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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Design and manufacturing of a hip joint motion simulator with a novel modular design approach(Springer Heidelberg, 2023) Mihcin, Senay; Department of Mechanical Engineering; Torabnia, Shams; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of EngineeringThe study is aimed to develop a hip joint wear simulator using a modular design approach to help experimentally monitor and control critical wear parameters to validate in-silico wear models. The proper control and application of wear parameters such as the range of motion, and the applied force values while estimating the lost material due to wear are essential for thorough analysis of wear phenomena for artificial joints. The simulator's dynamics were first modeled, then dynamic loading data was used to calculate the forces, which were further used for topology optimization to reduce the forces acting on each joint. The reduction of the link weights, connected to the actuators, intends to improve the quality of motion transferred to the femoral head. The modular design approach enables topology-optimized geometry, associated gravitational and dynamic forces, resulting in a cost-effective, energy-efficient product. Moreover, this design allows integration of the subject specific data by allowing different boundary conditions following the requirements of industry 5.0. Overall, the in-vitro motion stimulations of the hip-joint prosthesis and the modular design approach used in the study might help improve the accuracy and the effectiveness of wear simulations, which could lead into the development of better and longer-lasting joint prostheses for all. The subject-specific and society-based daily life data implemented as boundary conditions enable inclusion of the personalized effects. Next, with the results of the simulator, CEN Workshop Agreement (CWA) application is intended to cover the personalized effects for previously excluded populations, providing solution to inclusive design for all.Publication Metadata only Intraoperative fluoroscopic safety assessment of femoral head implants with 3-dimensional risk parameters to minimize cut-out(Turkish Assoc Orthopaedics Traumatology, 2023) Department of Mechanical Engineering; Subaşı, Ömer; Aslan, Lercan; Oral, Atacan; Demirhan, Mehmet; Seyahi, Aksel; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; School of Medicine; College of EngineeringObjective: This study aimed to introduce a method to extract the 3-dimensional spatial position of the femoral head implant from 2-dimensional fluoroscopic projections, allowing surgeons to assess fixation much more accurately and prevent cut-out complications in proximal femoral nailing. Methods: To define a safety region for the tip in the femoral head, a novel 3-dimensional distance-based risk parameter called TSD3D was introduced. An intersection algorithm was developed that solely takes the fluoroscopic anteroposterior and lateral distances to reveal the 3-dimensional location of the screw or Kirschner wire tip, enabling the utilization of the 3-dimensional parameter. Orthogonal perspectives of 6 femur proximal bone substitutes with randomly inserted Kirschner wires were imaged under fluoroscopy. The developed algorithm was used to calculate the implant tip location in 3-dimensional from 2-dimensional images for each case. Algorithm accuracy was validated with the computed tomography-obtained 3-dimensional models of the same femur substitutes. Results: The newly introduced risk parameter successfully visualizes 3-dimensional safety regions. Utilizing the 2-dimensional fluoroscopic distances as inputs to the algorithm, the 3-dimensional position of the implanted Kirschner wire tip is calculated with a maximum of 9.8% error for a single Cartesian-coordinate measurement comparison. Conclusion: By incorporating the newly introduced 3-dimensional risk parameter, surgeons can more precisely evaluate the position of the implant and avoid cut-out complications, instead of relying solely on misleading 2-dimensional fluoroscopic projections of the femoral head.Publication Metadata only Effect of the micro-textured piston on the performance of a hermetic reciprocating compressor(Sage Publications Ltd, 2023) Haque, Umar Ul; Department of Mechanical Engineering; Shahzad, Aamir; Lazoğlu, İsmail; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of EngineeringA hermetic reciprocating compressor is one of the most critical parts for the energy efficiency of a household refrigerator. Piston-cylinder contact in the hermetic compressor accounts for most of the energy loss. The tribological performance of the piston-cylinder pair can be enhanced by introducing micro-texturing on the piston surface. In this research, an experimental study is presented to tribologically assess the effect of the micro-textured piston on the performance of the hermetically sealed reciprocating compressor. The micro-texture on the piston surface was prepared by the laser surface texturing method. Four different micro-textures were studied: radial micro-grooves, axial micro-grooves, mesh micro-grooves, and micro-dimples. The textures’ size, shape, and depth were studied using scanning electron microscopy (SEM) and white light interferometry (WLI) techniques. The results were compared with the non-textured piston compressor. It was found that the radial, axial, and mesh micro-grooves pistons have a negative effect on the coefficient of performance of the hermetic reciprocating compressor. However, the piston with the micro-dimples texture increased the compressor's coefficient of performance by 1%. Refrigerant leakage from the piston-cylinder clearance was also investigated and it was observed that micro-dimples on the piston surface decrease the refrigerant leakage by 35% due to the presence of a continuous oil film between piston and cylinder. The compressor's cooling capacity (Qc) was observed to be increased by 1 W in the case of a micro-dimpled piston.Publication Metadata only Paper integrated microfluidic contact lens for colorimetric glucose detection(Royal Soc Chemistry, 2024) İstif, Emin; Department of Mechanical Engineering; İşgör, Pelin Kübra; Abbasiasl, Taher; Das, Ritu; Yener, Umut Can; Beker, Levent; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); Graduate School of Sciences and Engineering; College of EngineeringContact lenses offer a simple, cost-effective, and non-invasive method for in situ real-time analysis of various biomarkers. Electro-chemical sensors are integrated into contact lenses for analysis of various biomarkers. However, they suffer from rigid electronic components and connections, leading to eye irritation and biomarker concentration deviation. Here, a flexible and microfluidic integrated paper-based contact lens for colorimetric analysis of glucose was implemented. Facilitating a three-dimensional (3D) printer for lens fabrication eliminates cumbersome cleanroom processes and provides a simple, batch compatible process. Due to the capillary force of the filter paper, the sample was routed to detection chambers inside microchannels, and it allowed further colorimetric detection. The paper-embedded microfluidic contact lens successfully detects glucose down to 2 mM within ∼10 s. The small dimension of the microfluidic system enables detection of glucose levels as low as 5 μl. The results show the potential of the presented approach to analyze glucose concentration in a rapid manner. It is demonstrated that the fabricated contact lens can successfully detect glucose levels of diabetic patients.Publication Metadata only Left atrial ligation in the avian embryo as a model for altered hemodynamic loading during early vascular development(Journal of Visualized Experiments, 2023) Department of Mechanical Engineering; Sevgin, Börteçine; Çoban, Merve Nur; Karataş, Faruk; Pekkan, Kerem; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringDue to its four-chambered mature ventricular configuration, ease of culture, imaging access, and efficiency, the avian embryo is a preferred vertebrate animal model for studying cardiovascular development. Studies aiming to understand the normal development and congenital heart defect prognosis widely adopt this model. Microscopic surgical techniques are introduced to alter the normal mechanical loading patterns at a specific embryonic time point and track the downstream molecular and genetic cascade. The most common mechanical interventions are left vitelline vein ligation, conotruncal banding, and left atrial ligation (LAL), modulating the intramural vascular pressure and wall shear stress due to blood flow. LAL, particularly if performed in ovo, is the most challenging intervention, with very small sample yields due to the extremely fine sequential microsurgical operations. Despite its high risk, in ovo LAL is very valuable scientifically as it mimics hypoplastic left heart syndrome (HLHS) pathogenesis. HLHS is a clinically relevant, complex congenital heart disease observed in human newborns. A detailed protocol for in ovo LAL is documented in this paper. Briefly, fertilized avian embryos were incubated at 37.5 degrees C and 60% constant humidity typically until they reached Hamburger-Hamilton (HH) stages 20 to 21. The egg shells were cracked open, and the outer and inner membranes were removed. The embryo was gently rotated to expose the left atrial bulb of the common atrium. Pre-assembled micro-knots from 10-0 nylon sutures were gently positioned and tied around the left atrial bud. Finally, the embryo was returned to its original position, and LAL was completed. Normal and LALinstrumented ventricles demonstrated statistically significant differences in tissue compaction. An efficient LAL model generation pipeline would contribute to studies focusing on synchronized mechanical and genetic manipulation during the embryonic development of cardiovascular components. Likewise, this model will provide a perturbed cell source for tissue culture research and vascular biology.Publication Metadata only Electro-conductive silica nanoparticles-incorporated hydrogel based on alginate as a biomimetic scaffold for bone tissue engineering application(Taylor and Francis, 2024) Derakhshankhah, Hossein; Eskandani, Morteza; Vandghanooni, Somayeh; Jaymand, Mehdi; Department of Mechanical Engineering; Nakhjavani, Sattar Akbar; Taşoğlu, Savaş; Department of Mechanical Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of EngineeringAn innovative electrically conductive hydrogel was fabricated through the incorporation of silica nanoparticles (SiO2 NPs) and poly(aniline-co-dopamine) (PANI-co-PDA) into oxidized alginate (OAlg) as a biomimetic scaffold for bone tissue engineering application. The developed self-healing chemical hydrogel was characterized by FTIR, SEM, TEM, XRD, and TGA. The electrical conductivity and swelling ratio of the hydrogel were obtained as 1.7 × 10−3 S cm−1 and 130%, respectively. Cytocompatibility and cell proliferation potential of the developed scaffold were approved by MTT assay using MG-63 cells. FE-SEM imaging approved the potential of the fabricated scaffold for hydroxyapatite (HA) formation and bioactivity induction through immersing in SBF solution.Publication Metadata only Review of machine learning techniques in soft tissue biomechanics and biomaterials(Springer, 2024) Donmazov, Samir; Pişkin, Senol; Department of Mechanical Engineering; Saruhan, Eda Nur; Pekkan, Kerem; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringBackground and ObjectiveAdvanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and transcatheter interventions. Recent advances in heart valve engineering, medical device and patch design are built upon these models. Furthermore, understanding vascular growth and remodeling in native and tissue-engineered vascular biomaterials, as well as designing and testing drugs on soft tissue, are crucial aspects of predictive regenerative medicine. Traditional nonlinear optimization methods and finite element (FE) simulations have served as biomaterial characterization tools combined with soft tissue mechanics and tensile testing for decades. However, results obtained through nonlinear optimization methods are reliable only to a certain extent due to mathematical limitations, and FE simulations may require substantial computing time and resources, which might not be justified for patient-specific simulations. To a significant extent, machine learning (ML) techniques have gained increasing prominence in the field of soft tissue mechanics in recent years, offering notable advantages over conventional methods. This review article presents an in-depth examination of emerging ML algorithms utilized for estimating the mechanical characteristics of soft biological tissues and biomaterials. These algorithms are employed to analyze crucial properties such as stress-strain curves and pressure-volume loops. The focus of the review is on applications in cardiovascular engineering, and the fundamental mathematical basis of each approach is also discussed.MethodsThe review effort employed two strategies. First, the recent studies of major research groups actively engaged in cardiovascular soft tissue mechanics are compiled, and research papers utilizing ML and deep learning (DL) techniques were included in our review. The second strategy involved a standard keyword search across major databases. This approach provided 11 relevant ML articles, meticulously selected from reputable sources including ScienceDirect, Springer, PubMed, and Google Scholar. The selection process involved using specific keywords such as "machine learning" or "deep learning" in conjunction with "soft biological tissues", "cardiovascular", "patient-specific," "strain energy", "vascular" or "biomaterials". Initially, a total of 25 articles were selected. However, 14 of these articles were excluded as they did not align with the criteria of focusing on biomaterials specifically employed for soft tissue repair and regeneration. As a result, the remaining 11 articles were categorized based on the ML techniques employed and the training data utilized.ResultsML techniques utilized for assessing the mechanical characteristics of soft biological tissues and biomaterials are broadly classified into two categories: standard ML algorithms and physics-informed ML algorithms. The standard ML models are then organized based on their tasks, being grouped into Regression and Classification subcategories. Within these categories, studies employ various supervised learning models, including support vector machines (SVMs), bagged decision trees (BDTs), artificial neural networks (ANNs) or deep neural networks (DNNs), and convolutional neural networks (CNNs). Additionally, the utilization of unsupervised learning approaches, such as autoencoders incorporating principal component analysis (PCA) and/or low-rank approximation (LRA), is based on the specific characteristics of the training data. The training data predominantly consists of three types: experimental mechanical data, including uniaxial or biaxial stress-strain data;synthetic mechanical data generated through non-linear fitting and/or FE simulations;and image data such as 3D second harmonic generation (SHG) images or computed tomography (CT) images. The evaluation of performance for physics-informed ML models primarily relies on the coefficient of determination R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}<^>{2}$$\end{document}. In contrast, various metrics and error measures are utilized to assess the performance of standard ML models. Furthermore, our review includes an extensive examination of prevalent biomaterial models that can serve as physical laws for physics-informed ML models.ConclusionML models offer an accurate, fast, and reliable approach for evaluating the mechanical characteristics of diseased soft tissue segments and selecting optimal biomaterials for time-critical soft tissue surgeries. Among the various ML models examined in this review, physics-informed neural network models exhibit the capability to forecast the mechanical response of soft biological tissues accurately, even with limited training samples. These models achieve high R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${R}<^>{2}$$\end{document} values ranging from 0.90 to 1.00. This is particularly significant considering the challenges associated with obtaining a large number of living tissue samples for experimental purposes, which can be time-consuming and impractical. Additionally, the review not only discusses the advantages identified in the current literature but also sheds light on the limitations and offers insights into future perspectives.Publication Metadata only Mechanical characterization and torsional buckling of pediatric cardiovascular materials(Springer Heidelberg, 2024) Donmazov, Samir; Pişkin, Şenol; Arnaz, Ahmet; Department of Mechanical Engineering; Kul, Demet; Pekkan, Kerem; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Health Sciences; College of EngineeringIn complex cardiovascular surgical reconstructions, conduit materials that avoid possible large-scale structural deformations should be considered. A fundamental mode of mechanical complication is torsional buckling which occurs at the anastomosis site due to the mechanical instability, leading surgical conduit/patch surface deformation. The objective of this study is to investigate the torsional buckling behavior of commonly used materials and to develop a practical method for estimating the critical buckling rotation angle under physiological intramural vessel pressures. For this task, mechanical tests of four clinically approved materials, expanded polytetrafluoroethylene (ePTFE), Dacron, porcine and bovine pericardia, commonly used in pediatric cardiovascular surgeries, are conducted (n = 6). Torsional buckling initiation tests with n = 4 for the baseline case (L = 7.5 cm) and n = 3 for the validation of ePTFE (L = 15 cm) and Dacron (L = 15 cm and L = 25 cm) for each are also conducted at low venous pressures. A practical predictive formulation for the buckling potential is proposed using experimental observations and available theory. The relationship between the critical buckling rotation angle and the lumen pressure is determined by balancing the circumferential component of the compressive principal stress with the shear stress generated by the modified critical buckling torque, where the modified critical buckling torque depends linearly on the lumen pressure. While the proposed technique successfully predicted the critical rotation angle values lying within two standard deviations of the mean in the baseline case for all four materials at all lumen pressures, it could reliably predict the critical buckling rotation angles for ePTFE and Dacron samples of length 15 cm with maximum relative errors of 31% and 38%, respectively, in the validation phase. However, the validation of the performance of the technique demonstrated lower accuracy for Dacron samples of length 25 cm at higher pressure levels of 12 mmHg and 15 mmHg. Applicable to all surgical materials, this formulation enables surgeons to assess the torsional buckling potential of vascular conduits noninvasively. Bovine pericardium has been found to exhibit the highest stability, while Dacron (the lowest) and porcine pericardium have been identified as the least stable with the (unitless) torsional buckling resistance constants, 43,800, 12,300 and 14,000, respectively. There was no significant difference between ePTFE and Dacron, and between porcine and bovine pericardia. However, both porcine and bovine pericardia were found to be statistically different from ePTFE and Dacron individually (p < 0.0001). ePTFE exhibited highly nonlinear behavior across the entire strain range [0, 0.1] (or 10% elongation). The significant differences among the surgical materials reported here require special care in conduit construction and anastomosis design.Publication Metadata only Effect of impeller rotational phase on the FDA blood pump velocity fields(Wiley, 2024) Department of Mechanical Engineering; Uçak, Kağan; Karataş, Faruk; Pekkan, Kerem; Department of Mechanical Engineering; College of EngineeringBackgroundThe Food and Drug Administration (FDA) blood pump is an open-source benchmark cardiovascular device introduced for validating computational and experimental performance analysis tools. The time-resolved velocity field for the whole impeller has not been established, as is undertaken in this particle image velocimetry (PIV) study. The level of instantaneous velocity fluctuations is important, to assess the flow-induced rotor vibrations which may contribute to the total blood damage. MethodsTo document these factors, time-resolved two-dimensional PIV experiments were performed that were precisely phase-locked with the impeller rotation angle. The velocity fields in the impeller and in the volute conformed with the previous single blade passage experiments of literature. ResultsDepending on the impeller orientation, present experiments showed that volute outlet nozzle flow can fluctuate up to 34% during impeller rotation, with a maximum standard experimental uncertainty of 2.2%. Likewise, the flow fields in each impeller passage also altered in average 33.5%. Considerably different vortex patterns were observed for different blade passages, with the largest vortical structures reaching an average core radii of 7 mm. The constant volute area employed in the FDA pump design contributes to the observed velocity imbalance, as illustrated in our velocity measurements. ConclusionsBy introducing the impeller orientation parameter for the nozzle flow, this study considers the possible uncertainties influencing pump flow. Expanding the available literature data, analysis of inter-blade relative velocity fields is provided here for the first-time to the best of our knowledge. Consequently, our research fills a critical knowledge gap in the understanding of the flow dynamics of an important benchmark cardiovascular device. This study prompts the need for improved hydrodynamic designs and optimized devices to be used as benchmark test devices, to build more confidence and safety in future ventricular assist device performance assessment studies.Publication Metadata only Switching the left and the right hearts: a novel BI-ventricle mechanical support strategy with spared native single-ventricle(Springer, 2023) Şişli, Emrah; Aka, İbrahim Başar; Tuncer, Osman Nuri; Atay, Yüksel; Özbaran, Mustafa; Department of Mechanical Engineering; Yıldırım, Canberk; Pekkan, Kerem; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of EngineeringEnd-stage Fontan patients with single-ventricle (SV) circulation are often bridged-to-heart transplantation via mechanical circulatory support (MCS). Donor shortage and complexity of the SV physiology demand innovative MCS. In this paper, an out-of-the-box circulation concept, in which the left and right ventricles are switched with each other is introduced as a novel bi-ventricle MCS configuration for the "failing" Fontan patients. In the proposed configuration, the systemic circulation is maintained through a conventional mechanical ventricle assist device (VAD) while the venous circulation is delegated to the native SV. This approach spares the SV and puts it to a new use at the right-side providing the most-needed venous flow pulsatility to the failed Fontan circulation. To analyze its feasibility and performance, eight SV failure modes have been studied via an established multi-compartmental lumped parameter cardiovascular model (LPM). Here the LPM model is experimentally validated against the corresponding pulsatile mock-up flow loop measurements of a representative 15-year-old Fontan patient employing a clinically-approved VAD (Medtronic-HeartWare). The proposed surgical configuration maintained the healthy cardiac index (3-3.5 l/min/m(2)) and the normal mean systemic arterial pressure levels. For a failed SV with low ejection fraction (EF = 26%), representing a typical systemic Fontan failure, the proposed configuration enabled a similar to 28 mmHg amplitude in the venous/pulmonary waveforms and a 2 mmHg decrease in the central venous pressure (CVP) together with acceptable mean pulmonary artery pressures (17.5 mmHg). The pulmonary vascular resistance (PVR)-SV failure case provided a similar to 5 mmHg drop in the CVP, with venous/pulmonary pulsatility reaching to similar to 22 mmHg. For the high PVR failure case with a healthy SV (EF = 44%) pulmonary hypertension is likely to occur as expected. While this condition is routinely encountered during the heart transplantation and managed through pulmonary vasodilators a need for precise functional assessment of the spared failed-ventricle is recommended if utilized in the PVR failure mode. Comprehensive in vitro and in silico results encourage this novel concept as a low-cost, more physiological alternative to the conventional bi-ventricle MCS pending animal experiments.