Cardiovascular Engineering and Technology最新文献

{"title":"Comment on the Paper \"EDL Induced Electro-magnetized Modified Hybrid Nano-blood Circulation in an Endoscopic Fatty Charged Arterial Indented Tract, Poly Karmakar, Sanatan Das, Cardiovascular Engineering and Technology (2024) 15:171-198\".","authors":"Asterios Pantokratoras","doi":"10.1007/s13239-026-00855-9","DOIUrl":"https://doi.org/10.1007/s13239-026-00855-9","url":null,"abstract":"<p><p>Two serious errors and many typographical errors exist in the above paper.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148686605","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":"Evaluation of Human Stem Cell Conditioned Medium and Culture Conditions on Alleviating Elastase-Compromised Human Aortic Smooth Muscle Cell Function.","authors":"Christofer S Baldwin, Nickolas Gustavison, Jorge Almodovar, Shilpa Iyer, Raj R Rao","doi":"10.1007/s13239-026-00853-x","DOIUrl":"https://doi.org/10.1007/s13239-026-00853-x","url":null,"abstract":"<p><p>Cardiovascular health depends critically on the integrity of the vascular extracellular matrix (ECM) and the behavior of vascular smooth muscle cells (VSMCs), both of which can be adversely affected in vascular diseases. This study quantitatively evaluates the therapeutic potential of conditioned medium (CM) derived from bone marrow (BM-MSCs) and adipose-derived stem cells (ADSCs) in an elastase-injured human aortic smooth muscle cell (HASMC) model. We systematically varied seeding densities (2000, 5000, and 10,000 cells/cm²) and serum conditions to optimize the SC-SMC secretome for vascular repair. Our results indicate that neither BM-SMC nor AD-SMC CM significantly enhanced lysyl oxidase (LOX) activity. In fact, serum-supplemented BM-SMC CM significantly suppressed LOX activity at seeding densities of 2000 cells/cm² (p = 0.0378) and 10,000 cells/cm² (p = 0.0080) compared to injured untreated controls. High-density AD-SMC CM (10,000 cells/cm²) also resulted in a significant decrease in elastin levels (p < 0.05). In addition, serum presence was critical for maintaining the reparative phenotype. Serum-free (SF) conditions for both cell sources led to widespread, statistically significant reductions (p < 0.0001) in key repair and inflammatory biomarkers, including PDGF-AA, Leptin, Lipocalin-2, Osteopontin, RBP4, MMP-1, and IL-6. IL-11 emerged as a primary discriminatory biomarker, showing significant differences between BM and AD treatments at high seeding densities, with both sources causing a significant decrease (p < 0.0001) compared to injured untreated controls. These findings demonstrate that seeding density and serum conditions are critical variables that quantitatively modulate the efficacy of SC-SMC-CM. The study highlights that BM-SMC-derived CM offers a more stable platform for elastin maintenance under serum-free conditions, providing a foundation for developing tailored, cell-free regenerative therapies for cardiovascular disease.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148674403","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 Motion Artifacts in Cardiorespiratory Vital Signs as Oxygen Saturation and Non-Invasive Blood Pressure Through Redundant Denoising and Adaptive Filtering Methods for Wearable Healthcare Monitoring Systems.","authors":"Fabian Andres Castaño, Alher Mauricio Hernández","doi":"10.1007/s13239-026-00850-0","DOIUrl":"https://doi.org/10.1007/s13239-026-00850-0","url":null,"abstract":"<p><strong>Background and objective: </strong>Chronic cardiovascular diseases have motivated the development of wearable systems capable of continuously monitoring physiological variables such as oxygen saturation (SpO <math><mmultiscripts><mrow></mrow> <mn>2</mn> <mrow></mrow></mmultiscripts> </math> ) and non-invasive blood pressure (NIBP). However, motion artifacts remain one of the main limitations affecting the reliability of these measurements in ambulatory environments. This article presents a novel framework for motion artifact reduction in photoplethysmography (PPG) and NIBP signals based on redundant sensing, inertial measurements, ECG-guided temporal synchrony, and multichannel signal processing.</p><p><strong>Methods: </strong>The proposed framework combines independent component analysis and recursive least-squares adaptive filtering to separate physiological information from motion-induced interference. Performance was compared with conventional finite impulse response (FIR) filtering and wavelet shrinkage (WS) methods using signal-to-noise ratio (SNR), weighted distortion assessment (WDA), oxygen saturation estimation, and blood pressure estimation metrics.</p><p><strong>Results: </strong>The proposed method achieved statistically significant improvements in signal quality and physiological parameter estimation. Average SNR improved from <math><mrow><mo>-</mo> <mn>5.93</mn> <mo>±</mo> <mn>5.05</mn></mrow> </math> dB to <math><mrow><mo>-</mo> <mn>3.43</mn> <mo>±</mo> <mn>2.02</mn></mrow> </math> dB in the red PPG channel ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.02</mn></mrow> </math> ), while the WDA index increased from 0.48 to 0.73. Oxygen saturation estimation improved from <math><mrow><mn>80.87</mn> <mo>±</mo> <mn>9.09</mn> <mo>%</mo></mrow> </math> in motion-contaminated signals to <math><mrow><mn>94.16</mn> <mo>±</mo> <mn>2.72</mn> <mo>%</mo></mrow> </math> after denoising ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.04</mn></mrow> </math> ), approaching resting measurements ( <math><mrow><mn>95.23</mn> <mo>±</mo> <mn>2.31</mn> <mo>%</mo></mrow> </math> ). For NIBP signals, statistically significant improvements were also observed ( <math><mrow><mi>p</mi> <mo>=</mo> <mn>0.045</mn></mrow> </math> ), particularly for systolic pressure estimation, although diastolic pressure remained affected by residual motion-related distortions.</p><p><strong>Conclusions: </strong>The proposed framework improves the robustness of wearable PPG and NIBP monitoring under motion conditions through the combined use of sensor redundancy, ECG-guided temporal coupling, inertial measurements, and adaptive multichannel signal processing. The results demonstrate significant improvements in signal quality and physiological parameter estimation compared with conventional denoising approaches, supporting the potential use of the method in ambulatory cardiovascular monitoring applications.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148671441","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 Small-Diameter Tricuspid Valve Prosthesis for the Correction of Congenital Heart Defects Based on an Adult Donor Mitral Valve Homograft.","authors":"Anton Vladimirovich Tsaregorodtsev, Anna Grigorevna Erokhina","doi":"10.1007/s13239-026-00834-0","DOIUrl":"10.1007/s13239-026-00834-0","url":null,"abstract":"<p><strong>Background: </strong>Tricuspid valve replacement is the preferred method when valve repair is not feasible. Stented xenobioprostheses, which limit the growth of the fibrous ring due to their rigid titanium frame and often have a short service life, are particularly problematic in children. An alternative approach is the implantation of a mitral valve homograft in the tricuspid position, which is more resistant to calcification. However, the limited availability of small-diameter homografts from adult donors restricts their use. To address this, a new technique for downsizing an adult mitral homograft was developed and tested in a wet lab and in silico (using 3D printing technologies).</p><p><strong>Methods: </strong>Two techniques for reducing the size of the mitral homograft were developed: one creating a single papillary muscle and the other creating two neo-papillary muscles. The hydrodynamics of the resulting prostheses were assessed using visual inspection and ultrasound evaluation.</p><p><strong>Results: </strong>It was demonstrated that reducing the mitral homograft by resecting the commissures, a portion of the anterior leaflet, and the posterior leaflet along with their subvalvular structures is a reliable method. This technique does not violate the congruence of the anterior and posterior leaflets and ensures optimal hydrodynamic parameters.</p><p><strong>Conclusions: </strong>The proposed technique makes it possible to downsize an adult mitral homograft to a \"pediatric\" size. It can be used clinically as an intraoperative adaptation technique, performed on the \"back table\" in 30-40 minutes.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"385-397"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846030","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":"Sources of Variability in Intracranial Aneurysm Model Reconstruction and Evaluation: A Systematic Investigation.","authors":"Jared T Chong, Hang Yi, Alex E Wang, Cindy Ju, Luke Bramlage, Bryan Ludwig, Zifeng Yang","doi":"10.1007/s13239-026-00841-1","DOIUrl":"10.1007/s13239-026-00841-1","url":null,"abstract":"<p><strong>Purpose: </strong>The intracranial aneurysm (IA) model reconstruction is critical for pathophysiology diagnosis and computational simulations. This study aimed to quantify the impact of segmentation thresholds and software platforms on the reconstruction of IA geometry as well as the impact of inter-user variability on the assessment of morphology.</p><p><strong>Methods: </strong>600 IA models were reconstructed from 100 patient DSA datasets using Materialise Mimics and 3D Slicer at three grey value (GV) thresholds; 1000, 1500, and 2500. Geometric measurements were performed in 3-matic by three users. Measurements included vessel diameters and aneurysm morphology parameters. Mimics, the 2500 GV threshold, and the most experienced user (R1) served as baselines for comparison. Normality was evaluated using Shapiro-Wilk tests, and statistical differences were assessed with paired t-tests and relative percent differences.</p><p><strong>Results: </strong>All anatomical regions showed statistically significant geometric variation across software and threshold. Model evaluation showed potential statistically significant variation between users. Models from 3D Slicer were consistently smaller than those from Mimics with percent differences ranging from - 1.27 to - 4.38% (all p < .05). Lower thresholds produced consistently larger models; decreasing from 2500 to 1000 GV increased average diameters by up to 15.9%, depending on specific region. User-related variability was most pronounced in the least experienced user, with size measurements deviating by up to 22.67% from the baseline.</p><p><strong>Conclusion: </strong>Segmentation software, threshold selection, and user interaction each introduce meaningful and statistically significant variability into IA model geometry and evaluation. Standardization of segmentation protocols-especially threshold values and operator training-is essential to improve reproducibility.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"414-424"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442564/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147845966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Model for Predicting Optimal Clinical Intervention in Pre-Operative Neonates with Transposition of the Great Arteries.","authors":"Madisyn Messmore, William DeCampli, Alain Kassab","doi":"10.1007/s13239-026-00839-9","DOIUrl":"10.1007/s13239-026-00839-9","url":null,"abstract":"<p><strong>Purpose: </strong>Transposition of the Great Arteries (TGA) is a congenital heart defect characterized by the abnormal positioning of the pulmonary artery over the left ventricle and aorta over the right ventricle. Systemic oxygen delivery, therefore, is dependent on the ability for blood to flow (shunt) between the \"parallel\" (systemic and pulmonary) circulations. Prior to the standard procedure for treatment of TGA (the arterial switch operation (ASO)), shunting is commonly inadequate, resulting in systemic hypoxemia and hypoxia. In this case the standard intervention is the balloon atrial septostomy, but it may not be sufficient and has a certain complication rate. Other adjustable anatomical and physiological factors may influence shunting but have not been adequately studied.</p><p><strong>Methods: </strong>In this investigation, we develop a lumped parameter model (LPM) of TGA to explore the influence of several adjustable factors that can be altered by catheter or pharmacological interventions aimed at improving systemic arterial oxygen delivery to clinically acceptable levels in the preoperative period for newborns with TGA. This model is used to ascertain the sensitivity of oxygen saturation to these parameters and to propose optimal treatment scenarios using formal optimization techniques. Sensitivity in this study is determined using finite difference methods, and a Nelder Mead (NM) algorithm is used for optimization.</p><p><strong>Results: </strong>Out of 729 tested cases in the sensitivity study, percentage systemic arterial oxygen saturation (Ssa) was most sensitive to systemic vascular resistance (SVR) in 32.77% of cases and was the most sensitive to PDA diameter in 32.46% of cases. Increasing patent ductus arteriosus (PDA) diameter and SVR both yield an increase in Ssa in nearly all cases, while decreasing pulmonary vascular resistance (PVR) yields an increase in Ssa in nearly all cases. Notably, atrial septal defect (ASD) enlargement was not always most sensitive parameter for increasing Ssa. Best results were obtained with an objective function with a weight on pulmonary-to-systemic flow ratio of 0.1 compared to the weight of unity on Ssa. Lastly, while it does not significantly impact the results of optimization, compliance ratio does have the potential to influence optimal pre-operative strategy.</p><p><strong>Conclusions: </strong>This study illuminates the influence of SVR and PVR in oxygen delivery to the systemic circulation through extensive sensitivity testing. These results hold promise for applying other interventions aside from atrial septostomy for improving systemic arterial oxygen saturation. Using our methodology in conjunction with machine learning (ML) using clinical data, an optimization-based tool will be developed to guide pre-operative decision-making in TGA management.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"398-413"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442601/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147876383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncertainty Quantification of Finite Element Strain Predictions for a Nitinol Medical Device: Influence of Input Parameter Probability Distribution on Output Uncertainty.","authors":"Ian A Carr, Kenneth I Aycock, Harshad Paranjape, Craig Bonsignore, Jason D Weaver, Brent A Craven","doi":"10.1007/s13239-026-00837-x","DOIUrl":"10.1007/s13239-026-00837-x","url":null,"abstract":"<p><p>Establishing credibility of computational modeling of medical devices is critical when an incorrect decision could cause patient harm. Uncertainty quantification (UQ) can impart credibility by providing an estimate of the model uncertainty due to variability in the input parameters. To perform UQ, non-deterministic simulations are performed where model inputs are represented by probability density functions (PDFs). Computational modeling of medical devices, however, is typically constrained by limited sample sizes and sparse experimental data. As a result, it is generally not possible to definitively characterize the true input distributions for UQ. The sparse data must instead be fit with an assumed PDF. While the assumption of a Gaussian distribution is common, other PDFs may be more appropriate depending on the context. In this study, we investigate the influence of input PDF choice on output uncertainty from non-deterministic finite element simulations of a nitinol medical device. We first characterize the geometry, material properties, and the experimental test conditions. We then perform a screening study to determine the relative importance of each parameter on our primary quantity of interest (QOI), peak strain amplitude. Next we perform three UQ studies, each using one of three different PDF types: Gaussian, gamma, and uniform. By sampling the input parameter PDFs using a Latin hypercube approach, we perform non-deterministic simulations to predict the output distributions. Our results show that use of uniform distributions yields output predictions with the largest variance and is thus the most conservative choice unless infrequent events are of interest. In contrast, we show that for conservative predictions of extreme events, a better choice is to use Gaussian or gamma distributions with asymptotic tails of finite probability that are neglected when using uniform distributions.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"457-475"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13215217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147846037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personalized Deep Networks for Enhanced ECG Segmentation.","authors":"Maylon Pereira Folli, Gabriel Tozatto Zago, Stephanie Rezende Alvarenga Moulin Mares, Rodrigo Varejão Andreão","doi":"10.1007/s13239-026-00835-z","DOIUrl":"10.1007/s13239-026-00835-z","url":null,"abstract":"<p><p>Electrocardiography (ECG) plays a vital role in the diagnosis of cardiovascular diseases by analyzing the electrical activity of the heart. ECG semantic segmentation is a subfield focused on sample-wise delineation of ECG waveforms by assigning a physiological label to each time sample, enabling explicit estimation of clinically meaningful onset and offset boundaries. Recent advancements in deep learning have significantly improved ECG classification accuracy; however, the same has not yet been observed in automatic ECG segmentation. Existing models often lack explainability and adaptability to patient-specific variations, thereby reducing their generalizability. This study proposes a personalized deep neural network approach for enhanced ECG processing. This method incorporates convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks, incorporating an attention mechanism to refine segmentation accuracy. A novel loss function is introduced to ensure smoother temporal transitions and better classification accuracy. The model was evaluated using the QT Database, demonstrating substantial improvements in P-wave and QRS delineation and in T-wave offset localization segmentation when fine-tuned for individual patients when fine-tuned and evaluated on held-out data from the same patient, demonstrating the benefit of intra-patient adaptation. Our results indicate that personalization improves delineation accuracy for challenging waveforms (notably P and T waves), supporting the potential of deep learning to better capture patient-specific morphology and providing a stronger basis for waveform-level, clinically interpretable ECG analysis.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"489-501"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442478/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147730731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing Non-invasive Fractional Flow Reserve Estimation with Machine Learning-Enhanced 1D Hemodynamic Modeling.","authors":"Cyrus Tanade, Japneet Kaur Mavi, Guinevere Ferreira, Sam Schwaller, Amanda Randles","doi":"10.1007/s13239-026-00836-y","DOIUrl":"10.1007/s13239-026-00836-y","url":null,"abstract":"<p><p>Patient-specific computational models exhibit strong concordance with invasively measured fractional flow reserve (FFR)-the clinical gold standard for diagnosing coronary ischemia. However, current modeling techniques frequently rely on computationally intensive assumptions such as pulsatile flow dynamics and often fail to optimally leverage patient-specific clinical data that is routinely available, limiting their practical clinical adoption. In this study, we propose a hybrid coronary angiography-based approach that reduces computational complexity through simplified steady-state flow assumptions, while simultaneously better leveraging available clinical information. Specifically, we integrate physics-based modeling with a machine learning (ML) feedback loop designed to refine and improve FFR predictions. We evaluated this hybrid framework using a retrospective two-center cohort comprising 132 patients with 132 coronary lesions. Our results demonstrate that steady-state models effectively capture essential hemodynamic patterns, closely matching pulsatile model predictions. The ML refinement step enhances diagnostic accuracy, yielding a sensitivity of 83.3%, specificity of 100.0%, positive predictive value of 100.0%, negative predictive value of 88.2%, and overall precision of 92.6%. By effectively combining efficient computational modeling with targeted ML-driven refinements, our approach represents a robust, clinically viable solution for accurate patient-specific FFR estimation.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"425-438"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13340754/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147789382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Tissue Freezing on the Functional and Biomechanical Characteristics of Porcine Aortic Roots.","authors":"Tanita Drejer Jeppesen, Johannes Høgfeldt Jedrzejczyk, Anne Lund Vingborg, Alberte Damgaard Schmidt Hansen, Søren Nielsen Skov, Leila Louise Benhassen, J Michael Hasenkam, Peter Johansen","doi":"10.1007/s13239-026-00833-1","DOIUrl":"10.1007/s13239-026-00833-1","url":null,"abstract":"<p><strong>Purpose: </strong>Freeze-preservation of porcine aortic tissue is often necessary for experimental planning and standardization, but the impact of freezing on aortic root properties has not been systematically investigated. This study evaluated the effects of freezing and thawing on the biomechanical, fluid dynamic, and ultrasonographic characteristics of porcine aortic roots.</p><p><strong>Methods: </strong>A total of 32 porcine hearts were obtained from a local abattoir. Specimens were randomized to a fresh group (immediate testing) or a thawed group (storage at - 20 °C for 30 days followed by thawing in saline). Uniaxial tensile testing was performed on samples from the sinotubular junction (STJ) and non-coronary cusp (NCC) (n = 10 per group). Functional testing was conducted in a pulsatile flow loop (n = 6 per group), with mean aortic pressure gradient, forward and retrograde flow measured and the regurgitant fraction calculated. Ultrasonography was used to assess annular diameters and coaptation lengths.</p><p><strong>Results: </strong>Tensile testing revealed no statistically significant differences in E-module, maximum stress, maximum load, or stiffness between fresh and thawed specimens at either the STJ or NCC. Mean aortic gradient, retrograde flow and regurgitant fraction did not differ. Ultrasonography showed no statistically significant changes in annular geometry or leaflet coaptation length after freezing and thawing.</p><p><strong>Conclusion: </strong>Freezing and thawing did not result in measurable differences in the biomechanical, fluid dynamic, or geometrical properties of porcine aortic roots under the tested protocol and within the sensitivity of our measurements. These findings support the use of thawed porcine aortic roots in experimental cardiovascular research.</p>","PeriodicalId":54322,"journal":{"name":"Cardiovascular Engineering and Technology","volume":" ","pages":"476-488"},"PeriodicalIF":2.4,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13442319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}