Yazar "Pişkin, Şenol" seçeneğine göre listele

Listeleniyor 1 - 11 / 11
  • Küçük Resim
    Öğe
    A canonical correlation analysis of the relationship between clinical attributes and patient-specific hemodynamic indices in adult pulmonary hypertension
    (Elsevier Sci Ltd, 2020) Pişkin, Şenol; Patnaik, Sourav S.; Han, David; Bordones, Alifer D.; Murali, Srinivas; Finol, Ender A.
    Pulmonary hypertension (PH) is a progressive disease affecting approximately 10-52 cases per million, with a higher incidence in women, and with a high mortality associated with right ventricle (RV) failure. In this work, we explore the relationship between hemodynamic indices, calculated from in silico models of the pulmonary circulation, and clinical attributes of RV workload and pathological traits. Thirty-four patient-specific pulmonary arterial tree geometries were reconstructed from computed tomography angiography images and used for volume meshing for subsequent computational fluid dynamics (CFD) simulations. Data obtained from the CFD simulations were post-processed resulting in hemodynamic indices representative of the blood flow dynamics. A retrospective review of medical records was performed to collect the clinical variables measured or calculated from standard hospital examinations. Statistical analyses and canonical correlation analysis (CCA) were performed for the clinical variables and hemodynamic indices. Systolic pulmonary artery pressure (sPAP), diastolic pulmonary artery pressure (dPAP), cardiac output (CO), and stroke volume (SV) were moderately correlated with spatially averaged wall shear stress (0.60 <= R-2 <= 0.66; p < 0.05). Similarly, the CCA revealed a linear and strong relationship (rho = 0.87; p << 0.001) between 5 clinical variables and 2 hemodynamic indices. To this end, in silico models of PH blood flow dynamics have a high potential for predicting the relevant clinical attributes of PH if analyzed in a group-wise manner using CCA. (C) 2020 IPEM. Published by Elsevier Ltd. All rights reserved.
  • Küçük Resim Yok
    Öğe
    Design, development and temporal evaluation of an MRI-compatible in-vitro circulation model using a compliant AAA phantom
    (ASME (American Society of Mechanical Engineers), 2021) Thirugnanasambandam, Mirunalini; Canch, Tejas; Pişkin, Şenol; Karmonik, Christof; Kung, Ethan; Menon, Prahlad; Avril, Stephane; Finol, Ender A
    Biomechanical characterization of abdominal aortic aneurysms (AAA) has become commonplace in rupture risk assessment studies. However, its translation to the clinic has been greatly limited due to the complexity associated with its tools and their implementation. The unattainability of patient-specific tissue properties leads to the use of generalized population-averaged material models in finite element analyses, which adds a degree of uncertainty to the wall mechanics quantification. In addition, computational fluid dynamics modeling of AAA typically lacks the patient-specific inflow and outflow boundary conditions that should be obtained by non-standard of care clinical imaging. An alternative approach for analyzing AAA flow and sac volume changes is to conduct in vitro experiments in a controlled laboratory environment. We designed, built, and characterized quantitatively a benchtop flow-loop using a deformable AAA silicone phantom representative of a patient-specific geometry. The impedance modules, which are essential components of the flow-loop, were fine-tuned to ensure typical intra-sac pressure conditions. The phantom was imaged with a magnetic resonance imaging (MRI) scanner to acquire time-resolved images of the moving wall and the velocity field inside the sac. Temporal AAA sac volume changes lead to a corresponding variation in compliance throughout the cardiac cycle. The primary outcome of this work was the design optimization of the impedance elements, the quantitative characterization of the resistive and capacitive attributes of a compliant AAA phantom, and the exemplary use of MRI for flow visualization and quantification of the deformed AAA geometry.
  • Küçük Resim
    Öğe
    Ex vivo regional mechanical characterization of porcine pulmonary arteries
    (Springer, 2021) Pillalamarri, Narasimha Rao; Patnaik, Sourav Sanchit; Pişkin, Şenol; Gueldner, P.; Finol, Ender A.
    Background: Regional mechanical characterization of pulmonary arteries can be useful in the development of computational models of pulmonary arterial mechanics. Objective: We performed a biomechanical and microstructural characterization study of porcine pulmonary arteries, inclusive of the main, left, and right pulmonary arteries (MPA, LPA, and RPA, respectively). Methods: The specimens were initially stored at ?20 °C and allowed to thaw for 12–24 h prior to testing. Each artery was further subdivided into proximal, middle, and distal regions, leading to ten location-based experimental groups. Planar equibiaxial tensile testing was performed to evaluate the mechanical behavior of the specimens, from which we calculated the stress at the maximum strain (S55), tensile modulus (TM), anisotropy index (AI), and strain energy in terms of area under the stress-strain curve (AUC). Histological quantification was performed to evaluate the area fraction of elastin and collagen content, intima-media thickness (IMT), and adventitial thickness (AT). The constitutive material behavior of each group was represented by a five-constant Holzapfel-Gasser-Ogden model. Results: The specimens exhibited non-linear stress-strain characteristics across all groups. The MPA exhibited the highest mean wall stress and TM in the longitudinal and circumferential directions, while the bifurcation region yielded the highest values of AI and AUC. All regions revealed a higher stiffness in the longitudinal direction compared to the circumferential direction, suggesting a degree of anisotropy that is believed to be within the margin of experimental uncertainty. Collagen content was found to be the highest in the MPA and decreased significantly at the bifurcation, LPA and RPA. Elastin content did not yield such significant differences amongst the ten groups. The MPA had the highest IMT, which decreased concomitantly to the distal LPA and RPA. No significant differences were found in the AT amongst the ten groups. Conclusion: The mechanical properties of porcine pulmonary arteries exhibit strong regional dissimilarities, which can be used to inform future studies of high fidelity finite element models.
  • Küçük Resim
    Öğe
    From experiments to simulation: Shear-induced responses of red blood cells to different oxygen saturation levels
    (Frontiers Media Sa, 2020) Ugurel, Elif; Pişkin, Şenol; Aksu, Ali Cenk; Eser, Aysenur; Yalcin, Ozlem
    Red blood cells (RBC) carry and deliver oxygen (O-2) to peripheral tissues through different microcirculatory regions where they are exposed to various levels of shear stress (SS). O-2 affinity of hemoglobin (Hb) decreases as the blood enters the microcirculation. This phenomenon determines Hb interactions with RBC membrane proteins that can further regulate the structure of cytoskeleton and affect the mechanical properties of cells. The goal of this study is to evaluate shear-induced RBC deformability and simulate RBC dynamics in blood flow under oxygenated and deoxygenated conditions. Venous blood samples from healthy donors were oxygenated with ambient air or deoxygenated with 100% nitrogen gas for 10 min and immediately applied into an ektacytometer (LORRCA). RBC deformability was measured before and after the application of continuous 5 Pa SS for 300 s by LORRCA and recorded as elongation index (EI) values. A computational model was generated for the simulation of blood flow in a real carotid artery section. EI distribution throughout the artery and its relationships with velocity, pressure, wall SS and viscosity were determined by computational tools. RBC deformability significantly increased in deoxygenation compared to oxygenated state both before and after 5 Pa SS implementation (p < 0.0001). However, EI values after continuous SS were not significant at higher SS levels (>5.15 Pa) in deoxygenated condition. Simulation results revealed that the velocity gradient dominates the generation of SS and the shear thinning effect of blood has a minor effect on it. Distribution of EI was calculated during oxygenation/deoxygenation which is 5-10 times higher around the vessel wall compared to the center of the lumen for sections of the pulsatile flow profile. The extent of RBC deformability increases as RBCs approach to the vessel wall in a real 3D artery model and this increment is higher for deoxygenated condition compared to the oxygenated state. Hypoxia significantly increases shear-induced RBC deformability. RBCs could regulate their own mechanical properties in blood flow by increasing their deformability in hypoxic conditions. Computational tools can be applied for defining hypoxia-mediated RBC deformability changes to monitor blood flow in hypoxic tissues.
  • Küçük Resim
    Öğe
    How can surgical continuity be maintained during the COVID-19 pandemic? a quality improvement study in the pre-vaccination period
    (Bilimsel Tip Yayinevi, 2021) Pişkin, Şenol; Çolakoğlu, Muhammet Kadri; Öter, Volkan; Özgün, Yiğit Mehmet; Aydın, Osman; Güven, Alper; Surel, Aziz Ahmet; Özmen, Mehmet Mahir; Bostancı, Erdal Birol
    Objective: During the COVID-19 pandemic, most of the elective surgeries had to be postponed. However, it is not possible to delay the surgical treatment of cancer patients for a long time. The aim of this study was to present how gastrointestinal system surgery operations are managed without delay and how employee safety is ensured , together with the results of the last five months. For this purpose, a preclinical and clinical screening system was created. Material and Methods: Data of the patients who presented to our outpatient clinic between April 1st 2020 and August 31st 2020 were retrospectively reviewed. Results: During the last five months of the pandemic, a total of 387 patients were hospitalized and 309 of these patients underwent surgical procedures. 165 of the patients who underwent surgery were newly diagnosed malignancy patients. All patients who were hospitalized were subjected to a screening for COVID-19 during the preclinical, clinical and surgical period. In the preclinical period, five patients were found positive and were directed to COVID-19 treatment without hospitalization. In the clinical period, six patients were isolated by showing symptoms during the hospitalization period. Only one of these patients received surgical treatment. The remaining five patients underwent endoscopic and interventional procedures. In this process, COVID-19 positivity was detected in a total of five healthcare workers. Conclusion: With this preclinical and clinical screening method, it is shown that a COVID-19 sterile environment can be provided by early detection of positive cases in both patients and healthcare workers. In this way, the possibility of surgical continuity was demonstrated.
  • Küçük Resim Yok
    Öğe
    Impact of Physical Wind Simulation on the Player
    (Institute of Electrical and Electronics Engineers Inc., 2024) Alpan, Zeynep Burcu Kaya; Ramzan, Muhammad Javed; Şatıroğlu, Alperen; Pişkin, Şenol
    In this paper, we will share the results of a study investigating the impact of physical, dynamic wind simulation on player's perceived realism. Previously, results showed increased measurements of perceived realism on a diverse set of items of the scale 'Perceived Realism in Games' and prompted the investigation of the physical impact of haptic wind simulation through a mechanical wind simulator. This study aims to fill that gap through implementing a simple mechanical wind simulator and testing the results in the lab environment. © 2024 IEEE.
  • Küçük Resim Yok
    Öğe
    In silico simulation of hemodynamics and blood cell mechanics inside human vasculature
    (IOS PRESS, 2021) Pişkin, Şenol; Elgebaly, Aya Ahmed Faeek
    No Abstract Available
  • Küçük Resim
    Öğe
    Patient-specific computational analysis of hemodynamics in adult pulmonary hypertension
    (Springer Link, 2021) Pillalamarri, Narasimha R.; Pişkin, Şenol; Patnaik, Sourav S.; Murali, Srinivas; Finol, Ender A.
    Pulmonary hypertension (PH) is a progressive disease characterized by elevated pressure and vascular resistance in the pulmonary arteries. Nearly 250,000 hospitalizations occur annually in the US with PH as the primary or secondary condition. A definitive diagnosis of PH requires right heart catheterization (RHC) in addition to a chest computed tomography, a walking test, and others. While RHC is the gold standard for diagnosing PH, it is invasive and posseses inherent risks and contraindications. In this work, we characterized the patient-specific pulmonary hemodynamics in silico for diverse PH WHO groups. We grouped patients on the basis of mean pulmonary arterial pressure (mPAP) into three disease severity groups: at-risk ([Formula: see text], denoted with A), mild ([Formula: see text], denoted with M), and severe ([Formula: see text], denoted with S). The pulsatile flow hemodynamics was simulated by evaluating the three-dimensional Navier-Stokes system of equations using a flow solver developed by customizing OpenFOAM libraries (v5.0, The OpenFOAM Foundation). Quasi patient-specific boundary conditions were implemented using a Womersley inlet velocity profile and transient resistance outflow conditions. Hemodynamic indices such as spatially averaged wall shear stress ([Formula: see text]), wall shear stress gradient ([Formula: see text]), time-averaged wall shear stress ([Formula: see text]), oscillatory shear index ([Formula: see text]), and relative residence time ([Formula: see text]), were evaluated along with the clinical metrics pulmonary vascular resistance ([Formula: see text]), stroke volume ([Formula: see text]) and compliance ([Formula: see text]), to assess possible spatiotemporal correlations. We observed statistically significant decreases in [Formula: see text], [Formula: see text], and [Formula: see text], and increases in [Formula: see text] and [Formula: see text] with disease severity. [Formula: see text] was moderately correlated with [Formula: see text] and [Formula: see text] at the mid-notch stage of the cardiac cycle when these indices were computed using the global pulmonary arterial geometry. These results are promising in the context of a long-term goal of identifying computational biomarkers that can serve as surrogates for invasive diagnostic protocols of PH.
  • Küçük Resim
    Öğe
    Patient-specific hemodynamics of new coronary artery bypass configurations
    (Springer, 2020) Rezaeimoghaddam, Mohammad; Oguz, Gokce Nur; Ates, Mehmet Sanser; Alkan Bozkaya, Tijen; Pişkin, Şenol; Lashkarinia, S Samaneh; Tenekecioglu, Erhan; Karagoz, Haldun; Pekkan, Kerem
    Purpose: This study aims to quantify the patient-specific hemodynamics of complex conduit routing configurations of coronary artery bypass grafting (CABG) operation which are specifically suitable for off-pump surgeries. Coronary perfusion efficacy and local hemodynamics of multiple left internal mammary artery (LIMA) with sequential and end-to-side anastomosis are investigated. Using a full anatomical model comprised of aortic arch and coronary artery branches the optimum perfusion configuration in multi-vessel coronary artery stenosis is desired. Methodology: Two clinically relevant CABG configurations are created using a virtual surgical planning tool where for each configuration set, the stenosis level, anastomosis distance and angle were varied. A non-Newtonian computational fluid dynamics solver in OpenFOAM incorporated with resistance boundary conditions representing the coronary perfusion physiology was developed. The numerical accuracy is verified and results agreed well with a validated commercial cardiovascular flow solver and experiments. For segmental performance analysis, new coronary perfusion indices to quantify deviation from the healthy scenario were introduced. Results: The first simulation configuration set;-a CABG targeting two stenos sites on the left anterior descending artery (LAD), the LIMA graft was capable of 31 mL/min blood supply for all the parametric cases and uphold the healthy LAD perfusion in agreement with the clinical experience. In the second end-to-side anastomosed graft configuration set;-the radial artery graft anastomosed to LIMA, a maximum of 64 mL/min flow rate in LIMA was observed. However, except LAD, the obtuse marginal (OM) and second marginal artery (m2) suffered poor perfusion. In the first set, average wall shear stress (WSS) were in the range of 4 to 35 dyns/cm2 for in LAD. Nevertheless, for second configuration sets the WSS values were higher as the LIMA could not supply enough blood to OM and m2. Conclusion: The virtual surgical configurations have the potential to improve the quality of operation by providing quantitative surgical insight. The degree of stenosis is a critical factor in terms of coronary perfusion and WSS. The sequential anastomosis can be done safely if the anastomosis angle is less than 90 degrees regardless of degree of stenosis. The smaller proposed perfusion index value, O(0.04 - 0) × 102, enable us to quantify the post-op hemodynamic performance by comparing with the ideal healthy physiological flow.
  • Küçük Resim
    Öğe
    Review of machine learning techniques in soft tissue biomechanics and biomaterials
    (Springer, 2024) Donmazov, Samir; Saruhan, Eda Nur; Pekkan, Kerem; Pişkin, Şenol
    Background 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.
  • Küçük Resim
    Öğe
    Sensitivity of computational fluid dynamics simulations against soft errors
    (SPRINGER WIEN, 2021) Yetkin, E. Fatih; Pişkin, Şenol
    Computational capabilities of the largest high performance computing systems have increased by more than 100 folds in the last 10 years and keep increasing substantially every year. This increase is made possible mostly by multi-core technology besides the increase in clock speed of CPUs. Nowadays, there are systems with more than 100 thousand cores installed and available for processing simultaneously. Computational simulation tools are always in need of more than available computational sources. This is the case for especially complex, large scale flow problems. For these large scale problems, the soft error tolerance of the simulation codes should also be encountered where it is not an issue in relatively small scale problems due to the low occurrence probabilities. In this study, we analyzed the reaction of an incompressible flow solver to randomly generated soft errors at several levels of computation. Soft errors are induced into the final global assembly matrix of the solver by manipulating predetermined bit-flip operations. Behaviour of the computational fluid dynamics (CFD) solver is observed after iterative matrix solver, flow convergence and CFD iterations. Results show that the iterative solvers of CFD matrices are highly sensitive to customized soft errors while the final solutions seem more intact to bit-flip operations. But, the solutions might still differ from the real physical results depending on the bit-flip location and iteration number. So, the next generation computing platforms and codes should be designed to be able to detect bit-flip operations and be designed bit-flip resistant.