Annals of Biomedical Engineering最新文献

{"title":"Back Muscle Activity During One Hour of Vertical Vibration Simulating a Helicopter Flight.","authors":"Ana I Lorente, Robert S Salzar","doi":"10.1007/s10439-025-03868-y","DOIUrl":"https://doi.org/10.1007/s10439-025-03868-y","url":null,"abstract":"<p><strong>Purpose: </strong>Back pain is detected at high rates in helicopter aircrew members, leading in some cases to flying incapacitations. The cause of this pain remains unclear in this population. The goal of this research is to better understand how muscles respond over time (1 h) in a seat that vertically vibrates simulating a helicopter flight.</p><p><strong>Methods: </strong>Surface electromyography (EMG) data at six locations (middle trapezius, erector spinae, longissimus, iliocostalis lumborum, and multifidus) was collected in 14 subjects during 1 h of vertical whole-body vibration (0.2 g at 4 Hz). To simulate a helicopter flight, a rigid seat with the dimensions of an H-60 helicopter was used, including pedals and hand controls of a flight simulator, HGU-56/P helmets and a 5-point harness. The EMG readings were collected at 0, 15, 30, 45, and 60 min during the vibrational exposure.</p><p><strong>Results: </strong>Low muscle activity was seen in all the tracked muscles with insignificant changes over time (middle trapezius and erector spinae increased the EMG amplitude less than 0.5 %MVC, longissimus decreased the median frequency 3.75 Hz). Muscle activity was below 10 %MVC (maximum voluntary contraction) in most of the cases, with average values between 2 and 7 %MVC. The average median frequency ranged from 33 Hz to 53 Hz.</p><p><strong>Conclusion: </strong>The muscle activity of the back remained unaltered during the vibrational exposure of 1 h. A better understanding of how whole-body vibrations affect back muscles during flights would help in reducing the high prevalence of pain in aircrew members.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145197862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion Model-Based Design of Bionic Bone Scaffolds with Tunable Microstructures.","authors":"Jiading Chen, Shuwei Shen, Liang Xu, Zhiyuan Zheng, Xiaoyan Zou, Min Ye, Chi Zhang, Honghong Liu, Peng Yao, Ronald X Xu","doi":"10.1007/s10439-025-03847-3","DOIUrl":"https://doi.org/10.1007/s10439-025-03847-3","url":null,"abstract":"<p><strong>Purpose: </strong>In the clinical treatment of bone defects that exceed the critical size threshold, traditional methods using metal fixation devices, autografts, and allografts exhibit significant limitations. Meanwhile, bone scaffolds with minimal risks of secondary injury, low immune rejection are emerging as a promising alternative. The effective design of porosity, pore size, and trabecular thickness in bone scaffolds is critical; however, current strategies often struggle to optimally balance these parameters. Here, we propose a bionic bone scaffold design method that mimics multiple properties of natural cancellous bone using a diffusion model.</p><p><strong>Methods: </strong>First, we develop a classifier-free conditional diffusion model and train it on a Micro-CT (μCT) image dataset of porcine vertebral cancellous bone. The training model can produce personalized 2-dimensional images of natural-like bone with tunable microstructures. Subsequently, we stack images layer by layer to form 3-dimensional scaffolds, mimicking the CT/μCT image reconstruction process. Finally, computational fluid dynamics analysis is conducted to validate the scaffold models' fluid properties, while bioresin bone scaffold samples are 3D-printed for mechanical testing and biocompatibility assessment.</p><p><strong>Results: </strong>The three key morphological parameters of the generated images-porosity (50-70%), pore size (468-936 μm), and trabecular thickness (156-312 μm)-can be precisely and independently controlled. Fluid simulation and mechanical testing confirm scaffolds' robust performance in permeability (10⁻⁹ to 10⁻⁸ m²), average fluid shear stress (0.1-0.3 Pa), Young's modulus (14-fold adjustable range), compressive strength (9-fold adjustable range), and viscoelastic properties. The scaffolds also exhibit good biocompatibility, meeting the basic requirements for clinical implantation.</p><p><strong>Conclusion: </strong>These promising results highlight the potential of our method for the personalized design of scaffolds to effectively repair large bone defects.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145190721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Dynamics Simulations and Their Novel Applications in Drug Delivery for Cancer Treatment: A Review.","authors":"Begüm Sarac, Seydanur Yücer, Fatih Ciftci, Mansour Ghorbanpour, Esma Ahlatcioglu Ozerol","doi":"10.1007/s10439-025-03864-2","DOIUrl":"https://doi.org/10.1007/s10439-025-03864-2","url":null,"abstract":"<p><p>Molecular Dynamics (MD) simulations have emerged as a vital tool in optimizing drug delivery for cancer therapy, offering detailed atomic-level insights into the interactions between drugs and their carriers. Unlike traditional experimental methods, which can be resource-intensive and time-consuming, MD simulations provide a more efficient and precise approach to studying drug encapsulation, stability, and release processes. These simulations are essential for designing effective drug carriers and gaining a deeper understanding of the molecular mechanisms that influence drug behavior in biological systems. Recent research has highlighted the broad applicability of MD simulations in assessing different drug delivery systems, such as functionalized carbon nanotubes (FCNTs), chitosan-based nanoparticles, metal-organic frameworks (MOFs), and human serum albumin (HSA). FCNTs are known for their high drug-loading capacity and stability, while biocompatible carriers like HSA and chitosan are favored for their biodegradability and reduced toxicity. Case studies involving anticancer drugs, including Doxorubicin (DOX), Gemcitabine (GEM), and Paclitaxel (PTX), showcase how MD simulations can improve drug solubility and optimize controlled release mechanisms. Although the computational complexity of these simulations presents challenges, advances in high-performance computing and machine learning techniques are driving significant progress. These innovations are facilitating the development of more targeted and efficient cancer therapies. By combining MD simulations with experimental validation, researchers are enhancing predictive models and accelerating the creation of next-generation drug delivery systems.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145190687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical Surgical Process Modeling: Analysis of Workflow and Performance of Emerging Technologies in Image-Guided Spine Surgery.","authors":"Anshuj Deva, Tatiana A Rypinski, Parvathy Sudhir Pillai, Bhavin Soni, Owais Sarwar, Aaron C Milhorn, Aaron K Jones, Claudio E Tatsui, Laurence D Rhines, Robert Y North, Christopher Alvarez-Breckenridge, Justin E Bird, Jeffrey H Siewerdsen","doi":"10.1007/s10439-025-03855-3","DOIUrl":"https://doi.org/10.1007/s10439-025-03855-3","url":null,"abstract":"<p><strong>Background: </strong>Surgical process modeling (SPM) presents a rigorous ontology and useful means of understanding complex surgical workflows. Early-stage understanding of the potential benefit of emerging technologies can be gained with such an approach- for example, in image-guided spine surgery.</p><p><strong>Purpose: </strong>This work extends SPM ontology to a statistical framework for computational modeling and simulation, analyzing the effect of new technologies on quantitative outcomes. Two example use cases are detailed in spine surgery-target localization with long-length imaging and pedicle screw placement with intraoperative CT and navigation.</p><p><strong>Methods: </strong>The SPM ontology of phase, step, and activity was mapped to a directed graph depiction of workflow in which activities were described by statistical distributions in outcomes, parameterized and validated via retrospective and/or prospective studies, and structured within an SPM table and object-oriented computational framework. The approach was applied to quantify the influence of two example technologies in spine surgery: (1) long-length radiographic imaging for target localization (compared to conventional fluoroscopic level-counting); and (2) intraoperative CT and 3D navigation for pedicle screw placement (compared to conventional fluoroscopic guidance). Distributions in cycle time, radiation dose, and geometric accuracy were investigated, with clear depiction of median and outlier performance provided by 3D visualization.</p><p><strong>Results: </strong>Statistical SPMs yielded insight on complex workflows and the potential benefits of emerging technologies. For target localization, intraoperative long-length imaging reduced median cycle time from 15.5 min (for fluoroscopic level-counting) to 13.4 min and eliminated outliers associated with visibility of markers or human error. For pedicle screw placement, 3D navigation introduced an additional median ~ 15 min procedural overhead in planning and registration but reduced median procedure time from 229 min (for fluoroscopy guidance) to 180 min. 3D navigation also quantifiably improved the geometric accuracy of screw placement and reduced the frequency of pedicle screw breach (Grade C or worse).</p><p><strong>Conclusions: </strong>Statistical SPMs provide a valuable methodology to evaluate and communicate complex interventional workflows and the potential benefit of emerging technologies. Two SPM use cases were developed in the context of spine surgery and provided a basis for investigating the potential performance of emerging technologies, such as intraoperative imaging, navigation, robotic assistance, and augmented reality systems. As a framework for virtual clinical trials, statistical SPMs can provide insight on outcome measures that are difficult to evaluate in the laboratory and expensive / time-consuming to measure in prospective clinical studies.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145190729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gait-to-Contact (G2C): A Novel Deep Learning Framework to Predict Total Knee Replacement Wear from Gait Patterns.","authors":"Mattia Perrone, Scott Simmons, Philip Malloy, Vasili Karas, Catherine Yuh, John Martin, Steven P Mell","doi":"10.1007/s10439-025-03863-3","DOIUrl":"https://doi.org/10.1007/s10439-025-03863-3","url":null,"abstract":"<p><strong>Purpose: </strong>Total knee replacement (TKR) is the most common inpatient surgery in the US. Studies leveraging finite element analysis (FEA) models have shown that variability of gait patterns can lead to significant variability of wear rates in TKR settings. However, FEA models can be resource-intensive and time-consuming to execute, hindering further research in this area. This study introduces a novel deep learning-based surrogate modeling approach aimed at significantly reducing computational costs and processing time compared to traditional FEA models.</p><p><strong>Methods: </strong>A published method was used to generate 314 variations of ISO14243-3 (2014) anterior/posterior translation, internal/external rotation, flexion/extension, and axial loading time series, and a validated FEA model was used to calculate linear wear distribution on the polyethylene liner. A deep learning model featuring a transformer-CNN based encoder-decoder architecture was trained to predict linear wear distribution using gait pattern time series as input. Model performance was evaluated by comparing the deep learning and FEA model predictions using metrics such as mean absolute percentage error (MAPE) for relevant geometric features of the wear scar, structural similarity index measure (SSIM), and normalized mutual information (NMI).</p><p><strong>Results: </strong>The deep learning model significantly reduced the computational time for generating wear predictions compared to FEA, with the former training and inferring in minutes, and the latter requiring days. Comparisons of deep learning model wear map predictions to FEA results yielded MAPE values below 6% for most of the variables and SSIM and NMI values above 0.88, indicating a high level of agreement.</p><p><strong>Conclusion: </strong>The deep learning approach provides a promising alternative to FEA for predicting wear in TKR, with substantial reductions in computational time and comparable accuracy. Future research will aim to apply this methodology to clinical patient data, which could lead to more personalized and timely interventions in TKR settings.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145181801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models in Injury Prediction Tools: Simplifying User Interactions and Improving Risk Interpretation.","authors":"Vivek Bhaskar Kote, Koen Flores, Brian Connolly, Diego Pensado, Anup D Pant, Daniel P Nicolella","doi":"10.1007/s10439-025-03845-5","DOIUrl":"https://doi.org/10.1007/s10439-025-03845-5","url":null,"abstract":"<p><p>Advances in Large Language Models (LLMs) offer new opportunities to improve accessibility and usability of finite-element (FE) modeling in injury biomechanics. This study presents an LLM-based tool capable of guiding novice users in selecting response surface models trained on FE simulation results and predicting injury outcomes in Behind Armor Blunt Trauma scenarios. Beyond executing predictive tasks, the LLM-based tool communicates complex injury metrics in clear, non-technical language, facilitating broader understanding and adoption of sophisticated modeling frameworks. These findings highlight the potential of integrating LLMs with FE modeling to bridge expertise gaps, enhance interactivity, and support decision-making in injury prediction and other engineering domains.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Growth Factor-Free Engineered Biphasic Scaffold for Enhanced Bone Regeneration.","authors":"Suranji Wijekoon, Weiwei Wang, Sama Abdulmalik, Allen Zennifer, Sai Sadhananth Srinivasan, Xiaojun Yu, Sangamesh Gurappa Kumbar","doi":"10.1007/s10439-025-03857-1","DOIUrl":"https://doi.org/10.1007/s10439-025-03857-1","url":null,"abstract":"<p><p>Large-area bone regeneration remains a significant clinical challenge, as current grafts often mineralize only at the defect edges, leaving the core underdeveloped. This study introduces a biphasic, biomimetic scaffold integrating structural support with uniform bioactivity to address this limitation. The scaffold features a highly porous outer tube for mechanical strength and cell infiltration, paired with an electrospun nanofiber core enriched with decellularized extracellular matrix (dECM) to promote cell recruitment and mineralization. Twenty-five dECMs were derived from co-cultures of bone-healing cell types: osteoblasts (OB), chondrocytes (CH), mesenchymal stromal cells (MSCs), fibroblasts (FB), and endothelial cells (EC). Among them, OB + MSC-derived dECM showed the greatest osteogenic potential. This dECM was applied to an optimized nanofiber core (232 ± 87 nm from 5 wt% solution), with a protein content of 67.9 ± 8.3 µg/mg and DNA < 50 ng/mg. The outer tube exhibited 89.6 ± 5.8% porosity and a compressive modulus of 123 ± 6.7 MPa. After BSA coating and simulated body fluid immersion, scaffolds showed calcium phosphate deposition (0.28 ± 0.03 mmol/L Ca²⁺/scaffold). In a 10 mm critical-sized femoral defect in rats, scaffolds containing both CaP and OB + MSC-derived dECM significantly enhanced bone healing. Imaging and histological analyses showed a twofold increase in bone volume, mineral density, and cortical bone formation. The compressive modulus of regenerated bone was threefold higher than untreated controls and autografts. By 12 weeks, complete defect bridging and structural recovery were achieved. This biphasic scaffold design presents a promising strategy for large bone defect repair by enabling uniform tissue regeneration, combining osteoinductive cues with structural performance suited for clinical translation.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Modeling of Bridging Vein Rupture and Acute Subdural Hematoma Growth.","authors":"Delin Zeng, Andrew V Basilio, Toshiyuki Yanaoka, Leanne A Pichay, Gerard A Ateshian, Steve A Maas, Barclay Morrison","doi":"10.1007/s10439-025-03860-6","DOIUrl":"https://doi.org/10.1007/s10439-025-03860-6","url":null,"abstract":"<p><p>Due to relative motion between the skull and brain caused by mechanical impact to the head during traumatic brain injury (TBI), bridging vein (BV) rupture can occur, resulting in the formation of acute subdural hematoma (ASDH). ASDH is associated with worse clinical outcomes and higher mortality because the resulting blood clot compresses surrounding brain tissue, exacerbating secondary injuries such as cerebral edema and ischemia. In this study, we developed a computational schema to predict BV rupture and model ASDH growth. Leveraging the deformation in the cerebrospinal fluid (CSF) layer in the Global Human Body Models Consortium (GHBMC) finite element head model to evaluate relative motion at the brain-skull interface, we introduced a novel BV rupture prediction approach based on statistical measures of the strain of these CSF elements. This approach attempts to account for the population variability in BV geometry. Validation using real-world crash accident reconstruction data demonstrated good predictive performance. Based on BV rupture predictions, we modeled ASDH growth, in which hematoma expansion was driven by the simulated patient-specific intracranial pressure (ICP) response due to primary injury and secondary injuries. Hematoma growth ceased once local hematoma cavity pressure equilibrated with ICP. Simulation results produced significant hematoma expansion with greater ICP elevation, a critical indicator for high mortality rate in the clinic. The computational schema developed in this study provides a foundation for future studies to improve the prediction of mortality rate for patients with BV rupture and ASDH after TBI, which can aid in safety system design.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Helmet-Head Decoupling in Ice Hockey Impacts: An In-lab Exploratory Study Using Autoregressive Modeling of Acceleration Data Measured from a Helmet-Mounted Inertial Measurement Unit (IMU).","authors":"Dario Sciacca, Anisoara Ionescu","doi":"10.1007/s10439-025-03848-2","DOIUrl":"https://doi.org/10.1007/s10439-025-03848-2","url":null,"abstract":"<p><strong>Purpose: </strong>This study aims to develop and validate in-lab a novel approach for estimating head linear acceleration in ice hockey impacts using IMU-instrumented helmets. The use of AutoRegressive (AR) modeling was investigated as a solution to mitigate the decoupling observed between the helmet and the head.</p><p><strong>Methods: </strong>A series of impacts were conducted on a helmeted Hybrid III 50th percentile male Anthropometric Test Device (ATD). The impacts were performed using a custom-built pendulum impactor in four directions (front, front-oblique, side and back-oblique) and at two energies, 33 and 79 J, except for the back-oblique direction, which was tested only at 33 J. The processing pipeline included impact segmentation, main direction estimation and application of the AR-based transfer function modeling. The error with respect to the reference signals from the headform was quantified and the transformed signals were compared with the unprocessed (raw) and lowpass filtered signals. The generalization capabilities of the transfer function were also evaluated on a different helmet type.</p><p><strong>Results: </strong>The application of the transfer function resulted in a reduction of up to 9.04 g (57%) and 27.54% for the average Root Mean Squared Error (RMSE) and peak Mean Absolute Percentage Error (MAPE), respectively, with a consistent error decrease across all impact directions, compared to the lowpass filtered signal. However, when evaluated on a different helmet model, the transfer function showed larger errors.</p><p><strong>Conclusion: </strong>The proposed methodology effectively improves the estimation of head linear acceleration across all impact directions. Nevertheless, performance varies with helmet type, indicating the need for helmet-specific adjustments (e.g., through model retraining).</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Conceptual Design and Additive Manufacturing of a Bidirectional Gradient Gyroid Structure for Tibial Stem.","authors":"Atiyeh Taheri, Farzam Farahmand, Marjan Bahraminasab","doi":"10.1007/s10439-025-03854-4","DOIUrl":"https://doi.org/10.1007/s10439-025-03854-4","url":null,"abstract":"<p><strong>Purpose: </strong>Advancements in additive manufacturing technology have facilitated the use of cellular lattice structures for orthopedic implants. Gradient porosity can enhance the biomechanical performance of cementless implants by improving fixation and reducing aseptic loosening. Previous studies designing gradient cellular implants have been often limited to unidirectional graded structures. This study aimed at conceptual design of bidirectional graded lattice structures for the tibial stem of total knee replacement (TKR), to enhance osteogenic response and periprosthetic bone remodeling.</p><p><strong>Methods: </strong>A multi-objective optimization problem was addressed using the design of experiment approach to find the optimal gradient parameters. Three finite element models, including a preoperative, an early postoperative, and a late postoperative model of the TKR, were developed to predict the osseointegration and remodeling behaviors, based on a computational mechanobiology framework.</p><p><strong>Results: </strong>Five optimal graded lattice structures were obtained, each hypothetically appropriate for a specific group of patients. A low porosity (20% density) axially graded structure was predicted to induce a strong osteogenic response, as needed for over-aged patients with weak osteoblast activity. Also, a high porosity (10% density) radially graded structure was predicted to lead to a low bone resorption, as required for young adults demanding long implant lifespan. The overall optimal structure made of bidirectional gradient (27% radial and 73% axial) with high porosity (10% density) was predicted to enhance the bone remodeling with minimal change in osteogenic response. SEM examination of the graded gyroid specimens, fabricated by selective laser melting, revealed small fabrication errors compared to the average lattice dimensions.</p><p><strong>Conclusion: </strong>Computational and experimental results were promising and provided supportive evidence for the beneficial impact of bidirectional graded tibial stems and their manufacturability.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":5.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145123932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}