Annals of Biomedical Engineering最新文献

{"title":"Computational Hemodynamics-Based Growth Prediction for Small Abdominal Aortic Aneurysms: Laminar Simulations Versus Large Eddy Simulations","authors":"Mostafa Rezaeitaleshmahalleh,&nbsp;Zonghan Lyu,&nbsp;Nan Mu,&nbsp;Min Wang,&nbsp;Xiaoming Zhang,&nbsp;Todd E. Rasmussen,&nbsp;Robert D. McBane II,&nbsp;Jingfeng Jiang","doi":"10.1007/s10439-024-03572-3","DOIUrl":"10.1007/s10439-024-03572-3","url":null,"abstract":"<div><p>Prior studies have shown that computational fluid dynamics (CFD) simulations help assess patient-specific hemodynamics in abdominal aortic aneurysms (AAAs); patient-specific hemodynamic stressors are frequently used to predict an AAA’s growth. Previous studies have utilized both laminar and turbulent simulation models to simulate hemodynamics. However, the impact of different CFD simulation models on the predictive modeling of AAA growth remains unknown and is thus the knowledge gap that motivates this study. Specifically, CFD simulations were performed for 70 AAA models derived from 70 patients’ computed tomography angiography (CTA) data with known growth status (i.e., fast-growing [&gt; 5 mm/yr] or slowly growing [&lt; 5 mm/yr]). We used laminar and large eddy simulation (LES) models to obtain hemodynamic parameters to predict AAAs’ growth status. Predicting the growth status of AAAs was based on morphological, hemodynamic, and patient health parameters in conjunction with three classical machine learning (ML) classifiers, namely, support vector machine (SVM), K-nearest neighbor (KNN), and generalized linear model (GLM). Our preliminary results estimated aneurysmal flow stability and wall shear stress (WSS) were comparable in both laminar and LES flow simulations. Moreover, computed WSS and velocity-related hemodynamic variables obtained from the laminar and LES simulations showed comparable abilities in differentiating the growth status of AAAs. More importantly, the predictive modeling performance of the three ML classifiers mentioned above was similar, with less than a 2% difference observed (<i>p</i>-value &gt; 0.05). In closing, our findings suggest that two different flow simulations investigated did not significantly affect outcomes of computational hemodynamics and predictive modeling of AAAs’ growth status, given the data investigated.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 11","pages":"3078 - 3097"},"PeriodicalIF":3.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141632445","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":"Revealing Detailed Cartilage Function Through Nanoparticle Diffusion Imaging: A Computed Tomography & Finite Element Study","authors":"Juuso Tuppurainen,&nbsp;Petri Paakkari,&nbsp;Jiri Jäntti,&nbsp;Mikko T. Nissinen,&nbsp;Maria C. Fugazzola,&nbsp;René van Weeren,&nbsp;Sampo Ylisiurua,&nbsp;Miika T. Nieminen,&nbsp;Heikki Kröger,&nbsp;Brian D. Snyder,&nbsp;Anisha Joenathan,&nbsp;Mark W. Grinstaff,&nbsp;Hanna Matikka,&nbsp;Rami K. Korhonen,&nbsp;Janne T. A. Mäkelä","doi":"10.1007/s10439-024-03552-7","DOIUrl":"10.1007/s10439-024-03552-7","url":null,"abstract":"<div><p>The ability of articular cartilage to withstand significant mechanical stresses during activities, such as walking or running, relies on its distinctive structure. Integrating detailed tissue properties into subject-specific biomechanical models is challenging due to the complexity of analyzing these characteristics. This limitation compromises the accuracy of models in replicating cartilage function and impacts predictive capabilities. To address this, methods revealing cartilage function at the constituent-specific level are essential. In this study, we demonstrated that computational modeling derived individual constituent-specific biomechanical properties could be predicted by a novel nanoparticle contrast-enhanced computer tomography (CECT) method. We imaged articular cartilage samples collected from the equine stifle joint (<i>n</i> = 60) using contrast-enhanced micro-computed tomography (µCECT) to determine contrast agents’ intake within the samples, and compared those to cartilage functional properties, derived from a fibril-reinforced poroelastic finite element model. Two distinct imaging techniques were investigated: conventional energy-integrating µCECT employing a cationic tantalum oxide nanoparticle (Ta₂O₅-cNP) contrast agent and novel photon-counting µCECT utilizing a dual-contrast agent, comprising Ta₂O₅-cNP and neutral iodixanol. The results demonstrate the capacity to evaluate fibrillar and non-fibrillar functionality of cartilage, along with permeability-affected fluid flow in cartilage. This finding indicates the feasibility of incorporating these specific functional properties into biomechanical computational models, holding potential for personalized approaches to cartilage diagnostics and treatment.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 9","pages":"2584 - 2595"},"PeriodicalIF":3.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11329549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141619120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydration State Throughout Porcine Lumbar Intervertebral Discs: Comparing Fresh and Frozen-Thawed Specimens.","authors":"Concetta Morino, Jason Kait, Cameron R Bass","doi":"10.1007/s10439-024-03577-y","DOIUrl":"https://doi.org/10.1007/s10439-024-03577-y","url":null,"abstract":"<p><p>Water content in intervertebral discs (IVDs) is essential for physiological and mechanical function. Freezing post-mortem tissue prior to biomechanical testing is a common practice to prevent tissue degradation, but this process has been theorized to alter hydration within IVDs. The hydration state throughout porcine lumbar IVDs, a common lumbar surrogate, is unknown as are the effects of freezing on porcine IVD hydration. Nineteen porcine lumbar spines were stored in one of the three conditions: frozen (- 20 °C) wrapped in saline-soaked gauze, frozen (- 20 °C) without saline, or fresh. Water content was measured in four disc regions within each of 89 discs: nucleus pulposus (NP), inner (AF-A), intermediate (AF-B), and outer (AF-C) annulus fibrosus. A three-factor, repeated measure analysis of variance was conducted for storage condition, spinal level, and repeated measure disc region. No significant differences were observed in spinal level or storage condition as a main effect. Mean hydration was significantly different in each disc region with mass percentage of water found to be 88.8 ± 1.7% in NP, 79.6 ± 3.8% in AF-A, 71.9 ± 3.7% in AF-B, and 62.3 ± 3.3% in AF-C. No significant differences were shown in NP and AF-C regions between storage conditions. Two significant differences in storage condition were observed in AF-A and AF-B regions, but there is likely no biological difference in these populations. Water content throughout porcine lumbar IVD was determined and results suggest one freeze-thaw cycle at - 20 °C does not alter the overall hydration within the porcine lumbar IVD.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141619119","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":"HeartMate 3 for Heart Failure with Preserved Ejection Fraction: In Vitro Hemodynamic Evaluation and Anatomical Fitting","authors":"Nina Langer,&nbsp;Andrew F. Stephens,&nbsp;Michael Šeman,&nbsp;David McGiffin,&nbsp;David M. Kaye,&nbsp;Shaun D. Gregory","doi":"10.1007/s10439-024-03585-y","DOIUrl":"10.1007/s10439-024-03585-y","url":null,"abstract":"<div><p>Heart failure with preserved ejection fraction (HFpEF) constitutes approximately 50% of heart failure (HF) cases, and encompasses different phenotypes. Among these, most patients with HFpEF exhibit structural heart changes, often with smaller left ventricular cavities, which pose challenges for utilizing ventricular assist devices (VADs). A left atrial to aortic (LA-Ao) VAD configuration could address these challenges, potentially enhancing patient quality of life by lowering elevated mean left atrial pressure (MLAP). This study assessed the anatomical compatibility and left atrial unloading capacity using a simulated VAD-supported HFpEF patient. A HeartMate3-supported HFpEF patient in an LA-Ao configuration was simulated using a cardiovascular simulator. Hemodynamic parameters were recorded during rest and exercise at seven pump flow rates. Computed tomography scans of 14 HFpEF (NYHA II–III) and six heart failure with reduced ejection fraction patients were analysed for anatomical comparisons. HFpEF models were independently assessed for virtual anatomical fit with the HM3 in the LA-Ao configuration. Baseline MLAP was reduced from 15 to 11 mmHg with the addition of 1 L/min HM3 support in the rest condition. In an exercise simulation, 6 L/min of HM3 support was required to reduce the MLAP from 29 to 16 mmHg. The HM3 successfully accommodated six HFpEF patients without causing interference with other cardiac structures, whereas it caused impingement ranging from 4 to 14 mm in the remaining patients. This study demonstrated that the HM3 in an LA-Ao configuration may be suitable for unloading the left atrium and relieving pulmonary congestion in some HFpEF patients where size-related limitations can be addressed through pre-surgical anatomical fit analysis.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 12","pages":"3208 - 3218"},"PeriodicalIF":3.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10439-024-03585-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141625797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Extended Neck Position is Likely to Produce Cervical Spine Injuries Through Buckling in Accidental Head-First Impacts During Rugby Tackling","authors":"Pavlos Silvestros,&nbsp;Ryan D. Quarrington,&nbsp;Ezio Preatoni,&nbsp;Harinderjit S. Gill,&nbsp;Claire F. Jones,&nbsp;Dario Cazzola","doi":"10.1007/s10439-024-03576-z","DOIUrl":"10.1007/s10439-024-03576-z","url":null,"abstract":"<div><p>Catastrophic cervical spine injuries in rugby often occur during tackling. The underlying mechanisms leading to these injuries remain unclear, with neck hyperflexion and buckling both proposed as the causative factor in the injury prevention literature. The aim of this study was to evaluate the effect of pre-impact head–neck posture on intervertebral neck loads and motions during a head-first rugby tackle. Using a validated, subject-specific musculoskeletal model of a rugby player, and computer simulations driven by in vivo and in vitro data, we examined the dynamic response of the cervical spine under such impact conditions. The simulations demonstrated that the initial head–neck sagittal-plane posture affected intervertebral loads and kinematics, with an extended neck resulting in buckling and supraphysiologic intervertebral shear and flexion loads and motions, typical of bilateral facet dislocation injuries. In contrast, an initially flexed neck increased axial compression forces and flexion angles without exceeding intervertebral physiological limits. These findings provide objective evidence that can inform injury prevention strategies or rugby law changes to improve the safety of the game of rugby.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 11","pages":"3125 - 3139"},"PeriodicalIF":3.0,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11511737/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141615793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Stage Classification of Future Knee Osteoarthritis Severity After 8 Years Using MRI: Data from the Osteoarthritis Initiative","authors":"Teemu A. T. Nurmirinta,&nbsp;Mikael J. Turunen,&nbsp;Rami K. Korhonen,&nbsp;Jussi Tohka,&nbsp;Mimmi K. Liukkonen,&nbsp;Mika E. Mononen","doi":"10.1007/s10439-024-03578-x","DOIUrl":"10.1007/s10439-024-03578-x","url":null,"abstract":"<div><p>Currently, there are no methods or tools available in clinical practice for classifying future knee osteoarthritis (KOA). In this study, we aimed to fill this gap by classifying future KOA into three severity grades: KL01 (healthy), KL2 (moderate), and KL34 (severe) based on the Kellgren-Lawrance scale. Due to the complex nature of multiclass classification, we used a two-stage method, which separates the classification task into two binary classifications (KL01 vs. KL234 in the first stage and KL2 vs. KL34 in the second stage). Our machine learning (ML) model used two Balanced Random Forest algorithms and was trained with gender, age, height, weight, and quantitative knee morphology obtained from magnetic resonance imaging. Our training dataset comprised longitudinal 8-year follow-up data of 1213 knees from the Osteoarthritis Initiative. Through extensive experimentation with various feature combinations, we identified KL baseline and weight as the most essential features, while gender surprisingly proved to be one of the least influential feature. Our best classification model generated a weighted F1 score of 79.0% and a balanced accuracy of 65.9%. The area under the receiver operating characteristic curve was 83.0% for healthy (KL01) versus moderate (KL2) or severe (KL34) KOA patients and 86.6% for moderate (KL2) versus severe (KL34) KOA patients. We found a statistically significant difference in performance between our two-stage classification model and the traditional single-stage classification model. These findings demonstrate the encouraging results of our two-stage classification model for multiclass KOA severity classification, suggesting its potential application in clinical settings in future.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 12","pages":"3172 - 3183"},"PeriodicalIF":3.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10439-024-03578-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Primary Creep Characterization in Porcine Lumbar Spine Subject to Repeated Loading.","authors":"Concetta Morino, Shea Middleton, Joost Op't Eynde, Elizabeth Dimbath, Jason Kait, Jason Luck, Cameron Bass","doi":"10.1007/s10439-024-03579-w","DOIUrl":"https://doi.org/10.1007/s10439-024-03579-w","url":null,"abstract":"","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557888","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":"Association of Sport Helmet Status on Concussion Presentation and Recovery in Male Collegiate Student-Athletes","authors":"Adrian J. Boltz,&nbsp;Landon B. Lempke,&nbsp;Reid A. Syrydiuk,&nbsp;Stefan Duma,&nbsp;Paul Pasquina,&nbsp;Thomas W. McAllister,&nbsp;Michael McCrea,&nbsp;Avinash Chandran,&nbsp;Steven P. Broglio,&nbsp;CARE Consortium Investigators","doi":"10.1007/s10439-024-03575-0","DOIUrl":"10.1007/s10439-024-03575-0","url":null,"abstract":"<div><p>Sporting helmets contain force attenuating materials which reduce traumatic head injury risk and may influence sport-related concussion (SRC) sequelae. The purpose of this study was to examine the association of sport helmet status with SRC-clinical presentation and recovery trajectories in men’s collegiate athletes. Sport helmet status was based on the nature of sports being either helmeted/non-helmeted. 1070 SRCs in helmeted (HELM) sports (Men’s-Football, Ice Hockey, and Lacrosse), and 399 SRCs in non-helmeted (NOHELM) sports (Men’s-Basketball, Cheerleading, Cross Country/Track &amp; Field, Diving, Gymnastics, Soccer, Swimming, Tennis, and Volleyball) were analyzed. Multivariable negative binomial regression models analyzed associations between sport helmet status and post-injury cognition, balance, and symptom severity, adjusting for covariate effects (SRC history, loss of consciousness, anterograde/retrograde amnesia, event type). Kaplan-Meier curves evaluated median days to: initiation of return to play (iRTP) protocol, and unrestricted RTP (URTP) by sport helmet status. Log-rank tests were used to evaluate differential iRTP/URTP between groups. Two independent multivariable Weibull accelerated failure time models were used to examine differential iRTP and URTP between groups, after adjusting for aforementioned covariates and symptom severity score. Overall, the median days to iRTP and URTP was 6.3 and 12.0, respectively, and was comparable across NOHELM- and HELM-SRCs. Post-injury symptom severity was lower (Score Ratio 0.90, 95%CI 0.82, 0.98), and cognitive test performance was higher (Score Ratio 1.03, 95%CI 1.02, 1.05) in NOHELM-compared to HELM-SRCs. Estimated time spent recovering to iRTP/URTP was comparable between sport helmet status groups. Findings suggest that the grouping of sports into helmeted and non-helmeted show slight differences in clinical presentation but not recovery.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 10","pages":"2884 - 2896"},"PeriodicalIF":3.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557887","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":"A Comprehensive Literature Review on Advancements and Challenges in 3D Bioprinting of Human Organs: Ear, Skin, and Bone.","authors":"Aishwarya Varpe, Marwana Sayed, Nikhil S Mane","doi":"10.1007/s10439-024-03580-3","DOIUrl":"https://doi.org/10.1007/s10439-024-03580-3","url":null,"abstract":"<p><p>The field of 3D bioprinting is rapidly emerging within the realm of regenerative medicine, offering significant potential in dealing with the issue of organ shortages. Despite being in its early stages, it has the potential to replicate tissue structures accurately, providing new potential solutions for reconstructive surgery. This review explores the diverse applications of 3D bioprinting in regenerative medicine, pharmaceuticals, and the food industry, specifically focusing on ear, skin, and bone tissues due to their unique challenges and implications in the field. Significant progress has been made in cartilage and bone scaffold fabrication in ear reconstruction, yet challenges in functional maturation persist. Recent advancements highlight the potential for patient-specific ear substitutes, emphasizing the need for extensive clinical trials. In skin regeneration, 3D bioprinting addresses limitations in existing models, offering opportunities for improved wound healing and realistic skin models. While challenges exist, progress in biomaterials and in-situ bioprinting holds promise. In bone regeneration, 3D bioprinting presents personalized solutions for defects, but scaffold design refinement and addressing regulatory and ethical considerations are crucial. The transformative potential of 3D bioprinting in the field of medicine holds the promise of redefining therapeutic approaches and delivering personalized treatments and functional tissues. Interdisciplinary collaboration is essential for fully realizing the capabilities of 3D bioprinting. This review provides a detailed analysis of current methodologies, challenges, and prospects in 3D bioprinting for ear, skin, and bone tissue regeneration.</p>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557885","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":"Evaluation of the Transfemoral Bone–Implant Interface Properties Using Vibration Analysis","authors":"Mostafa Mohamed,&nbsp;Eric Beaudry,&nbsp;Ahmed W. Shehata,&nbsp;Donald Raboud,&nbsp;Jacqueline S. Hebert,&nbsp;Lindsey Westover","doi":"10.1007/s10439-024-03561-6","DOIUrl":"10.1007/s10439-024-03561-6","url":null,"abstract":"<div><p>Evaluating the bone–implant interface (BII) properties of osseointegrated transfemoral (TFA) implants is important for early failure detection and prescribing loads during rehabilitation. The objective of this work is to derive and validate a 1D finite element (FE) model of the Osseointegrated Prosthetic Limb (OPL) TFA system that can: (1) model its dynamic behaviour and (2) extract the BII properties. The model was validated by: (1) comparing the 1D FE formulation to the analytical and 3D FE solutions for a simplified cylinder, (2) comparing the vibration modes of the actual TFA geometry using 1D and 3D FE models, and (3) evaluating the BII properties for three extreme conditions (LOW, INTERMEDIATE, and HIGH) generated using 3D FE and experimental (where the implant was embedded, using different adhesives, in synthetic femurs) signals for additional validation. The modes predicted by the 1D FE model converged to the analytical and the 3D FE solutions for the cylinder. The 1D model also matched the 3D FE solution with a maximum frequency difference of 2.02% for the TFA geometry. Finally, the 1D model extracted the BII stiffness and the system’s damping properties for the three conditions generated using the 3D FE simulations and the experimental INTERMEDIATE and HIGH signals. The agreement between the 1D FE and the 3D FE solutions for the TFA geometry indicates that the 1D model captures the system’s dynamic behaviour. Distinguishing between the different BII conditions demonstrates the 1D model’s potential use for the non-invasive clinical evaluation of the TFA BII properties.</p></div>","PeriodicalId":7986,"journal":{"name":"Annals of Biomedical Engineering","volume":"52 11","pages":"2987 - 3008"},"PeriodicalIF":3.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141557890","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}