- Selected Pics
- Project Aims
- Background
- Videos
- Installation
- Building And Running
- Simulation Setup File
- Simulation Runtime Controls
- Changelog
- License
- Contributing Authors
- Funding Sources
- Acknowledgements
- References
Our project has several key objectives. Firstly, we aim to utilize N-body techniques to develop an interactive model of the left atrium. This model will allow users to manipulate various parameters in real-time, facilitating the induction and observation of common arrhythmias.
Secondly, we seek to create a training and study tool for electrophysiologists, researchers, and medical students. By accurately simulating left atrial arrhythmias and their treatment using simulated ablations, the model will serve as a valuable educational resource, enhancing understanding and skill development in this critical medical field.
Additionally, the project aims to advance research in electrophysiology by providing a platform for exploring novel treatment strategies and studying arrhythmia mechanisms. This could lead to new insights and innovations in the field, ultimately benefiting patients with cardiac arrhythmias.
In summary, the project's objectives include developing a cutting-edge model for arrhythmia simulation, providing an advanced training tool for medical professionals, and advancing research in electrophysiology.
Heart disease and strokes rank among the leading causes of death globally [1,2]. Supraventricular Tachycardia (SVT) significantly contributes to strokes, heart failure, and, in some cases, acute myocardial infarction [3-5]. Therefore, reducing SVT occurrence is crucial in our efforts to promote healthier lives free of cardiovascular diseases and strokes.
SVT encompasses all cardiac arrhythmias originating above the ventricles. This abnormal heartbeat can disrupt the natural synchronization between the atria and ventricles, causing blood to stagnate in the left atrium (LA) and forming potentially lethal blood clots known as mural thrombi [6]. These clots can dislodge and travel to the brain or coronary arteries, leading to a stroke or heart attack, as seen in individuals with atrial fibrillation (AF) who face a five-fold increased stroke risk [7].
Normally, the sinus node acts as the heart's pacemaker, generating an electrical impulse that dictates the heart's rhythm. Ectopic electrical impulses can disrupt this rhythm, causing the atria to flutter or beat out of sync with the ventricles [8].
While SVT can often be controlled with medication and lifestyle changes, some drugs can be challenging to tolerate, and certain effective medications can have hepatotoxic effects [9]. Catheter ablation, though more invasive, has proven to be the most efficacious and safest method for treating recurring SVT [10-13].
Advancements in radiofrequency (RF) catheter ablation and electro-anatomical mapping have enabled doctors to perform procedures on beating hearts that were once thought impossible [14,15]. However, much remains unknown about the causes of heart arrhythmias and how to treat them using RF catheter ablation [16]. A computer model of the LA, such as the one we have developed, can assist doctors, researchers, and medical students in rapidly and inexpensively testing ideas and observing outcomes.
The LA was chosen for modeling due to its role in complex arrhythmias [17-20]. Our model simulates both electrical and mechanical activity, allowing users to adjust parameters at the muscle level and introduce ectopic events. These tools enable users to induce arrhythmias in the LA that can be eliminated through simulated ablations, all in an interactive simulation setting.
Video Micro-Reenter: https://youtu.be/llIGgZSiTnE
Video Macro-Reenter: https://youtu.be/3m_7lrOe2cw
Video Spiral Wave-Reentry: https://youtu.be/c-ID603Vm9Q
Video AFib-Like: https://youtu.be/GG6Q7uG8OhQ
Video Realistic Topology: https://www.youtube.com/watch?v=y_ju9k7Y6So
- This simulation requires a CUDA-enabled GPU from Nvidia. Click here for a list of GPUs.
| *Note: These are guidelines, not rules | CPU | GPU | RAM |
|---|---|---|---|
| Minimum: | AMD/Intel Six-Core Processor | Any CUDA-Enabled GPU | 16GB DDR4 |
| Recommended: | AMD/Intel Eight-Core Processor | RTX 3090/Quadro A6000 | 32GB DDR5 |
Disclosure: This simulation only works on Linux-based distros currently. All development and testing was done in Ubuntu 20.04/22.04
Install Nvidia CUDA Toolkit:
sudo apt update
sudo apt install nvidia-cuda-toolkit
Install Mesa Utils:
sudo apt update
sudo apt install mesa-utils
Install gcc and nvcc:
sudo apt update
sudo apt install build-essential
Install GLFW:
sudo apt update
sudo apt install libglfw3-dev libglu1-mesa-dev freeglut3-dev mesa-common-dev
Install X11-related libraries:
sudo apt update
sudo apt install libxinerama-dev libxcursor-dev libxi-dev
Install gedit:
sudo apt update
sudo apt install gedit
Install ffmpeg:
sudo apt update
sudo apt install ffmpeg
Navigate to the cloned folder and run the following command to build and compile the simulation:
./compile
If it says that you do not have permissions, run the following command and try again.
chmod +x compile
After compiling, run the simulation:
./run
There are three simulation setup files.
These files can be adjusted by the user before running a simulation to set up the basic framework of the run.
All units used in the simulation are as follows:
Length is in millimeters (mm)
Time is in milliseconds (ms)
Mass is in grams (g)
This file is read at startup and tells the program to either resume the simulation from a previous run or create a new run from the
frameworks in the nodes and muscles files. It also reads in some basic visualization parameters.
This file is read at startup and sets base simulation settings, such as beat rate and node and muscle characteristics.
It also reads in several visualization parameters.
This file is read at startup and sets the basic physics of the simulation.
Our model includes a Graphical User Interface (GUI) to allow the user to dynamically adjust various attributes for both the simulation and various characteristics of the left atrium.
Primary controls for managing the simulation execution and visual output.
| Control | Description |
|---|---|
| Contraction Toggle | Enables/disables visual contraction of heart tissue |
| Draw Front Half Only | Renders only the closest half of the model for clarity/performance |
| Show Nodes | Toggle to draw front half/all/no nodes |
| Record Video | Starts/stops recording simulation video |
| Screenshot | Captures still image of current view |
| Simulation Speed | Determines the amount of calculations in between render calls |
Interactive modes for mouse actions on 3D heart surface.
| Mode | Description |
|---|---|
| Mouse Off | Turns all mouse functions off |
| Ablate Mode | Block (ablate) the signal from traveling through selected nodes |
| Ectopic Beat | Sets up a recurrent timed pulse (beat) from the selected node |
| Ectopic Trigger | Initiates a single pulse from the selected node |
| Adjust Area | Select/modify muscle characteristics for a group of muscles |
| Adjust Line | Select/modify muscle characteristics for a single muscle |
| Identify Node | Identify the number that corresponds to a specific node |
Panel for management of cardiac rhythms
| Control | Description |
|---|---|
| Beat Period (ms) | Sets baseline interval between heartbeats |
| Ectopic Beats | View/Adjust current ectopic beats |
Tools for saving/loading simulation states.
| Utility | Description |
|---|---|
| Save Settings | Exports simulation parameters to a file for later use |
| Find Nodes | Finds the ID of the top-most and front-most node |
| Save State | Saves complete simulation state for short-term use |
| Load State | Restores simulation from saved state |
Refer to the changelog for details.
- This code is protected by the MIT License and is free to use for personal and academic use.
- Leah Rogers
- Mason Bane
- Kyla Moore
- Gavin McIntosh
- Avery Campbell
- Melanie Little
- Derek Hopkins
- Brandon Wyatt
- Madhur Wyatt
- Charles Puelz (CoPI)
- Bryant Wyatt (PI)
This research was supported by the NVIDIA cooperation’s Applied Research Accelerator Program. Student support was provided by Tarleton State University’s Presidential Excellence in Research Scholars and the Bill and Winnie Wyatt Foundation.
We would like to thank Tarleton State University’s Mathematics Department for use of their High-Performance Computing lab for the duration of this project.
[1] World Health Organization. (12/9/2020). The top 10 causes of death. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/the top-10-causes-of-death
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