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  Subjects -> ENGINEERING (Total: 2312 journals)
    - CHEMICAL ENGINEERING (196 journals)
    - CIVIL ENGINEERING (192 journals)
    - ELECTRICAL ENGINEERING (104 journals)
    - ENGINEERING (1213 journals)
    - ENGINEERING MECHANICS AND MATERIALS (389 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (70 journals)
    - MECHANICAL ENGINEERING (93 journals)

ENGINEERING (1213 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 7)
3D Research     Hybrid Journal   (Followers: 19)
AAPG Bulletin     Hybrid Journal   (Followers: 7)
AASRI Procedia     Open Access   (Followers: 15)
Abstract and Applied Analysis     Open Access   (Followers: 3)
Aceh International Journal of Science and Technology     Open Access   (Followers: 2)
ACS Nano     Full-text available via subscription   (Followers: 254)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 2)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 7)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi     Open Access  
Adsorption     Hybrid Journal   (Followers: 4)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 6)
Advanced Science     Open Access   (Followers: 5)
Advanced Science Focus     Free   (Followers: 3)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 7)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 18)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 6)
Advances in Complex Systems     Hybrid Journal   (Followers: 7)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 11)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 22)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 27)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 10)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 30)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in OptoElectronics     Open Access   (Followers: 5)
Advances in Physics Theories and Applications     Open Access   (Followers: 12)
Advances in Polymer Science     Hybrid Journal   (Followers: 41)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 40)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Aerobiologia     Hybrid Journal   (Followers: 2)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 6)
AIChE Journal     Hybrid Journal   (Followers: 32)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Akademik Platform Mühendislik ve Fen Bilimleri Dergisi     Open Access   (Followers: 1)
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 9)
American Journal of Environmental Engineering     Open Access   (Followers: 17)
American Journal of Industrial and Business Management     Open Access   (Followers: 23)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Regional Science     Hybrid Journal   (Followers: 8)
Annals of Science     Hybrid Journal   (Followers: 7)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 6)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 18)
Applied Clay Science     Hybrid Journal   (Followers: 5)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Network Science     Open Access   (Followers: 1)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Physics Research     Open Access   (Followers: 3)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 8)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ASEE Prism     Full-text available via subscription   (Followers: 3)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 1)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 8)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 2)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Avances en Ciencias e Ingeniería     Open Access  
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 1)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 5)
Batteries     Open Access   (Followers: 6)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 24)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 4)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)
BER : Survey of Business Conditions in Retail : An Executive Summary     Full-text available via subscription   (Followers: 4)
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Biofuels Engineering     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 10)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 5)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 18)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 34)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 5)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 4)
Biomedizinische Technik - Biomedical Engineering     Hybrid Journal  
Biomicrofluidics     Open Access   (Followers: 4)
BioNanoMaterials     Hybrid Journal   (Followers: 2)
Biotechnology Progress     Hybrid Journal   (Followers: 39)
Boletin Cientifico Tecnico INIMET     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 14)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 14)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers, Droit, Sciences et Technologies     Open Access  
Calphad     Hybrid Journal  
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 30)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 44)
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 8)
Case Studies in Thermal Engineering     Open Access   (Followers: 4)
Catalysis Communications     Hybrid Journal   (Followers: 6)
Catalysis Letters     Hybrid Journal   (Followers: 2)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 8)
Catalysis Science and Technology     Free   (Followers: 8)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 3)
Catalysis Today     Hybrid Journal   (Followers: 7)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 3)
Central European Journal of Engineering     Hybrid Journal   (Followers: 1)
CFD Letters     Open Access   (Followers: 6)
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencias Holguin     Open Access   (Followers: 1)
CienciaUAT     Open Access  
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Full-text available via subscription   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Full-text available via subscription   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 24)
Clay Minerals     Full-text available via subscription   (Followers: 10)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Coastal Engineering     Hybrid Journal   (Followers: 11)
Coastal Engineering Journal     Hybrid Journal   (Followers: 5)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 4)
Color Research & Application     Hybrid Journal   (Followers: 2)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 13)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 27)
Composite Interfaces     Hybrid Journal   (Followers: 6)
Composite Structures     Hybrid Journal   (Followers: 271)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 199)
Composites Part B : Engineering     Hybrid Journal   (Followers: 256)
Composites Science and Technology     Hybrid Journal   (Followers: 194)
Comptes Rendus Mécanique     Full-text available via subscription   (Followers: 2)
Computation     Open Access  
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Science and Engineering     Open Access   (Followers: 19)
Computers & Geosciences     Hybrid Journal   (Followers: 30)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 7)
Computers and Electronics in Agriculture     Hybrid Journal   (Followers: 5)
Computers and Geotechnics     Hybrid Journal   (Followers: 11)
Computing and Visualization in Science     Hybrid Journal   (Followers: 6)
Computing in Science & Engineering     Full-text available via subscription   (Followers: 33)
Conciencia Tecnologica     Open Access  
Concurrent Engineering     Hybrid Journal   (Followers: 3)
Continuum Mechanics and Thermodynamics     Hybrid Journal   (Followers: 8)
Control and Dynamic Systems     Full-text available via subscription   (Followers: 9)
Control Engineering Practice     Hybrid Journal   (Followers: 43)
Control Theory and Informatics     Open Access   (Followers: 8)
Corrosion Science     Hybrid Journal   (Followers: 25)
Corrosion Series     Full-text available via subscription   (Followers: 6)
CT&F Ciencia, Tecnologia y Futuro     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 | Last

Journal Cover Communications in Numerical Methods in Engineering
  [2 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1069-8299 - ISSN (Online) 1099-0887
   Published by John Wiley and Sons Homepage  [1592 journals]
  • Design Factors of Femur Fracture Fixation Plates made of Shape Memory
           Alloy based on the Taguchi Method by Finite Element Analysis
    • Authors: Cheolwoong Ko; Mikyung Yang, Taemin Byun, Sang-Wook Lee
      Abstract: This study proposed a way to design femur fracture fixation plates made of shape memory alloy based on CT (Computed Tomography) images of Korean cadaveric femurs. To this end, 3 major design factors of femur fracture fixation plates (circumference angle, thickness, and inner diameter) were selected based on the contact pressure when a femur fracture fixation plate was applied to a cylinder model using the Taguchi Method. Then the effects of the design factors were analyzed.It was shown that the design factors were statistically significant at a level of p=0.05 concerning the inner diameter and the thickness. The factors affecting the contact pressure were inner diameter, thickness, and circumference angle, in that order. Particularly, in the condition of Case 9 (inner diameter 27 mm, thickness 2.4 mm, and circumference angle 270 deg), the max. average contact pressure was 21.721 MPa, while the min. average contact pressure was 3.118 MPa in Case 10 (inner diameter 29 mm, thickness 2.0 mm, and circumference angle 210 deg).When the femur fracture fixation plate was applied to the cylinder model, the displacement due to external sliding and pulling forces was analyzed. As a result, the displacement in the sliding condition was at max. 3.75 times greater than that in the pulling condition, which indicated that the cohesion strength between the femur fracture fixation plate and the cylinder model was likely to be greater in the pulling condition.When a human femur model was applied, the max. average contact pressure was 10.76 MPa, which was lower than the yield strength of a human femur (108 MPa). In addition, the analysis of the rib behaviors of the femur fracture fixation plate in relation to the recovery effect of the shape memory alloy, showed that the rib behaviors varied depending on the arbitrarily curved shapes of the femur sections.
      PubDate: 2018-02-15T14:15:25.055549-05:
      DOI: 10.1002/cnm.2967
       
  • Effects of fibroblast-myocyte coupling on the sinoatrial node activity: a
           computational study
    • Authors: Alexey A. Karpaev; Roman A. Syunyaev, Rubin R. Aliev
      Abstract: While the sinoatrial node (SAN) is structurally heterogeneous, the majority of computer simulations of electrical activity take into account SAN pacemaker cells only. Our aim was to investigate how fibroblasts affect the SAN activity. We simulated the rabbit sinoatrial node accounting for differences between central and peripheral pacemaker cells, and for fibroblast-myocyte electrical coupling. We have observed that only if fibroblast-myocyte coupling is taken into account 1) action potential is initiated in the central part of the SAN (within 1.2 mm of the center of simulated tissue), otherwise leading centers are located on the periphery; 2) few (1 to 6) leading centers initiate action potential in the SAN, otherwise we observed more than 8 leading centers; 3) acetylcholine superfusion results in a shift of leading centers toward the SAN periphery; 4) sinus pauses up to 1.9 s follow acetylcholine superfusion. We observed negligible effect of fibroblast-myocyte coupling on the period of SAN activation. We conclude that fibroblast-myocyte coupling may explain action potential initiation and propagation from the center of the SAN observed in experimental studies, while atrial load on the peripheral SAN fails to explain this fact.
      PubDate: 2018-02-12T09:45:30.953403-05:
      DOI: 10.1002/cnm.2966
       
  • Gradient-based optimization with B-splines on sparse grids for solving
           forward-dynamics simulations of three-dimensional, continuum-mechanical
           musculoskeletal system models
    • Authors: J. Valentin; M. Sprenger, D. Pflüger, O. Röhrle
      Abstract: Investigating the interplay between muscular activity and motion is the basis to improve our understanding of healthy or diseased musculoskeletal systems. To be able to analyze the musculoskeletal systems, computational models are employed. Albeit some severe modeling assumptions, almost all existing musculoskeletal system simulations appeal to multi-body simulation frameworks. Although continuum-mechanical musculoskeletal system models can compensate for some of these limitations, they are essentially not considered due to their computational complexity and cost. The proposed framework is the first activation-driven musculoskeletal system model, in which the exerted skeletal muscle forces are computed using three-dimensional, continuum-mechanical skeletal muscle models and in which muscle activations are determined based on a constraint optimization problem. Numerical feasibility is achieved by computing sparse grid surrogates with hierarchical B-splines, and adaptive sparse grid refinement further reduces the computational effort. The choice of B-splines allows the use of all existing gradient-based optimization techniques without further numerical approximation. This paper demonstrates that the resulting surrogates have low relative errors (less than 0.76%) and can be used within forward simulations that are subject to constraint optimization. To demonstrate this, we set up several different test scenarios in which an upper limb model consisting of the elbow joint, the biceps and triceps brachii and an external load is subjected to different optimization criteria. Even though this novel method has only been demonstrated for a two-muscle system, it can easily be extended to musculoskeletal systems with three or more muscles. This article is protected by copyright. All rights reserved.
      PubDate: 2018-02-10T13:20:24.048463-05:
      DOI: 10.1002/cnm.2965
       
  • Predicting drug-induced arrhythmias by multiscale modeling
    • Authors: F. Sahli Costabal; J. Yao, E. Kuhl
      Abstract: Drugs often have undesired side effects. In the heart, they can induce lethal arrhythmias such as torsades de pointes. The risk evaluation of a new compound is costly and can take a long time, which often hinders the development of new drugs. Here we establish a high resolution, multiscale computational model to quickly assess the cardiac toxicity of new and existing drugs. The input of the model is the drug-specific current block from single cell electrophysiology; the output is the spatio-temporal activation profile and the associated electrocardiogram. We demonstrate the potential of our model for a low risk drug, ranolazine, and a high risk drug, quinidine: For ranolazine, our model predicts a prolonged QT interval of 19.4% compared to baseline and a regular sinus rhythm at 60.15 beats per minute. For quinidine, our model predicts a prolonged QT interval of 78.4% and a spontaneous development of torsades de pointes both in the activation profile and in the electrocardiogram. Our model reveals the mechanisms by which electrophysiological abnormalities propagate across the spatio-temporal scales, from specific channel blockage, via altered single cell action potentials and prolonged QT intervals, to the spontaneous emergence of ventricular tachycardia in the form of torsades de pointes. Our model could have important implications for researchers, regulatory agencies, and pharmaceutical companies on rationalizing safe drug development and reducing the time-to-market of new drugs. This article is protected by copyright. All rights reserved.
      PubDate: 2018-02-09T10:45:41.822979-05:
      DOI: 10.1002/cnm.2964
       
  • Issue Information
    • Abstract: No abstract is available for this article.
      PubDate: 2018-02-07T03:57:42.292559-05:
      DOI: 10.1002/cnm.2963
       
  • ASSESSMENT OF MECHANICAL PROPERTIES OF HUMAN HEAD TISSUES FOR TRAUMA
           MODELLING
    • Authors: Estivaliz Lozano-Mínguez; Marta Palomar, Diego Infante-García, María José Rupérez, Eugenio Giner
      Abstract: Many discrepancies are found in the literature regarding the damage and constitutive models for head tissues as well as the values of the constants involved in the constitutive equations. Their proper definition is required for consistent numerical model performance when predicting human head behaviour, and hence skull fracture and brain damage. The objective of this research is to perform a critical review of constitutive models and damage indicators describing human head tissues response under impact loading. A 3D finite element human head model has been generated using computed tomography images, which has been validated through the comparison to experimental data in the literature. The threshold values of the skull and the scalp that lead to fracture have been analysed. We conclude that: 1) compact bone properties are critical in skull fracture, 2) the elastic constants of the cerebrospinal fluid affect the intracranial pressure distribution, and 3) the consideration of brain tissue as a nearly-incompressible solid with a high (but not complete) water content offers pressure responses consistent with the experimental data.
      PubDate: 2018-01-22T21:45:57.185899-05:
      DOI: 10.1002/cnm.2962
       
  • Flow pattern analysis in Type B aortic dissection patients after
           stent-grafting repair: Comparison between complete and incomplete false
           lumen thrombosis
    • Authors: Wan Naimah Wan Ab Naim; Poo Balan Ganesan, Zhonghua Sun, Jing Lei, Shirley Jansen, Shahrul Amry Hashim, Teik Kok Ho, Einly Lim
      Abstract: Endovascular stent graft repair has become a common treatment for complicated Stanford Type B aortic dissection in order to restore true lumen flow and induce false lumen thrombosis. Using computational fluid dynamics, this study reports the differences in flow patterns and wall shear stress distribution in complicated Stanford Type B aortic dissection patients after endovascular stent graft repair. Five patients were included in this study: two having more than 80% false lumen thrombosis (Group 1), while three others had less than 80% false lumen thrombosis (Group 2) within one year following endovascular repair. Group 1 patients had concentrated re-entry tears around the abdominal branches only, while Group 2 patients had re-entry tears that spread along the dissection line. Blood flow inside the false lumen which affected thrombus formation, increased with the number of re-entry tears and when only small amounts of blood that entered the false lumen exited through the branches. In those cases where dissection extended below the abdominal branches (Group 2), patients with fewer re-entry tears and longer distance between the tears had low wall shear stress contributing to thrombosis. This work provides an insight into predicting the development of complete or incomplete false lumen thrombosis and, has implications for patient selection for treatment
      PubDate: 2018-01-13T08:05:27.813327-05:
      DOI: 10.1002/cnm.2961
       
  • Effect of Heated-Air Blanket on the Dispersion of Squames in an Operating
           Room
    • Authors: X. He; S. Karra, P. Pakseresht, S. V. Apte, S. Elghobashi
      Abstract: High-fidelity, predictive fluid flow simulations of the interactions between the rising thermal plumes from forced air warming blower and the ultraclean ventilation air in an operating (OR) are conducted to explore whether this complex flow can impact the dispersion of squames to the surgical site. A large-eddy simulation (LES), accurately capturing the spatio-temporal evolution of the flow in three-dimensions together with the trajectories of squames, is performed for a realistic OR consisting of an operating table (OT), side tables, surgical lamps, medical staff, and a patient. Two cases are studied with blower-off and blower-on together with Lagrangian trajectories of 3 million squames initially placed on the floor surrounding the OT. The LES results show that with the blower-off, squames are quickly transported by the ventilation air away from the table and towards the exit grilles. In contrast, with the hot air blower turned on, the ventilation air flow above and below the OT is disrupted significantly. The rising thermal plumes from the hot air blower drag the squames above the OT and the side tables and then they are advected downwards toward the surgical site by the ventilation air from the ceiling. Temporal history of the number of squames reaching four imaginary boxes surrounding the side tables, the OT, and the patient's knee shows that several particles reach these boxes for the blower-on case. This article is protected by copyright. All rights reserved.
      PubDate: 2018-01-09T02:30:30.489769-05:
      DOI: 10.1002/cnm.2960
       
  • An adaptive Hybridizable Discontinuous Galerkin approach for cardiac
           electrophysiology
    • Authors: J. M. Hoermann; C. Bertoglio, M. Kronbichler, M. R. Pfaller, R. Chabiniok, W. A. Wall
      Abstract: Cardiac electrophysiology simulations are numerically challenging due to the propagation of a steep electrochemical wave front and thus require discretizations with small mesh sizes to obtain accurate results. In this work, we present an approach based on the Hybridizable Discontinuous Galerkin method (HDG), which allows an efficient implementation of high-order discretizations into a computational framework. In particular using the advantage of the discontinuous function space, we present an efficient p-adaptive strategy for accurately tracking the wave front. HDG allows to reduce the overall degrees of freedom in the final linear system to those only on the element interfaces. Additionally, we propose a rule for a suitable integration accuracy for the ionic current term depending on the polynomial order and the cell model to handle high-order polynomials. Our results show that for the same number of degrees of freedom coarse high-order elements provide more accurate results than fine low-order elements. Introducing p-adaptivity further reduces computational costs while maintaining accuracy by restricting the use of high-order elements to resolve the wave front. For a patient-specific simulation of a cardiac cycle p-adaptivity reduces the average number of degrees of freedom by 95% compared to the non-adaptive model. In addition to reducing computational costs, using coarse meshes with our p-adaptive high-order HDG method also simplifies practical aspects of mesh generation and postprocessing. This article is protected by copyright. All rights reserved.
      PubDate: 2018-01-08T09:00:39.550764-05:
      DOI: 10.1002/cnm.2959
       
  • Controlling the error on target motion through real-time mesh adaptation:
           applications to Deep Brain Stimulation
    • Authors: Huu Phuoc Bui; Satyendra Tomar, Hadrien Courtecuisse, Michel Audette, Stéphane Cotin, Stéphane P.A. Bordas
      Abstract: An error-controlled mesh refinement procedure for needle insertion simulations is presented. As an example, the procedure is applied for simulations of electrode implantation for Deep Brain Stimulation. We take into account the brain shift phenomena occurring when a craniotomy is performed. We observe that the error in the computation of the displacement and stress fields is localised around the needle tip and the needle shaft during needle insertion simulation. By suitably and adaptively refining the mesh in this region, our approach enables to control, and thus to reduce, the error whilst maintaining a coarser mesh in other parts of the domain. Through academic and practical examples we demonstrate that our adaptive approach, as compared to a uniform coarse mesh, increases the accuracy of the displacement and stress fields around the needle shaft, while for a given accuracy, saves computational time with respect to a uniform finer mesh. This facilitates real-time simulations. The proposed methodology has direct implications in increasing the accuracy, and controlling the computational expense of the simulation of percutaneous procedures such as biopsy, brachytherapy, regional anesthesia, or cryotherapy. Moreover, the proposed approach can be helpful in the development of robotic surgeries because the simulation taking place in the control loop of a robot needs to be accurate, and to occur in real time. This article is protected by copyright. All rights reserved.
      PubDate: 2018-01-05T02:46:06.926393-05:
      DOI: 10.1002/cnm.2958
       
  • Generalized Backpropagation Algorithm for Training Second-order Neural
           Networks
    • Authors: Fenglei Fan; Wenxiang Cong, Ge Wang
      Abstract: The artificial neural network is a popular framework in machine learning. To empower individual neurons, we recently suggested that the current type of neurons could be upgraded to 2nd order counterparts, in which the linear operation between inputs to a neuron and the associated weights is replaced with a nonlinear quadratic operation. A single 2nd–order neurons already has a strong nonlinear modeling ability, such as implementing basic fuzzy logic operations. In this paper, we develop a general backpropagation (BP) algorithm to train the network consisting of 2nd-order neurons. The numerical studies are performed to verify the generalized BP algorithm.
      PubDate: 2017-12-26T01:15:28.266171-05:
      DOI: 10.1002/cnm.2956
       
  • Magnetic drug targeting simulations in blood flows with fluid-structure
           interaction
    • Authors: S. Calandrini; G. Capodaglio, E. Aulisa
      Abstract: We present fluid-structure interaction (FSI) simulations of magnetic drug targeting (MDT) in blood flows. In this procedure, a drug is attached to ferromagnetic particles in order to externally direct it to a specific target after it is injected inside the body. The goal is to minimize the healthy tissue affected by the treatment and to maximize the number of particles that reach the target location. MDT has been studied both experimentally and theoretically by several authors. In recent years, computational fluid dynamics (CFD) simulations of MDT in blood flows have been carried out to obtain further insight on the combination of parameters that provide the best capture efficiency. However, to this day, no computational study addressed MDT in an FSI setting. With this paper, we aim to fill this gap and investigate the impact of the solid deformation on the capture efficiency. This article is protected by copyright. All rights reserved.
      PubDate: 2017-12-23T13:30:36.429676-05:
      DOI: 10.1002/cnm.2954
       
  • A Compartment-Quasi3D multiscale approach for drug absorption, transport,
           and retention in the human lungs.
    • Authors: Ravishekar (Ravi) Kannan; Narender Singh, Andrzej Przekwas
      Abstract: The majority of current models used for modeling the pulmonary drug absorption, transport, and retention are 0D compartmental models where the airways are generally split into the airways and alveolar sections. Such block models deliver low fidelity solutions and the spatial lung drug concentrations cannot be obtained. Other approaches utilize high fidelity CFD models with limited capabilities due to their exorbitant computational cost. Recently, we presented a novel, fast-running and robust Quasi-3D (Q3D) model for modeling the pulmonary airflow. This Q3D method preserved the 3D lung geometry, delivered extremely accurate solutions and was 25,000 times faster in comparison to the CFD methods. In this paper, we present a Q3D-compartment multiscale combination to model the pulmonary drug absorption, transport, and retention. The initial deposition is obtained from CFD simulations. The lung absorption compartment model of Yu and Rosania is adapted to this multiscale format. The lung is modeled in the Q3D format till 8th airway generation. The remainder of the lung along with the systemic circulation and elimination processes were modeled using compartments. The Q3D model is further adapted, by allowing for various heterogeneous annular lung layers. This allows us to model the drug transport across the layers and along the lung. Using this multiscale model, the spatio-temporal drug concentrations in the different lung layers and the temporal concentration in the plasma are obtained. The concentration profile in the plasma was found to be better aligned with the experimental findings in comparison with compartmental model for the standard test cases. Thus, this multiscale model can be used to optimize the target-specific drug delivery, increase the localized bio-availability, thereby facilitating applications from the bench to bedside for various patient/lung-disease variations.
      PubDate: 2017-12-22T12:15:25.137032-05:
      DOI: 10.1002/cnm.2955
       
  • Machine Learning Based Diagnosis of Melanoma Using Macro Images
    • Authors: D. Gautam; M. Ahmed, Y. K. Meena, A. U. Haq
      Abstract: Cancer bears a poisoning threat to human society. Melanoma, the skin cancer originates from skin layers and penetrates deep into subcutaneous layers. There exists an extensive research in melanoma diagnosis using dermatoscopic images captured through dermatoscope. While designing a diagnostic model for general handheld imaging systems is an emerging trend. This article proposes a computer aided decision support system for macro images captured by a general purpose camera. The general imaging conditions are adversely affected by the non-uniform illumination which further effect the extraction of relevant information. To mitigate it, we process an image to define a smooth illumination surface using the multi-stage illumination compensation approach and the infected region is extracted using proposed multi-mode segmentation method. The lesion information is numerated as a feature set comprising of geometry, photometry, border series and texture measures. The redundancy in feature set is reduced using information theory methods, and a classification boundary is modeled to distinguish benign and malignant samples using Support Vector Machine(SVM), Random Forest(RF), Neural Network(NN) and Fast Discriminative Mixed Membership based Naive Bayesian classifier(FDMMNB). Moreover, the experimental outcome is supported by hypothesis testing and boxplot representation for classification losses. The simulation results prove the significance of proposed model that shows an improved performance as compared to competing arts. This article is protected by copyright. All rights reserved.
      PubDate: 2017-12-20T02:46:12.90603-05:0
      DOI: 10.1002/cnm.2953
       
  • Multi-level hp-finite cell method for embedded interface problems with
           application in biomechanics
    • Authors: Mohamed Elhaddad; Nils Zander, Tino Bog, László Kudela, Stefan Kollmannsberger, Jan S. Kirschke, Thomas Baum, Martin Ruess, Ernst Rank
      Abstract: This work presents a numerical discretization technique for solving three-dimensional material interface problems involving complex geometry without conforming mesh generation. The finite cell method (FCM), which is a high-order fictitious domain approach, is used for the numerical approximation of the solution without a boundary-conforming mesh. Weak discontinuities at material interfaces are resolved by using separate FCM meshes for each material sub-domain, and weakly enforcing the interface conditions between the different meshes. Additionally, a recently developed hierarchical hp-refinement scheme is employed to locally refine the FCM meshes in order to resolve singularities and local solution features at the interfaces. Thereby, higher convergence rates are achievable for non-smooth problems. A series of numerical experiments with two- and three-dimensional benchmark problems is presented, showing that the proposed hp-refinement scheme in conjunction with the weak enforcement of the interface conditions leads to a significant improvement of the convergence rates, even in the presence of singularities. Finally, the proposed technique is applied to simulate a vertebra-implant model. The application showcases the method's potential as an accurate simulation tool for biomechanical problems involving complex geometry, and it demonstrates its flexibility in dealing with different types of geometric description. This article is protected by copyright. All rights reserved.
      PubDate: 2017-12-19T04:36:30.586625-05:
      DOI: 10.1002/cnm.2951
       
  • An efficient parallel simulation of unsteady blood flows in
           patient-specific pulmonary artery
    • Authors: Fande Kong; Vitaly Kheyfets, Ender Finol , Xiao-Chuan Cai
      Abstract: Simulation of blood flows in the pulmonary artery provides some insight into certain diseases by examining the relationship between some continuum metrics, e.g. the wall shear stress acting on the vascular endothelium, which responds to flow-induced mechanical forces by releasing vasodilators/constrictors. In ['kheyfets2015patient], V. Kheyfets studies numerically a patient-specific pulmonary circulation to show that decreasing wall shear stress is correlated with increasing pulmonary vascular impedance. In this paper, we develop a scalable parallel algorithm based on domain decomposition methods to investigate an unsteady model with patient specific pulsatile waveforms as the inlet boundary condition. The unsteady model offers tremendously more information about the dynamic behavior of the flow field, but computationally speaking, the simulation is a lot more expensive since a problem which is similar to the steady state problem has to be solved many times, and therefore, the traditional sequential approach is not suitable anymore. We show computationally that simulations using the proposed parallel approach with up to 10,000 processor cores can be obtained with much reduced compute time. This makes the technology potentially usable for the routine study of the dynamic behavior of blood flows in the pulmonary artery, in particular, the changes of the blood flows and the wall shear stress in the spatial and temporal dimensions. This article is protected by copyright. All rights reserved.
      PubDate: 2017-12-15T17:11:15.497595-05:
      DOI: 10.1002/cnm.2952
       
  • Computational study of estimating 3D trabecular bone microstructure for
           the volume of interest from CT scan data
    • Authors: Jung Jin Kim; Jimin Nam, In Gwun Jang
      Abstract: Inspired by the self-optimizing capabilities of bone, a new concept of bone microstructure reconstruction has been recently introduced using 2D synthetic skeletal images. As a preliminary clinical study, this paper proposes a topology optimization-based method that can estimate 3D trabecular bone microstructure for the volume of interest (VOI) from 3D computed tomography (CT) scan data with enhanced computational efficiency and phenomenological accuracy. For this purpose, a localized finite element (FE) model is constructed by segmenting a target bone from CT scan data and determining the physiological local loads for the VOI. Then, topology optimization is conducted with multi-resolution bone mineral density (BMD) deviation constraints to preserve the patient-specific spatial bone distribution obtained from the CT scan data. For the first time, to our knowledge, this study has demonstrated that 60 μm-resolution trabecular bone images can be reconstructed from 600 μm-resolution CT scan data (a 62-year-old female with no metabolic bone disorder) for the four VOIs in the proximal femur. The reconstructed trabecular bone includes the characteristic trabecular patterns and has morphometric indices that are in good agreement with the anatomical data in the literature. As for computational efficiency, the localization for the VOI reduces the number of FEs by 99%, compared with that of the full FE model. Compared with the previous single-resolution BMD deviation constraint, the proposed multi-resolution BMD deviation constraints enable at least 65% and 47% reduction in the number of iterations and computing time, respectively. These results demonstrate the clinical feasibility and potential of the proposed method.
      PubDate: 2017-12-07T22:42:05.146868-05:
      DOI: 10.1002/cnm.2950
       
  • Model for pressure drop and flow deflection in the numerical simulation of
           stents in aneurysms
    • Authors: S. Li; J. Latt, B. Chopard
      Abstract: The numerical simulation of flow diverters like stents contributes to the development and improvement of endovascular stenting procedures, leading ultimately to an improved treatment of intracranial aneurysms. Due to the scale difference between the struts of flow diverters and the full artery, it is common to avoid fully resolved simulations at the level of the stent porosity. Instead, the effect of stents on the flow is represented by a heuristic continuum model. However, the commonly used porous media models describe the properties of flow diverters only partially, because they do not explicitly account for the deflection of the flow direction by the stent. We show that this deficiency can be circumvented by adopting the theoretical framework of screen models. The article first reviews existing screen models. It then proposes an explicit formula for the drag and the deflection coefficient, as predicted by each model, for both perpendicular and inclined angles. The results of 2D numerical simulations are used to formulate a generalization of these formulas, to achieve best results in the case of stent modeling. The obtained model is then validated, again through 2D numerical simulation. This article is protected by copyright. All rights reserved.
      PubDate: 2017-12-01T20:10:36.323159-05:
      DOI: 10.1002/cnm.2949
       
  • Preconditioned Augmented Lagrangian formulation for nearly incompressible
           cardiac mechanics
    • Authors: J. O. Campos; R. W. Dos Santos, J. Sundnes, B. M. Rocha
      Abstract: Computational modeling of the heart is a subject of substantial medical and scientific interest, which may contribute to increase the understanding of several phenomena associated with cardiac physiological and pathological states. Modeling the mechanics of the heart have led to considerable insights, but it still represents a complex and a demanding computational problem, especially in a strongly coupled electromechanical setting. Passive cardiac tissue is commonly modeled as hyperelastic, and is characterized by quasi-incompressible, orthotropic and non-linear material behavior. These factors are known to be very challenging for the numerical solution of the model. The near-incompressibility is known to cause numerical issues such as the well known locking phenomenon and ill-conditioning of the stiffness matrix. In this work, the Augmented Lagrangian method (ALG) is used to handle the nearly incompressible condition. This approach can potentially improve computational performance by reducing the condition number of the stiffness matrix and thereby improving the convergence of iterative solvers. We also improve the performance of iterative solvers by the use of an algebraic multigrid preconditioner. Numerical results of the ALG method combined with a preconditioned iterative solver for a cardiac mechanics benchmark suite are presented to show its improved performance. This article is protected by copyright. All rights reserved.
      PubDate: 2017-11-27T21:15:28.374672-05:
      DOI: 10.1002/cnm.2948
       
  • Fluid-structure interaction of a pulsatile flow with an aortic valve
           model: a combined experimental and numerical study
    • Authors: J. Sigüenza; D. Pott, S. Mendez, S. J. Sonntag, T. A. S. Kaufmann, U. Steinseifer, F. Nicoud
      Abstract: The complex fluid-structure interaction problem associated with the flow of blood through a heart valve with flexible leaflets is investigated both experimentally and numerically. In the experimental test rig, a pulse duplicator generates a pulsatile flow through a biomimetic rigid aortic root where a model of aortic valve with polymer flexible leaflets is implanted. High-speed recordings of the leaflets motion and Particle Image Velocimetry measurements were performed together to investigate the valve kinematics and the dynamics of the flow. Large eddy simulations of the same configuration, based on a variant of the immersed boundary method, are also presented. A massively parallel unstructured finite-volume flow solver is coupled with a finite-element solid mechanics solver to predict the fluid-structure interaction between the unsteady flow and the valve. Detailed analysis of the dynamics of opening and closure of the valve are carried out, showing a good quantitative agreement between the experiment and the simulation regarding the global behavior, in spite of some differences regarding the individual dynamics of the valve leaflets. A multi-cycle analysis (over more than 20 cycles) enables to characterize the generation of turbulence downstream of the valve, showing similar flow features between the experiment and the simulation. The flow transitions to turbulence after peak systole, when the flow starts to decelerate. redFluctuations are observed in the wake of the valve, with maximum amplitude observed at the commissure side of the aorta. Overall, a very promising experiment-vs-simulation comparison is shown, demonstrating the potential of the numerical method. This article is protected by copyright. All rights reserved.
      PubDate: 2017-11-27T20:20:47.834431-05:
      DOI: 10.1002/cnm.2945
       
  • Acoustophoretic separation of infected erythrocytes from blood plasma in a
           microfluidic platform using biofunctionalized, matched-impedance layers
    • Authors: Tamaghna Gupta; Ritwick Ghosh, Ranjan Ganguly
      Abstract: Acoustophoresis is rapidly gaining prominence in the field of cell manipulation. In recent years, researchers have extensively used this method for separating different types of cells from the bulk fluid. In this paper, we propose a novel acoustophoresis based technique to capture infected or abnormal erythrocytes from blood plasma. A typical acoustic device consisting of a transducer assembly, microfluidic cavity and a reflector is considered. Based on the concept of impedance matching a pair of antibody-coated polystyrene layers is placed in the nodal regions of an acoustic field within the cavity. This technique allows bi-directional migration of the suspended cells to the biofunctionalized surfaces. Therefore, simultaneous capture of infected erythrocytes on both the layers is feasible. FEM is used to model the pressure field as well as the motion of erythrocytes under the influence of acoustic radiation, drag and gravitational forces. A parametric analysis is done by varying the excitation frequency, driving voltage and the thickness of the polystyrene layers. The resulting changes in the pressure amplitude and field pattern are investigated. The erythrocyte collection efficiency, rate of collection and the cell distribution on the layer surfaces are also determined under different field conditions. The occurrence of transient cavitation in the blood plasma-filled cavity at the chosen frequency is taken into account by using its threshold pressure value as the limiting factor of pressure amplitude. The study provides an insight into the phenomenon and serves as a guideline to fabricate low-cost, multifunctional rapid diagnostic devices based on acoustophoretic separation.
      PubDate: 2017-11-27T10:16:24.901663-05:
      DOI: 10.1002/cnm.2943
       
  • On computational fluid dynamics models for sinonasal drug transport:
           relevance of nozzle subtraction and nasal vestibular dilation
    • Authors: S. Basu; D. O. Frank-Ito, J. S. Kimbell
      Abstract: Generating anatomically realistic three-dimensional (3D) models of the human sinonasal cavity for numerical investigations of sprayed drug transport presents a host of methodological ambiguities. For example, subject-specific radiographic images used for 3D reconstructions typically exclude spray bottles. Subtracting a bottle contour from the 3D airspace and dilating the anterior nasal vestibule for nozzle placement augment the complexity of model-building. So, we explored the question: how essential are these steps to adequately simulate nasal airflow and identify the optimal delivery conditions for intranasal sprays' In particular, we focused on particle deposition patterns in the maxillary sinus, a critical target site for chronic rhinosinusitis (CRS). The models were reconstructed from post-surgery computed tomography scans for a 39-year-old Caucasian male, with CRS history. Inspiratory airflow patterns during resting breathing are reliably tracked through CFD-based steady state laminar-viscous modeling and such regimes portray relative lack of sensitivity to inlet perturbations. Consequently, we hypothesized that the posterior airflow transport and the particle deposition trends should not be radically affected by the nozzle subtraction and vestibular dilation. The study involved 1 base model and 2 derived models; the latter two with nozzle contours (two different orientations) subtracted from the dilated anterior segment of the left vestibule. We analyzed spray transport in the left maxillary sinus for multiple release conditions. Similar release points, localized on an approximately 2mm-by-4.5mm contour, facilitated improved maxillary deposition in all three test cases. This suggests functional redundancy of nozzle insertion in a 3D numerical model for identifying the optimal spray release locations. This article is protected by copyright. All rights reserved.
      PubDate: 2017-11-24T19:40:27.578547-05:
      DOI: 10.1002/cnm.2946
       
  • Computational predictions of damage propagation preceding dissection of
           ascending thoracic aortic aneurysms
    • Authors: S. J. Mousavi; S. Farzaneh, S. Avril
      Abstract: Dissections of ascending thoracic aortic aneurysms (ATAA) cause significant morbidity and mortality worldwide. They occur when a tear in the intima-media of the aorta permits the penetration of the blood and the subsequent delamination and separation of the wall in two layers, forming a false channel. In order to predict computationally the risk of tear formation, stress analyses should be performed layer-specifically and they should consider internal or residual stresses which exist in the tissue. In the present paper, we propose a novel layer–specific damage model based on the constrained mixture theory (CMT) which intrinsically takes into account these internal stresses and which can predict appropriately the tear formation. The model is implemented in finite-element commercial software Abaqus coupled with user material subroutine (UMAT). Its capability is tested by applying it to the simulation of different exemplary situations, going from in vitro bulge-inflation experiments on aortic samples to in vivo over-pressurizing of patient-specific ATAAs. The simulations reveal that damage correctly starts from the intimal layer (luminal side) and propagates across the media as a tear, but never hits the adventitia. This scenario is typically the first stage of development of an acute dissection, which is predicted for pressures of about 2.5 times the diastolic pressure by the model after calibrating the parameters against experimental data carried out on collected ATAA samples. Further validations on a larger cohort of patients should hopefully confirm the potential of the model in predicting patient-specific damage evolution and possible risk of dissection during aneurysm growth for clinical applications.
      PubDate: 2017-11-23T20:40:26.962607-05:
      DOI: 10.1002/cnm.2944
       
  • Nonlinear micro-CT based FE modeling of trabecular bone – Sensitivity of
           apparent response to tissue constitutive law and bone volume fraction
    • Authors: F.A. Sabet; O. Jin, S. Koric, I. Jasiuk
      Abstract: In this study, the sensitivity of the apparent response of trabecular bone to different constitutive models at the tissue-level was investigated using finite element modeling based on micro-computed tomography. Trabecular bone specimens from porcine femurs were loaded under a uniaxial compression experimentally and computationally. The apparent behaviors computed using von Mises, Drucker-Prager, and Cast Iron plasticity models were compared. Secondly, the effect of bone volume fraction was studied by changing the bone volume fraction of a trabecular bone sample and while keeping the same basic architecture. Also, constitutive models’ parameters of the tissue were calibrated for porcine bone and the effects of different parameters on resulting apparent response were investigated through a parametric study. The calibrated effective tissue elastic modulus of porcine trabecular bone was 10±1.2 GPa, which is in the lower range of modulus values reported in the literature for human and bovine trabecular bones (4-23.8 GPa). It was also observed that, unlike elastic modulus, yield properties of tissue could not be uniquely calibrated by fitting an apparent response from simulations to experiments under a uniaxial compression. Our results demonstrated that using these three tissue constitutive models had only a slight effect on the apparent response. As expected, there was a significant change in the apparent response with varying bone volume fraction. Also, both apparent modulus and maximum stress had a linear relation with bone volume fraction.
      PubDate: 2017-11-22T21:30:29.826613-05:
      DOI: 10.1002/cnm.2941
       
  • Electro-Mechanical Response of a 3D Nerve Bundle Model to Mechanical Loads
           Leading to Axonal Injury
    • Authors: I. Cinelli; M. Destrade, M. Duffy, P. McHugh
      Abstract: ObjectiveTraumatic brain injuries and damage are major causes of death and disability. We propose a 3D fully coupled electro-mechanical model of a nerve bundle to investigate the electrophysiological impairments due to trauma at the cellular level.MethodsThe coupling is based on a thermal analogy of the neural electrical activity by using the finite element software Abaqus CAE 6.13-3. The model includes a real-time coupling, modulated threshold for spiking activation and independent alteration of the electrical properties for each 3-layer fibre within a nerve bundle as a function of strain.ResultsResults of the coupled electro-mechanical model are validated with previously published experimental results of damaged axons. Here, the cases of compression and tension are simulated to induce (mild, moderate and severe) damage at the nerve membrane of a nerve bundle, made of four fibres. Changes in strain, stress distribution, and neural activity are investigated for myelinated and unmyelinated nerve fibres, by considering the cases of an intact and of a traumatized nerve membrane.ConclusionA fully coupled electro-mechanical modelling approach is established to provide insights into crucial aspects of neural activity at the cellular level due to traumatic brain injury.SignificanceOne of the key findings is the 3D distribution of residual stresses and strains at the membrane of each fibre due to mechanically-induced electrophysiological impairments, and its impact on signal transmission.
      PubDate: 2017-11-21T10:55:25.972809-05:
      DOI: 10.1002/cnm.2942
       
  • Relationship between the left ventricular size and the amount of
           trabeculations
    • Authors: Bruno Paun; Bart Bijnens, Constantine Butakoff
      Abstract: Contemporary imaging modalities offer non-invasive quantification of myocardial deformation; however, they make gross assumptions about internal structure of the cardiac walls. Our aim is to study the possible impact of the trabeculations on the stroke volume, strain and capacity of differently sized ventricles. The cardiac left ventricle is represented by an ellipsoid and the trabeculations by a tissue occupying a fixed volume. The ventricular contraction is modelled by scaling the ellipsoid whereupon the measurements of longitudinal strain, end-diastolic, end-systolic and stroke volume are derived and compared. When the trabeculated and non-trabeculated ventricles, having the same geometry and deformation pattern, contain the same amount of blood and contract with the same strain, we observed an increased stroke volume in our model of the trabeculated ventricle. When these ventricles contain and eject the same amount of blood, we observed a reduced strain in the trabeculated case. We identified that a trade-off between the strain and the amount of trabeculations could be reached with a 0.35-0.41 cm dense trabeculated layer, without blood filled recesses (for a ventricle with end-diastolic volume of about 150 ml). A trabeculated ventricle can work at lower strains compared to a non-trabeculated ventricle to produce the same stroke volume, which could be a possible explanation why athletes and pregnant women develop reversible signs of left ventricular non-compaction, since the trabeculations could help generating extra cardiac output. This knowledge might help to assess heart failure patients with dilated cardiomyopathies who often show signs of non-compaction.
      PubDate: 2017-11-09T21:45:31.006267-05:
      DOI: 10.1002/cnm.2939
       
  • A framework for designing patient-specific bioprosthetic heart valves
           using immersogeometric fluid–structure interaction analysis
    • Authors: Fei Xu; Simone Morganti, Rana Zakerzadeh, David Kamensky, Ferdinando Auricchio, Alessandro Reali, Thomas J.R. Hughes, Michael S. Sacks, Ming-Chen Hsu
      Abstract: Numerous studies have suggested that medical image derived computational mechanics models could be developed to reduce mortality and morbidity due to cardiovascular diseases by allowing for patient-specific surgical planning and customized medical device design. In this work, we present a novel framework for designing prosthetic heart valves using a parametric design platform and immersogeometric fluid–structure interaction (FSI) analysis. We parameterize the leaflet geometry using several key design parameters. This allows for generating various perturbations of the leaflet design for the patient-specific aortic root reconstructed from the medical image data. Each design is analyzed using our hybrid arbitrary Lagrangian–Eulerian/immersogeometric FSI methodology, which allows us to efficiently simulate the coupling of the deforming aortic root, the parametrically designed prosthetic valves, and the surrounding blood flow under physiological conditions. A parametric study is carried out to investigate the influence of the geometry on heart valve performance, indicated by the effective orifice area (EOA) and the coaptation area (CA). Finally, the FSI simulation result of a design that balances EOA and CA reasonably well is compared with patient-specific phase contrast magnetic resonance imaging data to demonstrate the qualitative similarity of the flow patterns in the ascending aorta. This article is protected by copyright. All rights reserved.
      PubDate: 2017-11-09T01:50:26.918554-05:
      DOI: 10.1002/cnm.2938
       
  • Evaluation of Hemodynamic Performance of Total Cavopulmonary Connection
           (TCPC) with Porous Inserts
    • Authors: K. Dhayananth; Arunn Narasimhan
      Abstract: Infants born with univentricular heart disease undergo Fontan surgery in order to establish separate systemic and pulmonary circulations. This surgery results in better blood circulation across a single ventricle that supplies oxygenated blood to the body and passively returns venous blood to the lungs through the total cavopulmonary connection (TCPC). Reducing the pressure drop across the TCPC during Fontan circulation helps in reducing the work load of univentricular heart and various designs have been proposed for this purpose. The goal of this work is to analyze the effect of placing a porous insert at an appropriate position in the pulmonary artery, on the pressure drop across the TCPC. A 3D computational model of a total TCPC connection provided with a porous insert is developed and solved by finite volume method, under assumptions of steady, laminar and Newtonian flows. The effects of the porous medium properties - porosity and permeability - across the connection, are analyzed. Compared to the no-porous medium case, TCPC with the porous medium insert, exhibits a maximum reduction of 27% in energy loss for the flow range studied. The porous medium employed in TCPC connection lowers the energy dissipation by curtailing the flow recirculation zones across the connection. The influences of the diameter of the blood vessel, total cardiac output, and the thickness, permeability and position of porous media, on energy loss are analyzed. The criteria to select the porous medium properties and position for a given Fontan geometry are also determined. This article is protected by copyright. All rights reserved.
      PubDate: 2017-11-08T09:03:20.981662-05:
      DOI: 10.1002/cnm.2937
       
  • Approach for Gait Analysis in Persons with Limb Loss Including Residuum
           and Prosthesis Socket Dynamics
    • Authors: A.K. LaPrè; M. Price, R. Wedge, B.R. Umberger, F. Sup
      Abstract: Musculoskeletal modeling and marker based motion capture techniques are commonly used to quantify the motions of body segments, and the forces acting on them during human gait. However, when these techniques are applied to analyze the gait of people with lower limb loss, the clinically relevant interaction between the residual limb and prosthesis socket is typically overlooked. It is known that there is considerable motion and loading at the residuum-socket interface, yet traditional gait analysis techniques do not account for these factors due to the inability to place tracking markers on the residual limb inside of the socket. In the present work, we used a global optimization technique and anatomical constraints to estimate the motion and loading at the residuum-socket interface as part of standard gait analysis procedures. We systematically evaluated a range of parameters related to the residuum-socket interface, such as the number of degrees of freedom, and determined the configuration that yields the best compromise between faithfully tracking experimental marker positions while yielding anatomically realistic residuum-socket kinematics and loads that agree with data from the literature. Application of the present model to gait analysis for people with lower limb loss will deepen our understanding of the biomechanics of walking with a prosthesis, which should facilitate the development of enhanced rehabilitation protocols and improved assistive devices.
      PubDate: 2017-11-07T06:40:20.315769-05:
      DOI: 10.1002/cnm.2936
       
  • PREDICTING THE ROLE OF MICROSTRUCTURAL AND BIOMECHANICAL CUES IN TUMOR
           GROWTH AND SPREADING
    • Authors: Raffaella Santagiuliana; Rui Pereira, Bernhard A. Schrefler, Paolo Decuzzi
      Abstract: A multitude of mathematical and computational approaches have been proposed for predicting tumor growth. Yet, most models treat malignant masses as fluids neglecting microstructural and biomechanical features of the tumor extracellular matrix (ECM). Here, a continuum porous media model is developed within the thermodynamically constrained averaging theory (TCAT) framework for elucidating the role of these mechanical cues in regulating tumor growth and spreading. The model comprises three fluid phases – tumor cells, host cells, and interstitial fluid – and a solid phase – the ECM – considered as an elasto-visco-plastic medium. After validating the computational model against a multicellular tumor spheroid of glioblastoma multiforme, the effect on tumor development of ECM stiffness, adhesion with tumor cells and porosity is investigated. It is shown that stiffer matrices and higher cell-matrix adhesion limit tumor growth and spreading towards the surrounding tissue. A decrease in ECM Young's modulus E from 600 to 200 Pa induces a 60% increase in tumor mass within 8 days of observation. Similarly, a decrease of the adhesion parameter μ from 40 to 5 is responsible for an increase in tumor mass of 100%. On the other hand, higher matrix porosities favor the growth of the malignant mass and the dissemination of tumor cells. A modest increase in the porosity parameter ε from 0.7 to 0.9 is associated with a 300% increase in tumor mass. This model could be used for predicting the response of malignant masses to novel therapeutic agents affecting directly the tumor microenvironment and its micromechanical cues.
      PubDate: 2017-10-30T08:10:20.20469-05:0
      DOI: 10.1002/cnm.2935
       
  • PET-CT Image Fusion using Random Forest and À-trous Wavelet Transform
    • Authors: Ayan Seal; Debotosh Bhattacharjee, Mita Nasipuri, Dionisio Rodríguez-Esparragón, Ernestina Menasalvas, Consuelo Gonzalo-Martin
      Abstract: New image fusion rules for multimodal medical images are proposed in this work. Image fusion rules are defined by Random Forest (RF) learning algorithm and a translation-invariant à-trous wavelet transform (AWT). The proposed method is threefold. First, source images are decomposed into approximation and detail coefficients using AWT. Second, RF is used to choose pixels from the approximation and detail coefficients for forming the approximation and detail coefficients of the fused image. Lastly, inverse AWT (iAWT) is applied to reconstruct fused image. All experiments have been performed on 198 slices of both Computed Tomography (CT) and Positron Emission Tomography (PET) images of a patient. A traditional fusion method based on Mallat wavelet transform has also been implemented on these slices. A new image fusion performance measure along with four existing measures has been presented, which helps to compare the performance of two pixel level fusion methods. The experimental results clearly indicate that the proposed method outperforms the traditional method in terms of visual and quantitative qualities and the new measure is meaningful. This article is protected by copyright. All rights reserved.
      PubDate: 2017-10-27T14:10:22.038313-05:
      DOI: 10.1002/cnm.2933
       
  • Image Enhancement Variational Methods for Enabling Strong Cost Reduction
           in OLED-based Point-of-Care Immunofluorescent Diagnostic Systems
    • Authors: Damiana Lazzaro; serena morigi, Patrizia Melpignano, Elena Piccolomini, Luca Benini
      Abstract: Objective:Immunofluorescence diagnostic systems cost is often dominated by high-sensitivity, low-noise CCD-based cameras which are used to acquire the fluorescence images. In this paper we investigate the use of low-cost CMOS sensors in a point-of-care immunofluorescence diagnostic application for the detection and discrimination of four different serotypes of the Dengue virus in a set of human samples. Methods: A two-phase post-processing software pipeline is proposed which consists in a first image enhancement stage for resolution increasing and segmentation, and a second diagnosis stage for the computation of the output concentrations. Results: blackWe present a novel variational coupled model for the joint super-resolution and segmentation stage, and an automatic innovative image analysis for the diagnosis purpose. A specially designed Forward Backward-based numerical algorithm is introduced and its convergence is proved under mild conditions. We present results on a cheap prototype CMOS camera compared with the results of a more expensive CCD device, for the detection of the Dengue virus with a low-cost OLED light source. The combination of the CMOS sensor and the developed post-processing software allows to correctly identify the different Dengue serotype using an automatized procedure. Conclusions: The results demonstrate that our diagnostic imaging system enables camera cost reduction up to 99%, at an acceptable diagnostic accuracy, with respect to the reference CCD-based camera system. The correct detection and identification of the Dengue serotypes has been confirmed by standard diagnostic methods (RT-PCR and ELISA). This article is protected by copyright. All rights reserved.
      PubDate: 2017-10-27T05:10:25.000612-05:
      DOI: 10.1002/cnm.2932
       
  • Numerical Methods for Polyline-to-Point-Cloud Registration with
           Applications to Patient-Specific Stent Reconstruction
    • Authors: Claire Yilin Lin; Alessandro Veneziani, Lars Ruthotto
      Abstract: We present novel numerical methods for Polyline-to-Point-Cloud Registration and their application to patient-specific modeling of deployed coronary artery stents from image data. Patient-specific coronary stent reconstruction is an important challenge in computational hemodynamics and relevant to the design and improvement of the prostheses. It is an invaluable tool in large-scale clinical trials that computationally investigate the effect of new generations of stents on hemodynamics and eventually tissue remodeling. Given a point cloud of strut positions, which can be extracted from images, our stent reconstruction method aims at finding a geometrical transformation that aligns a model of the undeployed stent to the point cloud. Mathematically, we describe the undeployed stent as a polyline, which is a piecewise linear object defined by its vertices and edges. We formulate the nonlinear registration as an optimization problem whose objective function consists of a similarity measure, quantifying the distance between the polyline and the point cloud, and a regularization functional, penalizing undesired transformations. Using projections of points onto the polyline structure, we derive novel distance measures. Our formulation supports most commonly used transformation models including very flexible nonlinear deformations. We also propose two regularization approaches ensuring the smoothness of the estimated nonlinear transformation. We demonstrate the potential of our methods using an academic 2D example and a real-life 3D bioabsorbable stent reconstruction problem. Our results show that the registration problem can be solved to sufficient accuracy within seconds using only a few number of Gauss-Newton iterations. This article is protected by copyright. All rights reserved.
      PubDate: 2017-10-26T12:50:23.057323-05:
      DOI: 10.1002/cnm.2934
       
  • Influence of atrial contraction dynamics on cardiac function
    • Authors: Sander Land; Steven A. Niederer
      Abstract: In recent years, there has been a move from mono- or biventricular models of the heart, to more complex models that incorporate the electromechanical function in all four chambers. However, the biophysical foundation is still under-developed, with most work in atrial cellular models having focused on electrophysiological properties. Here we present a biophysical model of human atrial contraction at body temperature, and use it to study the effects of atrial contraction on whole organ function, and a study of the effects of remodelling due to atrial fibrillation on atrial and ventricular function. This article is protected by copyright. All rights reserved.
      PubDate: 2017-10-08T22:45:26.19161-05:0
      DOI: 10.1002/cnm.2931
       
  • Influence of Bronchial Diameter Change on the airflow dynamics Based on a
           Pressure-controlled Ventilation System
    • Authors: Shuai Ren; Maolin Cai, Yan Shi, Weiqing Xu, Xiaohua Douglas Zhang
      Abstract: Bronchial diameter is a key parameter that affects the respiratory treatment of mechanically ventilated patients. In this paper, to reveal the influence of bronchial diameter on the airflow dynamics of pressure-controlled mechanically ventilated patients, a new respiratory system model is presented which combines multi-generation airways with lungs. Furthermore, experiments and simulation studies to verify the model are performed. Finally, through the simulation study, it can be determined that in airway generations 2 to 7, when the diameter is reduced to half of the original value, the maximum air pressure (maximum air pressure in lungs) decreases by nearly 16%, the maximum flow decreases by nearly 30%, and the total airway pressure loss (sum of each generation pressure drop) is more than 5 times the original value. Moreover, in airway generations 8 to 16, with increasing diameter, the maximum air pressure, maximum flow and total airway pressure loss remain almost constant. When the diameter is reduced to half of the original value, the maximum air pressure decreases by 3%, the maximum flow decreases by nearly 5%, and the total airway pressure loss increases by 200%. The study creates a foundation for improvement in respiratory disease diagnosis and treatment.
      PubDate: 2017-09-14T07:40:35.205308-05:
      DOI: 10.1002/cnm.2929
       
  • Hybrid cell-centred/vertex model for multicellular systems with
           equilibrium-preserving remodelling
    • Authors: P. Mosaffa; A. Rodríguez-Ferran, J. J. Muñoz*
      Abstract: We present a hybrid vertex/cell-centred model for mechanically simulating planar cellular monolayers undergoing cell reorganisation. Cell centres are represented by a triangular nodal network, while the cell boundaries are formed by an associated vertex network. The two networks are coupled through a kinematic constraint which we allow to relax progressively. Special attention is paid to the change of cell-cell connectivity due to cell reorganisation or remodelling events. We handle these situations by using a variable resting length and applying an Equilibrium-Preserving Mapping (EPM) on the new connectivity, which computes a new set of resting lengths that preserve nodal and vertex equilibrium. We illustrate the properties of the model by simulating monolayers subjected to imposed extension and during a wound healing process. The evolution of forces and the EPM are analysed during the remodelling events. As a by-product, the proposed technique enables to recover fully vertex or fully cell-centred models in a seamless manner by modifying a numerical parameter of the model. This article is protected by copyright. All rights reserved.
      PubDate: 2017-09-12T16:50:31.860935-05:
      DOI: 10.1002/cnm.2928
       
  • Haptic simulation of tissue tearing during surgery
    • Authors: C. Quesada; I. Alfaro, D. González, F. Chinesta, E. Cueto
      Abstract: We present a method for the real-time, interactive simulation of tissue tearing during laparoscopic surgery. The method is designed to work at haptic feedback rates (i.e., around 1kHz). Tissue tearing is simulated under the general framework of continuum damage mechanics. The problem is stated as a general, multidimensional parametric problem, which is solved by means of Proper Generalized Decomposition (PGD) methods. One of the main novelties is the reduction of history-dependent problems, such as damage mechanics, by resorting to an approach in which a reduced-order field of initial damage values is considered as a parameter of the formulation. We focus on the laparoscopic cholecystectomy procedure as a general example of the performance of the method. This article is protected by copyright. All rights reserved.
      PubDate: 2017-09-12T15:05:30.252407-05:
      DOI: 10.1002/cnm.2926
       
  • Viscous effects in pelvic floor muscles during childbirth: a numerical
           study
    • Authors: M.C.P. Vila Pouca; J.P.S. Ferreira, D.A. Oliveira, M.P.L. Parente, R.M. Natal Jorge
      Abstract: During vaginal delivery women sustain stretching of their pelvic floor, risking tissue injury and adverse outcomes. Realistic numerical simulations of childbirth can help in the understanding of the pelvic floor mechanics and on the prevention of related disorders.In previous studies, biomechanical finite element simulations of a vaginal delivery have been performed disregarding the viscous effects present on all biological soft tissues. The inclusion of the viscoelastic behaviour is fundamental, since it allows to investigate rate-dependent responses. The present work uses a visco-hyperelastic constitutive model to evaluate how the childbirth duration affects the efforts sustained by the pelvic floor during delivery.It was concluded that viscoelasticity adds a stiffness component that leads to higher forces comparing with the elastic response. Viscous solutions are rate-dependent and precipitous labours could be associated to higher efforts, while lower reaction forces were denoted for normal and prolonged labours, respectively. The existence of resting stages during labour demonstrated the capability of the tissue to relax and recover some of the initial properties, which helped to lower the forces and stresses involved.The present work represents a step further in achieving a robust non-invasive procedure, allowing to estimate how obstetrical factors influence labour and its outcomes.
      PubDate: 2017-09-08T16:50:24.626422-05:
      DOI: 10.1002/cnm.2927
       
  • Relative pressure estimation from velocity measurements in blood flows:
           state-of-the-art and new approaches
    • Authors: Cristóbal Bertoglio; Rodolfo Núñez, Felipe Galarce, David Nordsletten, Axel Osses
      Abstract: The relative pressure difference across stenotic blood vessels serves as an important clinical index for the diagnosis of many cardiovascular diseases. While the clinical gold standard for relative pressure difference measurements is invasive catheterization, Phase-Contrast Magnetic Resonance Imaging has emerged as a promising tool for enabling a non-invasive quantification, by linking highly spatially resolved velocity measurements with relative pressures via the incompressible Navier-Stokes equations. In this work we provide a review and analysis of current methods for relative pressure estimation and propose three additional techniques. Methods are compared using synthetic data from numerical examples and sensitivity to subsampling and noise was explored. Through our analysis, we verify that the newly proposed approaches are more robust with respect to spatial subsampling and less sensitive to noise, and therefore provide improved means for estimating relative pressure differences non-invasively. This article is protected by copyright. All rights reserved.
      PubDate: 2017-09-07T21:20:41.749902-05:
      DOI: 10.1002/cnm.2925
       
  • Flow Features and Device-Induced Blood Trauma in CF-VADs under a pulsatile
           blood flow condition: A CFD Comparative Study
    • Authors: Zengsheng Chen; Sofen K. Jena, Guruprasad A. Giridharan, Steven C. Koenig, Mark S. Slaughter, Bartley P. Griffith, Zhongjun J. Wu
      Abstract: In this study, the flow features and device-associated blood trauma in four clinical ventricular assist devices (VADs) (two implantable axial VADs, one implantable centrifugal VAD, and one extracorporeal VAD) were computationally analyzed under clinically relevant pulsatile flow conditions. The four VADs were operated at fixed pump speed at a mean rate of 4.5 L/min. Mean pressure difference, wall shear stress (WSS), volume distribution of scalar shear stress (SSS), and shear-induced hemolysis index (HI) were derived from the flow field of each VAD and were compared. The computationally predicted mean pressure difference across the three implantable VADs was ~ 70mm Hg and the extracorporeal VAD was ~ 345 mmHg, which matched well with their reported pressure-flow curves. The axial VADs had higher mean WSS and SSS compared to the centrifugal VADs. However, the residence time of the centrifugal VADs was much longer compared to the axial VADs because of the large volume of the centrifugal VADs. The highest SSS was observed in one axial VAD and the longest exposure time was observed in one centrifugal VAD. These two VADs generated the highest HI. The shear-induced HI varied as a function of flow rate within each cardiac cycle. At fixed pump speed, the HI was greatest at low flow rate due to longer exposure time to shear stress compared to at high flow rate. Subsequently, we hypothesize that in order to reduce the risk of blood trauma during VAD support, shear stress magnitude and exposure time need to be minimized.
      PubDate: 2017-08-31T17:00:38.953226-05:
      DOI: 10.1002/cnm.2924
       
  • The impact of personalized probabilistic wall thickness models on peak
           wall stress in abdominal aortic aneurysms
    • Authors: J. Biehler; W. A. Wall
      Abstract: If computational models are ever to be used in high stakes decision making in clinical practice, the use of personalized models and predictive simulation techniques is a must. This entails rigorous quantification of uncertainties as well as harnessing available patient-specific data to the greatest extent possible. Although researcher are beginning to realize that taking uncertainty in model input parameters into account is a necessity, the predominantly used probabilistic description for these uncertain parameters are based on elementary random variable models. In this work, we set out for a comparison of different probabilistic models for uncertain input parameters using the example of an uncertain wall thickness in finite element models of abdominal aortic aneurysms. We provide the first comparison between a random variable and a random field model for the aortic wall and investigate the impact on the probability distribution of the computed peak wall stress. Moreover, we show that the uncertainty about the prevailing peak wall stress can be reduced if non-invasively available, patient-specific data is harnessed for the construction of the probabilistic wall thickness model. This article is protected by copyright. All rights reserved.
      PubDate: 2017-08-10T10:49:35.686683-05:
      DOI: 10.1002/cnm.2922
       
  • A Comprehensive Pipeline for Multi-Resolution Modeling of the Mitral
           Valve: Validation, Computational Efficiency, and Predictive Capability
    • Authors: Andrew Drach; Amir H. Khalighi, Michael S. Sacks
      Abstract: Multiple studies have demonstrated that the pathological geometries unique to each patient can affect the durability of mitral valve (MV) repairs. While computational modeling of the MV is a promising approach to improve the surgical outcomes, the complex MV geometry precludes use of simplified models. Moreover, the lack of complete in-vivo geometric information presents significant challenges in the development of patient-specific computational models. There is thus a need to determine the level of detail necessary for predictive MV models. To address this issue, we have developed a novel pipeline for building attribute-rich computational models of MV with varying fidelity directly from the in-vitro imaging data. The approach combines high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high resolution, attribute-rich computational models. Subsequent lower resolution models were then developed, and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then identified the critical levels of fidelity for building predictive MV models in the dilated and repaired states. We demonstrated that a model with a feature size of ~5 mm and mesh size of ~1 mm was sufficient to predict the overall MV shape, stress, and strain distributions with high accuracy. However, we also noted that more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables sufficiently complex models for biomechanical simulations of MV in normal, dilated, repaired states.
      PubDate: 2017-08-03T20:25:28.324152-05:
      DOI: 10.1002/cnm.2921
       
  • Phase Contrast Cell Detection Using Multi-level Classification
    • Authors: Ehab Essa; Xianghua Xie
      Abstract: In this paper, we propose a fully automated learning based approach for detecting cells in time-lapse phase contrast images. The proposed system combines two machine learning approaches to achieve bottom-up image segmentation. We apply pixel-wise classification using random forests (RF) classifiers to determine the potential location of the cells. Each pixel is classified into four categories (cell, mitotic cell, halo effect, and background noise). Various image features are extracted at different scales to train the RF classifier. The resulting probability map is partitioned using the k-means algorithm to form potential cell regions. These regions are expanded into the neighboring areas to recover some missing or broken cell regions. In order to validate the cell regions, another machine learning method based on the bag-of-features and spatial pyramid encoding is proposed. The result of the second classifier can be a validated cell, a merged cell, or a non-cell. In the case that the cell region is classified as a merged cell, it is split by using the seeded watershed method. The proposed method is demonstrated on several phase contrast image datasets, i.e. U2OS, HeLa, and NIH 3T3. In comparison to state-of-the-art cell detection techniques, the proposed method shows improved performance, particularly in dealing with noise interference and drastic shape variations. This article is protected by copyright. All rights reserved.
      PubDate: 2017-07-28T20:00:48.851712-05:
      DOI: 10.1002/cnm.2916
       
  • A Novel Method for Rapid and Quantitative Mechanical Assessment of Soft
           Tissue for Diagnostic Purposes: A Computational Study
    • Authors: Javier Palacio-Torralba; Daniel W. Good, Grant D. Stewart, S. Alan McNeill, Robert L. Reuben, Yuhang Chen
      Abstract: Biological tissues often experience drastic changes in their microstructure due to their pathophysiological conditions. Such microstructural changes could result in variations in mechanical properties, which can be used in diagnosing or monitoring a wide range of diseases, most notably cancer. This paves the avenue for non-invasive diagnosis by instrumented palpation although challenges remain in quantitatively assessing the amount of diseased tissue by means of mechanical characterization. This paper presents a framework for tissue diagnosis using a quantitative and efficient estimation of the fractions of cancerous and non-cancerous tissue without a priori knowledge of tissue microstructure. First, the sample is tested in a creep or stress relaxation experiment and the behavior is characterized using a single term Prony series. A rule of mixtures, which relates tumor fraction to the apparent mechanical properties, is then obtained by minimizing the difference between strain energy of a heterogeneous system and an equivalent homogeneous one. Finally, the percentage of each tissue constituent is predicted by comparing the observed relaxation time with that calculated from the rule of mixtures. The proposed methodology is assessed using models reconstructed from histological samples and magnetic resonance imaging of prostate. Results show that estimation of cancerous tissue fraction can be obtained with a maximum error of 12% when samples of different sizes, geometries and tumor fractions are presented. The proposed framework has the potential to be applied to a wide range of diseases such as rectal polyps, cirrhosis or breast and prostate cancer whose current primary diagnosis remains qualitative.
      PubDate: 2017-07-28T08:30:48.509986-05:
      DOI: 10.1002/cnm.2917
       
  • A New Type of Neurons for Machine Learning
    • Authors: Fenglei Fan; Wenxiang Cong, Ge Wang
      Abstract: In machine learning, the use of an artificial neural network is the mainstream approach. Such a network consists of layers of neurons. These neurons are of the same type characterized by the two features: (1) an inner product of an input vector and a matching weighting vector of trainable parameters and (2) a nonlinear excitation function. Here we investigate the possibility of replacing the inner product with a quadratic function of the input vector, thereby upgrading the 1st order neuron to the 2nd order neuron, empowering individual neurons, and facilitating the optimization of neural networks. Also, numerical examples are provided to illustrate the feasibility and merits of the 2nd order neurons. Finally, further topics are discussed.
      PubDate: 2017-07-27T10:05:23.223874-05:
      DOI: 10.1002/cnm.2920
       
  • Inverse estimation of cardiac activation times via gradient-based
           optimisation
    • Authors: Siri Kallhovd; Mary M. Maleckar, Marie E. Rognes
      Abstract: Computational modeling may provide a quantitative framework for integrating multi-scale data to gain insight into mechanisms of heart disease, identify and test pharmacological and electrical therapy and interventions, and support clinical decisions. Patient-specific computational cardiac models can help guide such procedures, and cardiac inverse modelling is a promising alternative to adequately personalize these models. Indeed, full cardiac inverse modelling is currently becoming computationally feasible; however, fundamental work to assess the feasibility of emerging techniques is still needed. In this study, we use a PDE-constrained optimal control approach to numerically investigate the identifiability of an initial activation sequence from synthetic (partial) observations of the extracellular potential using the bidomain approximation and 2D representations of cardiac tissue. Our results demonstrate that activation times and duration of several stimuli can be recovered even with high levels of noise, that it is sufficient to sample the observations at the ECG-relevant sampling frequency of 1 kHz, and that spatial resolutions that are coarser than the standard in electrophysiological simulations can be used. The optimization of activation times is still effective when synthetic data are generated with a different cell membrane kinetics model than optimized for. The findings thus indicate that the presented approach has potential for finding activation sequences from clinical data modalities, as an extension to existing cardiac imaging approaches. This article is protected by copyright. All rights reserved.
      PubDate: 2017-07-25T21:55:32.161194-05:
      DOI: 10.1002/cnm.2919
       
  • Benchmark problems for numerical treatment of backflow at open boundaries
    • Authors: C. Bertoglio; A. Caiazzo, Y. Bazilevs, M. Braack, M. Esmaily, V. Gravemeier, A. Marsden, O. Pironneau, I. E. Vignon-Clementel, W. A. Wall
      Abstract: In computational fluid dynamics, incoming velocity at open boundaries, or backflow, often yields to unphysical instabilities already for moderate Reynolds numbers. Several treatments to overcome these backflow instabilities have been proposed in the literature. However, these approaches have not yet been compared in detail in terms of accuracy in different physiological regimes, in particular due to the difficulty to generate stable reference solutions apart from analytical forms. In this work, we present a set of benchmark problems in order to compare different methods in different backflow regimes (with a full reversal flow and with propagating vortices after a stenosis). The examples are implemented in FreeFem++ and the source code is openly available, making them a solid basis for future method developments. This article is protected by copyright. All rights reserved.
      PubDate: 2017-07-25T20:55:41.808253-05:
      DOI: 10.1002/cnm.2918
       
  • Integration of element specific persistent homology and machine learning
           for protein-ligand binding affinity prediction
    • Authors: Zixuan Cang; Guo Wei Wei
      Abstract: Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, gene expression, etc. Accurate prediction of protein-ligand binding affinities is vital to rational drug design and the understanding of protein-ligand binding and binding induced function. Existing binding affinity prediction methods are inundated with geometric detail and involve excessively high dimensions, which undermines their predictive power for massive binding data. Topology provides the ultimate level of abstraction and thus incurs too much reduction in geometric information. Persistent homology embeds geometric information into topological invariants and bridges the gap between complex geometry and abstract topology. However, it oversimplifies biological information. This work introduces element specific persistent homology (ESPH) or multicomponent persistent homology to retain crucial biological information during topological simplification. The combination of ESPH and machine learning gives rise to a powerful paradigm for macromolecular analysis. Tests on two large data sets indicate that the proposed topology based machine learning paradigm outperforms other existing methods in protein-ligand binding affinity predictions. ESPH reveals protein-ligand binding mechanism that can not be attained from other conventional techniques. The present approach reveals that protein-ligand hydrophobic interactions are extended to 40Å  away from the binding site, which has a significant ramification to drug and protein design. This article is protected by copyright. All rights reserved.
      PubDate: 2017-07-05T02:55:27.623639-05:
      DOI: 10.1002/cnm.2914
       
  • Performance evaluation of GPU parallelization, space-time adaptive
           
    • Authors: Rafael S. Oliveira; Bernardo M. Rocha, Denise Burgarelli, Wagner Meira Jr, Christakis Constantinides, Rodrigo Weber dos Santos
      Abstract: The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. In order to speed up cardiac simulations and to allow more precise and realistic uses, two different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs), and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, i.e., complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques we obtained speedups that ranged between 165-498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy. This article is protected by copyright. All rights reserved.
      PubDate: 2017-06-21T13:40:56.262362-05:
      DOI: 10.1002/cnm.2913
       
  • Gingival morphology-controlled design of the complete denture baseplate
    • Authors: Ning Dai; Xiaoling Yu, Yuchun Sun
      Abstract: A removable complete denture is still the main selection for edentulous patients. Over the last five years, digital technologies for producing complete dentures have rapidly developed. Nevertheless, the design method for the baseplate has become the bottleneck of digital complete denture technology development. In this study, we report a novel method for the generation of aesthetic gingiva and polished surfaces of complete dentures that are driven by the feature curve, which can be conveniently modified using the gingival shape factor. A solid modeling method based on Poisson's surface reconstruction is used to generate a high-quality baseplate solid. This method can aid dentists to realize the rapid design process of personalized aesthetic baseplace. Finally, the experimental results verify that the method of digital design for the baseplate proposed is efficient and accurate (standard deviation < 0.01 mm).
      PubDate: 2017-06-16T00:15:20.964917-05:
      DOI: 10.1002/cnm.2911
       
 
 
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