compared it with a healthy LV model. Hemodynamic and mechanical parameters, including flow velocity, shear stress, pressure gradient, and von Mises stress, were quantified.</p><p><strong>Results: </strong>The prosthetic valve restored global flow direction, stroke volume, and ventricular wall displacement, consistent with echocardiographic data. In the healthy LV, peak inflow velocities reached 0.6-0.7 m/s during early diastole with transient shear stress (∼0.08 s). The prosthetic valve produced higher inflow velocities (up to 6.5 m/s) and prolonged shear stress (∼0.08-0.18 s), indicating potential hemolysis risk. Pressure gradients peaked at ∼13 mmHg, and stress analysis showed preserved central motion with localized stress near the prosthesis.</p><p><strong>Conclusions: </strong>Patient-informed FSI modeling enables accurate, noninvasive assessment of post-operative hemodynamics and mechanical performance, identifying risks such as elevated shear stress and hemolysis while supporting optimized prosthetic design and personalized surgical planning.</p>","PeriodicalId":50640,"journal":{"name":"Computer Methods in Biomechanics and Biomedical Engineering","volume":" ","pages":"1-15"},"PeriodicalIF":1.6,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147522682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}