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15 projects in result set.
OpenSim Soccer Ball Kicking Example
- This project is for students and educators interested in how elements of a musculoskeletal model come together to generate simulations of human movement.
The soccer kick is meant to be compelling, challenging, and fun, allowing students to experiment with motor control strategies.
If you have questions, please feel free to contact us at opensim@stanford.edu.
To find out more about the OpenSim project, please visit our website at http://opensim.stanford.edu | |
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Registered: 2011-09-30 20:42 |
Fiber Tractography for Finite-Element Modeling of Transversely Isotropic Tissues
- This project demonstrates the process for fiber tractography of complex biological tissues with transverse isotropy, such as tendon and muscle. This is important for finite element studies of these tissues, as the fiber direction must be specified in the constitutive model. This project contains code, models, and data that can be used to reproduce the results of our publication on this technique. The supplied instructional videos will enable researchers to easily and efficiently apply this method to a variety of other tissues. The software used in the fiber tractography process and demonstrated in this project is Matlab, Autodesk Inventor (free for educators), and Autodesk Simulation CFD (free for educators). Full demonstrations and process instructions can be found in the 7 videos posted at https://vimeo.com/album/3414604:
Contents:
Chapter 1: Introduction (2:35)
This video introduces the CFD fiber tractography software pipeline
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Chapter 2: Supplementary materials code, models and data (20:21)
This video shows the shared models, code, and data posted online at simtk.org/m3lab_cfd4fea.
Chapter 3: Finite element simulations (5:38)
This video shows finite element simulations using the fiber mapping process.
Chapter 4: Iliacus example walkthrough (21:38)
This video shows the step-by-step process for fiber mapping the iliacus muscle (a hip flexor).
Chapter 5: Bflh example walkthrough (12:09)
This video shows the step-by-step process for fiber mapping the biceps femoris longhead muscle (a hamstring).
Chapter 6: Autodesk Inventor segmentation (9:09)
This video shows how to do segmentation of medical images in Autodesk Inventor in order to simplify the solid model for the CFD and FEA software.
Chapter 7: Curved inlet surfaces (6:28)
This video shows how to create curved inlet surfaces for use in Autodesk Simulation CFD. | |
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Activity Percentile: 57.32 Registered: 2015-05-28 18:52 |
Effect of Algisyl Injection on Porcine Heart Failure Models
- Heart failure (HF) is a worldwide epidemic that contributes considerably to the overall cost of health care in developed nations. The number of people afflicted with this complex disease is increasing at an alarming pace—a trend that is likely to continue for many years to come. Over 1 million Americans suffer a myocardial infarction (MI) each year and many experience post-MI left ventricular (LV) remodeling, which manifests as progressive changes in LV structure and function. Post-MI LV remodeling is responsible for nearly 70% of all HF cases. Reduction of LV wall stress is considered a cornerstone in the treatment of HF. There are currently no reliable means to directly measure wall stresses in the intact LV. Thus, we rely on FE models, using LS-DYNA, to predict these stresses, knowing that the predictions cannot be validated directly, albeit we can validate deformations. To make our work more accessible to other researchers we are willing to help convert our models to freely available FE software like Continuity (http://www.continuity.ucsd.edu/) and FEBio (https://febio.org/).
A novel promising therapy for HF using intramyocardial injections of alginate to de-stress the heart based on a “micro-LVAD” (LV assist device) mechanism of action was designed computationally, validated pre-clinically, and then validated clinically in the AUGMENT-HF international prospective multi-center trial. The overall goal of our proposed research is to optimize a therapy for HF that involves percutaneous injection of an alginate hydrogel (Algisyl) in the failing myocardium.
We developed a novel percutaneous large animal (swine) model of ischemic HF. By preconditioning coronary arteries using balloon inflation prior to placing embolism coils two weeks apart, we reduced swine mortality to 10% and generated a realistic model of ischemic cardiomyopathy in large coronary arteries similar to those in patients. Treatment of HF with Algisyl, even without coronary artery bypass grafting (CABG), resulted in sustained improvement of LV contractile function with reduced LV volume. Our method for automatically optimizing intramyocardial injections for treating HF strongly suggests LV contractile function will be further improved if stiffer implants are placed in chronically infarcted LV regions. Additionally, our method for simulating the progression of HF8 strongly suggests that delivering Algisyl in the borderzone of acutely infarcted LV regions can prevent HF progression.
Our studies support the exciting concept that the injection of inert material into the LV free-wall (with or without CABG) is an effective strategy for inducing LV reverse remodeling that improves LV function and results in decreased myofiber stress. Moreover, if this therapy can be delivered percutaneously rather than via the currently used open-heart procedure, this therapy may become revolutionary for HF treatment. A minimally invasive procedure would be in the best interest of this patient population (i.e., one that cannot tolerate general anesthesia and surgery) and it would be significantly more cost effective than surgery.
We have developed a novel suction-based catheter device that accurately and precisely delivers the material into the LV subendocardium and prevents any potential embolization of the Algisyl in the ventricle. Our catheter device latches onto the endocardium using a suction cup to ensure injections at the needed sites. This innovation makes it possible to inject material endocardially into the heart wall percutaneously (including the interventricular septum) through a femoral artery access. Furthermore, this approach allows us to test a pre-emptive or preventative strategy for treating acute MI so that ischemic HF does not develop.
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Registered: 2016-10-25 06:12 |
Infarcted human left ventricular myofiber stress
- Heart failure is increasing at an alarming rate, making it a worldwide epidemic. As the population ages and life expectancy increases, this trend is not likely to change. Myocardial infarction (MI)-induced adverse left ventricular (LV) remodeling is responsible for nearly 70% of heart failure cases. The adverse remodeling process involves an extension of the border zone (BZ) adjacent to an MI, which is normally perfused but shows myofiber contractile dysfunction. To improve patient-specific modeling of cardiac mechanics, we sought to create a finite element model of the human LV with BZ and MI morphologies integrated directly from delayed-enhancement magnetic resonance (DE-MR) images. Instead of separating the LV into discrete regions (e.g., the MI, BZ, and remote regions) with each having a homogeneous myocardial material property, we assumed a functional relation between the DE-MR image pixel intensity and myocardial stiffness and contractility--we considered a linear variation of material properties as a function of DE-MR image pixel intensity, which is known to improve the accuracy of the model''''s response. The finite element model was then calibrated using measurements obtained from the same patient--namely, 3D strain measurements-using complementary spatial modulation of magnetization magnetic resonance (CSPAMM-MR) images. This led to an average circumferential strain error of 8.9% across all American Heart Association (AHA) segments. We demonstrate the utility of our method for quantifying smooth regional variations in myocardial contractility using cardiac DE-MR and CSPAMM-MR images acquired from a 78-yr-old woman who experienced an MI approximately 1 yr prior. We found a remote myocardial diastolic stiffness of C(0) = 0.102 kPa, and a remote myocardial contractility of T(max) = 146.9 kPa, which are both in the range of previously published normal human values. Moreover, we found a normalized pixel intensity range of 30% for the BZ, which is consistent with the literature. Based on these regional myocardial material properties, we used our finite element model to compute patient-specific diastolic and systolic LV myofiber stress distributions, which cannot be measured directly. One of the main driving forces for adverse LV remodeling is assumed to be an abnormally high level of ventricular wall stress, and many existing and new treatments for heart failure fundamentally attempt to normalize LV wall stress. Thus, our noninvasive method for estimating smooth regional variations in myocardial contractility should be valuable for optimizing new surgical or medical strategies to limit the chronic evolution from infarction to heart failure. | |
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Activity Percentile: 0.00 Registered: 2015-04-16 18:15 |
Normal human left ventricular myofiber stress
- Ventricular wall stress is believed to be responsible for many physical mechanisms taking place in the human heart, including ventricular remodeling, which is frequently associated with heart failure. Therefore, normalization of ventricular wall stress is the cornerstone of many existing and new treatments for heart failure. In this paper, we sought to construct reference maps of normal ventricular wall stress in humans that could be used as a target for in silico optimization studies of existing and potential new treatments for heart failure. To do so, we constructed personalized computational models of the left ventricles of five normal human subjects using magnetic resonance images and the finite element method. These models were calibrated using left ventricular volume data extracted from magnetic resonance imaging (MRI) and validated through comparison with strain measurements from tagged MRI (950 ± 170 strain comparisons/subject). The calibrated passive material parameter values were C0 = 0.115 ± 0.008 kPa and B0 = 14.4 ± 3.18; the active material parameter value was Tmax = 143 ± 11.1 kPa. These values could serve as a reference for future construction of normal human left ventricular computational models. The differences between the predicted and the measured circumferential and longitudinal strains in each subject were 3.4% ± 6.3% and 0.5% ± 5.9%, respectively. The predicted end-diastolic and end-systolic myofiber stress fields for the five subjects were 2.21 ± 0.58 kPa and 16.54 ± 4.73 kPa, respectively. Thus, these stresses could serve as targets for in silico design of heart failure treatments. | |
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Registered: 2014-06-04 18:58 |
Simulation of Coronary Artery Bypass Graft and Surgical Ventricular Restoration
- This project is a virtual surgery tool for enabling clinicians to easily simulate the effects of coronary artery bypass graft (CABG) and surgical ventricular restoration (SVR) on patients with ischemic heart failure. | |
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Activity Percentile: 0.00 Registered: 2009-03-19 19:19 |
Collagen remodeling in tendon injury
- This model demonstrates the effect of different treatment regimens on a supraspinatus tendon injury. A complete tear is made in the tendon and fibroblasts migrate to the wound to deposit collagen and remodel the scar that is formed. The red agents are collagen fibers with an assigned heading. The blue triangles are fibroblasts that migrate throughout the wound and deposit and degrade collagen. The green color represents chemokine that is produced from the wound space and diffuse outward. | |
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Registered: 2017-12-01 16:46 |
Agent based model of Norovirus transmission on a cruise ship
- We've created an agent based model of the transmission of Norovirus on a cruise ship. This agent based model was defined in Netlogo. A cruise ship environment was created with several different compartments - cabin, dining/common area, and pool deck. Agents were divided into workers and passengers, who had different daily schedules of commuting through the common areas. Infection spread was modeled by a probability of spreading the virus to another agent upon contact, represented in Netlogo as sharing the same patch as an infected agent. Illness was modeled with an incubation period following initial infection, an infectious period where agents can spread the virus, and a symptomatic period where agents confine themselves to their cabin. Total infected agents over the duration of the cruise can be monitored. | |
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Registered: 2017-12-07 17:18 |
Innate immune response to bacterial infection in a superficial, acute wound
- We've created an agent based model in which cells of the innate (non-specific) immune system respond to a bacterial infection in a shallow, acute skin wound. The user can change rates in the model to compare the time for all the bacteria to be removed (bacterial clearance) in a healthy patient compared to a diabetic patient. Diabetic patients are at an increased risk of long-lasting bacterial infections because they have increased glucose sugar levels in their bloodstream and their immune cells are less effective at fighting infection.
Glucose is replenished from the blood stream at a constant rate. If bacteria have accumulated enough energy, they reproduce. Else the bacteria move towards the highest concentration of glucose, and consume it to gain more energy. A bacteria leaves a trail of chemical as it moves. A neutrophil, the first responder to an infection, then appears at the scene, recruiting other neutrophils to join in the fight. The neutrophils follow the chemical trail from the bacteria. Neutrophils leave a trail of immune chemicals which kill bacteria and gobble the bacteria up by phagocytosis if they get close enough. Later, macrophages appear at the scene which also release immune chemicals and gobble up bacteria. The macrophages are more effective at killing bacteria than neutrophils, but are slower to respond to the infection. Over time, the build-up of chemicals from the bacteria and immune cells damages the tissue. | |
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Registered: 2017-12-09 02:21 |
The Reference Model for Disease Progression
- The Reference Model is now:
• <a href="http://dx.doi.org/10.7759/cureus.9455" target="_blank"> COVID-19 model for US states and territories </a>
• <a href="https://jacob-barhak.github.io/InteractivePoster_MSM_IMAG_2019.html" target="_blank"> The Most Validated Cardiovascular (CVD) Diabetes Model known </a>
• <a href="https://patents.google.com/patent/US20140297241A1/en" target="_blank"> United States Patent 9,858,390</a>
• <a href="https://patents.google.com/patent/US20170286627A1/en" target="_blank"> United States Patent Number 10,923,234</a>
The Reference Model can now:
• Attempt to explain COVID-19 for US states
• Determine CVD models that significantly behave better on several diabetic populations
• Deduce that CVD probability halves every 5 years due to medicine improving - according to information from the last 3 decades
• Calculate life tables for diabetics
• Interface with ClinicalTrials.Gov
• Include human interpretation in the model
• Create an interactive map of our <a href="https://jacob-barhak.github.io/InteractivePoster_MSM_IMAG_2019.html" target="_blank"> <b> cumulative computational knowledge gap</b>
<a href="http://dx.doi.org/10.7759/cureus.9455" target="_blank"> <b> COVID-19 MODEL</b> </a>
The interactive plot below shows our cumulative knowledge gap by showing the error in the vertical axis for US states and territories listed on the horizontal axis. Circles at the bottom have a better fit between observed COVID-19 results and model results. Results are for normalized population of size 10,000 individuals. Hover over the circles to see additional details about each state. The slider determines the model optimization iteration. User can explore the map by changing size and color attributes.
<iframe width="1000" height="400" src="https://jacob-barhak.netlify.app/thereferencemodel/results_covid19_2020_06_27/populationplot" frameborder="0" > </iframe>
<a href="https://simtk.org/projects/mist" target="_blank"> <b> TECHNOLOGY </b> </a>
The Reference Model is a good way to cross reference information to find out pieces of information and assumptions that fit together, and allow competition against accumulated known data to guide our perception. High Performance Computing is a key to those capabilities and it provided using capabilities of the <a href="https://simtk.org/projects/mist" target="_blank"> MIcro Simulation Tool (MIST) </a> .
MIST also provides advance population generation techniques using Evolutionary computation. The Reference Model uses publicly available data such as clinical trial publications. This allows it to access more information since it allows accessing data that otherwise will be restricted from sharing. The Reference Model has an interface that allows it to read information from <a href="https://clinicaltrials.gov/" target="_blank" > ClinicalTrials.Gov</a> while maintaining tractability and reproducibility.
<b> <a href="https://simtk.org/plugins/simtk_news/index.php?group_id=1286" target="_blank"> PUBLICATIONS: </a> </b>
The Reference Model was created in 2012 and evolved since then. You can find key developments and publications by year in the <a href="https://simtk.org/plugins/simtk_news/index.php?group_id=1286" target="_blank"> news section </a>.
Here are some videos describing the Model:
This video gives a brief introduction
<iframe width="800" height="450" src="https://www.youtube.com/embed/s9L-qFF84Ew" title="The Reference Model for Disease Progression: Explaining COVID-19" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
This video will shows recent results of explaining COVID-19 using USA data:
<iframe width="800" height="450" src="https://www.youtube.com/embed/1M645o5gWrc" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
This video will show a breakthrough of becoming the first multiscale ensemble model for COVID-19:
<iframe width="800" height="450" src="https://www.youtube.com/embed/-z8N40TdKDk?start=1860" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
This video explains the model in a larger context as presented in AnacondaCon 2019:
<iframe width="800" height="450" src="https://www.youtube.com/embed/fQIYMf5wKGE" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
This video explains how human interpretation can be used as presented in the Multiscale Viral Pandemics working group webinar:
<iframe width="800" height="450" src="https://www.youtube.com/embed/aTB8-XEZheU" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
This video summarizes a decade of work as presented in PyTexas 2017:
<iframe width="800" height="450" src="https://www.youtube.com/embed/Pj_N4izLmsI?list=PL0MRiRrXAvRiwQUUwTTh5g8rhbQyYlubo" frameborder="0" gesture="media" allow="encrypted-media" allowfullscreen></iframe>
This describes the evolution of the model up to 2016 presented in PyTexas:
<iframe width="800" height="450" src="https://www.youtube.com/embed/htGRRjia-QQ" frameborder="0" allowfullscreen></iframe>
This describes the work presented in PyData in 2014:
<iframe width="800" height="450" src="https://www.youtube.com/embed/vyvxiljc5vA" frameborder="0" allowfullscreen></iframe> | |
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Registered: 2017-05-09 05:34 |
Population Modeling Workgroup
- This is the web portal of the Population Modeling Working Group associated with the Interagency Modeling and Analysis Group (IMAG).
For additional information see:
http://www.imagwiki.nibib.nih.gov/content/population-modeling-working-group
Visit our discussions at: https://simtk.org/pipermail/popmodwkgrpimag-news/
The working group produced several review papers mapping the field:
1) Population Modeling Working Group, Population Modeling by Examples (WIP) - SpringSim 2015 , April 12 - 15, Alexandria, VA, USA . Paper available <a href="http://dl.acm.org/citation.cfm?id=2887741"> Here </a> and <a href="https://simtk.org/docman/view.php/962/1892/PopModExample_Submit_2015_03_04.doc"> Here </a> Presentation available <a href="https://simtk.org/docman/view.php/962/1897/SpringSim2015PopMod_Upload_2015_04_10.pptx"> Here </a>
2) Population Modeling Working Group, Population Modeling by Examples II - SummerSim 2016 , July 24 - 27, Montreal, CA. Paper available <a href="https://simtk.org/docman/view.php/962/1963/SummerSim_2016_PopMod_Submit_2016_05_15_Robert_Smith.pdf"> Here </a> and <a href="https://doi.org/10.22360/SummerSim.2016.SCSC.060"> Here </a> Presentation available <a href="https://simtk.org/docman/view.php/962/1988/PopulationModellingByExamplesII_SummerSim_2016.pdf"> Here </a>
3) Population Modeling Working Group, Population Modeling by Examples III - SummerSim 2017 , July 9 - 12, Bellevue, WA, USA. Paper available <a href="https://doi.org/10.22360/SummerSim.2017.SCSC.013"> Here </a> and <a href="https://simtk.org/docman/view.php/962/4654/PopulationModelingByExamples3_Submit_2017_06_04.docx"> Here </a> Presentation is available <a href="https://simtk.org/docman/view.php/962/4657/SummerSim2017PopMod3_Upload_2017_07_09.pptx"> Here </a>
To view the map of population modeling and its classifications, please follow this <a href="https://docs.google.com/spreadsheets/d/1Ljl6l7hyYbb7wmyoFcrJl38593ufqt65agwHT_EIFEo/edit?usp=sharing"> link</a>:
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Registered: 2014-09-17 17:30 |
Simple Immune System Response Agent Based Model
- This is a simple Agent Based Model of the immune response to a hypothetical wound. The model accompanies a Science News for Students article as a supplement to allow readers the opportunity to directly experiment with biological simulation. Adjust the strength of the immune response, the number of bacteria in the wound, the bacterial colony growth rate, and other parameters to view the time course of healing. | |
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Activity Percentile: 0.00 Registered: 2015-07-29 00:16 |
Agent-Based Model of Skeletal Muscle Injury, Inflammation, and Regeneration
- This model simulates the sterile inflammation process that follows a muscle injury (contusion, laceration, etc). The simulation tracks key inflammatory cells (neutrophils and macrophages), as well as their secretions and interactions with native muscle cells (muscle fibers, satellite cells, fibroblasts). | |
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Activity Percentile: 0.00 Registered: 2015-06-25 19:33 |
Agent-based model of skeletal muscle disuse-induced atrophy
- This project is a tissue level prediction of muscle atrophy. The model aims to incorporate cellular interactions to establish the extent of muscle atrophy observed during disuse. Current predictions are focused on muscle fiber CSA, but methods are being developed to analyze ECM content and turnover as well | |
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Activity Percentile: 0.00 Registered: 2015-01-19 17:07 |
Agent-Based Model of Myocardial Scar Formation (Rouillard et al. 2012)
- Our group developed an agent-based model of myocardial scar healing, implemented in MATLAB. The model tracks migration, proliferation, and collagen remodeling by fibroblasts over 6 weeks of simulated infarct healing, incorporating the influence of regional strains, chemokine gradients, and local matrix orientation on the orientation of the fibroblasts and the collagen fibers they produce. The original model was published in the Journal of Physiology in 2012, and has been used with various minor modifications in several other papers and abstracts from our group since that time. If you use or adapt the model, please cite the original Journal of Physiology article: Rouillard AD, Holmes JW. Mechanical regulation of fibroblast migration and collagen remodeling in healing myocardial infarcts, J Physiol, 590(18):4585-4602, Sep 2012 (http://www.ncbi.nlm.nih.gov/pubmed/22495588). | |
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Registered: 2017-11-27 20:00 |