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In Silico Local Electrical Impedance Measurements in the Atria
<div>This document describes a dataset provided in the context of the manuscript “In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human” [1].</div> <div> </div> <div>Authors: Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dössel O, Luik A</div> <div> </div> <div>The dataset contains in silico simulation setups and results from forward electrical impedance simulations with EIDORS. Geometrical models include the commercially available ablation catheters IntellaNav MiFi and IntellaNav StPt catheter measuring local impedance (LI). </div> <div>Catheter geometries were embedded in different surrounding conditions of clinical importance. Catheter tissue interaction with and without scar, the insertion of the catheter into a pulmonary vein (PV), the withdrawal into a transeptal sheath, and catheter irrigation were modeled to quantify the respective effect on LI measurements. In vitro and clinical data used for validation purposes are included in the dataset as well.</div> <div> </div> <div>Abbreviations: </div> <div>LI: local impedance, all numbers are given in Ohms</div> <div>MiFi: IntellaNav MiFi catheter</div> <div>PV: pulmonary vein</div> <div>StPt: IntellaNav StPt catheter</div> <div> </div> <div> </div> <div>Simulation results, in vitro measurements and clinically measured traces are provided in the following MATLAB files in the subdirectory „results_LI“:</div> <div> </div> <div>• impConductivities.mat</div> <div>In vitro measurements and simulation results for MiFi and StPt in NaCl solutions of different concentrations as described in section III A of the related publication [1]. The struct "impedance" includes the following fields:</div> <div>⁃ conc: concentration of NaCl solutions from in vitro measurements in weight percentages</div> <div>⁃ cond: conductivities of the NaCl solutions from in vitro measurements in S/m</div> <div>⁃ temp: interpolated temperature curves from in vitro measurements in °C</div> <div>⁃ condSim: different conductivities of the NaCl solutions from in silicon experiments in S/m</div> <div>⁃ LI_MiFi_iV: 41x9 matrix with interpolated in vitro LI measurements with the MiFi catheter in 9 different NaCl solutions and at 41 interpolated temperature values</div> <div>⁃ LI_StPt_iV: 41x9 matrix with interpolated in vitro LI measurements with the StPt catheter in 9 different NaCl solutions and at 41 interpolated temperatures values</div> <div>⁃ LI_MiFi_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_MiFi_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_StPt_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_StPt_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different NaCl solutions</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different NaCl solutions</div> <div> </div> <div>• impSheath.mat</div> <div>Simulation results and clinical measurements of LI with MiFi and StPt for different overlaps with a transeptal sheath as described in section III B of the related publication [1]. The struct „impSheath“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and distal edge of the sheath in mm. Negative distances describe an insertion of the catheter into the sheath</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_MiFi_cd: 281x2 matrix containing clinical LI measurements with the MiFi catheter in the second column and corresponding time steps in the first column</div> <div>⁃ LI_StPt_cd: 301x2 matrix containing clinical LI measurements with the StPt catheter in the second column and corresponding time steps in the first column</div> <div> </div> <div>• impTissue.mat</div> <div>Simulation results for MiFi and StPt with variable distance and angle between catheter and tissue as described in section III C of the related publication [1]. The struct „impTissue“ contains the following fields:</div> <div>⁃ distance: 25 different distances between catheter tip and endocardial surface in mm</div> <div>⁃ distanceSel: 5 selected distances between catheter tip and endocardial surface in mm</div> <div>⁃ angle: 13 different angles between catheter and endocardial tissue surface in degrees</div> <div>⁃ LI_MiFi_d_alpha: 5x13 matrix with simulated LI values for the MiFi catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_MiFi_d_90: 25 simulated LI values for the MiFi catheter for different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div>⁃ LI_StPt_d_alpha: 5x13 matrix with simulated LI values for the StPt catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_StPt_d_90: 25 simulated LI values for the StPt catheter different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div> </div> <div>• impTissueScar.mat</div> <div>Simulation results for MiFi and StPt interacting with tissue in the presence of scar as described in section III C of the related publication [1]. The struct „impTissueScar“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and endocardial surface for all simulation setups in mm</div> <div>⁃ centerX: horizontal distance between the catheter tip and the center of the line of scar for all simulation setups in mm</div> <div>⁃ LI_MiFi3mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_StPt3mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_MiFi6mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div>⁃ LI_StPt6mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div> </div> <div>• impPV.mat</div> <div>Simulation results for MiFi and StPt insertion into a pulmonary vein (PV) as described in section III D of the related publication [1]. The struct „impPV“ includes the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and tissue surface in mm. Negative distances describe an insertion of the catheter into the vein.</div> <div>⁃ radius: inner radius of the PV in mm</div> <div>⁃ thickness: thickness of the PV tissue in mm</div> <div>⁃ LI_MiFi_d_r_th: 31x4x4 matrix containing the LI simulation results for the MiFi catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div>⁃ LI_StPt_d_r_th: 31x4x4 matrix containing the LI simulation results for the StPt catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div> </div> <div>• impFlush.mat</div> <div>Simulation results for MiFi and StPt flush with NaCl at different flow rates as described in section III E of the related publication [1]. The struct „impFlush“ includes the following fields:</div> <div>⁃ radius: radius of the NaCl spheres at the irrigation holes in mm</div> <div>⁃ LI_MiFi_NaCl: LI extracted from simulations with MiFi catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div>⁃ LI_StPt_NaCl: LI extracted from simulations with StPt catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div> </div> <div>Additionally, exemplary geometrical setups and results are provided as VTK files in the subdirectory „selectedGeometriesAndSimResults“:</div> <div> </div> <div>Each VTK file contains the following data fields:</div> <div>⁃ Ids (point data): integer specifying the Id of the respective vertex</div> <div>⁃ Voltage (point data): electric potential of the respective vertex with respect to a reference potential in mV</div> <div>⁃ Conductivity (cell data): conductivity of the material of the respective cell in S/mm</div> <div>⁃ Current (cell data): current density of the respective cell in nA/mm^2</div> <div>⁃ Ids (cell data): integer specifying the Id of the respective cell</div> <div>⁃ Material (cell data): integer specifying the material of the respective cell (for MiFi setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: mini electrode 1, 8: insulator mini electrode 1, 9: mini electrode 2, 10: insulator mini electrode 2, 11: mini electrode 3, 12: insulator mini electrode 3, 13: tissue, 14: blood, 15: sheath, 16:NaCl, 17: scar tissue; for StPt setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: tissue, 8: blood, 9: NaCl, 10: scar tissue)</div> <div> </div> <div>• mifi.vtk: MiFi catheter in blood </div> <div>• stpt.vtk: StPt catheter in blood</div> <div>• mifiTissue_dist000_angle0000.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 0°</div> <div>• mifiTissue_dist000_angle0450.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 45°</div> <div>• mifiTissue_dist000_angle0900.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 90°</div> <div>• mifiTissue_dist000_angle1350.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 135°</div> <div>• mifiTissue_dist000_angle1800.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 180°</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line3mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 3mm width</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line6mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 6mm width</div> <div>• mifi_PV_d0060_r030_th20.vtk: MiFi catheter 6mm above the endocardial surface with a PV of 3 mm radius and 2mm PV tissue thickness</div> <div>• mifi_PV_d-070_r030_th20.vtk: MiFi catheter inserted into a PV of 3 mm radius and 2mm PV tissue thickness; insertion depth = 7mm</div> <div>• mifi_flush_050-0.50.vtk: MiFi catheter within blood with NaCl spheres of 0.5mm radius at irrigation holes</div> <div>• mifi_sheath_0100.vtk: MiFi catheter within transeptal sheath extracted by 10mm</div> <div> </div> <div>[1] Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dossel O, Luik A. In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human. IEEE Trans Biomed Eng. 2023 Feb;70(2):533-543. doi: 10.1109/TBME.2022.3196545. Epub 2023 Jan 19. PMID: 35925848.</div> <p> </p>
A Bi-atrial Statistical Shape Model and 100 Volumetric Anatomical Models of the Atria
<p>This dataset is part of the publication "A bi-atrial statistical shape model for large-scale in silico studies of human atria: Model development and application to ECG simulations" by Nagel et al. (<a href="https://doi.org/10.1016/j.media.2021.102210">https://doi.org/10.1016/j.media.2021.102210</a>). It includes a bi-atrial statistical shape model built based on 47 MR and CT images (Left atrium segmentation challenge (Tobon-Gomez, 2015), Left atrium fibrosis and scar segmentation challenge (Karim, 2013), Left atrial wall thickness challenge (Karim, 2018)). ScalismoLab (https://scalismo.org) was used for parts of the model generation. Further Details are explained in the paper. The SSM is available as an h5 file including information about the mean shape's vertex locations and their triangulation as well as the eigenvectors and -values. </p> <p>100 random instances derived from the model are available. Each zip file contains the volumetric bi-atrial geometry as vtk file, which was augmented in a post-processing step with a homogeneous wall thickness, fiber orientation, intra-atrial bridges and material tags so that they are ready to use for electrophysiological simulations of atrial signals. Furthermore, the scalar field resulting from computing the gradient of the Laplace equation with the boundary conditions described by Piersanti et al. (Modeling cardiac muscle fibers in ventricular and atrial electrophysiology simulations, Computer Methods in Applied Mechanics and Engineering, 2020, <a href="https://doi.org/10.1016/j.cma.2020.113468">https://doi.org/10.1016/j.cma.2020.113468</a>) are available on the left and the right atrial instances. </p> <p>Furthermore, 95 geometries with uniformly distributed left atrial volumes are available in LAE_geometries.zip. </p>
The Right Atrium Affects In Silico Arrhythmia Vulnerability in Both Atria
<h1>The Right Atrium Affects In Silico Arrhythmia Vulnerability in Both Atria</h1> <div> </div> <div><strong>Authors:</strong> Patricia Martínez Díaz, Jorge Sánchez, Nikola Fitzen, Ursula Ravens, Olaf Dössel, Axel Loewe</div> <div>patricia.martinez@kit.edu / publications@ibt.kit.edu</div> <div><a href="https://doi.org/10.1016/j.hrthm.2024.01.047">doi:10.1016/j.hrthm.2024.01.047</a></div> <div> </div> <div>This dataset contains 8 biatrial meshes and 8 monoatrial (left-only) meshes, derived from MRI and CT segmentations with annotations and fibers, ready for simulations in the cardiac electrophysiology simulator <a href="https://doi.org/10.1016/j.cmpb.2021.106223">openCARP</a>. We also provide the code to reproduce a total of 576 reentries by reading the selected parameters.par and state.roe files. The meshes were generated using <a href="https://github.com/KIT-IBT/AugmentA">AugmentA code</a> and the simulated reentries were induced following the <a href="https://doi.org/10.3389/fphys.2021.656411">PEERP protocol</a> by Azzolin et al. A carputils bundle containing the <a href="https://doi.org/10.35097/1830">openCARP experiment</a>, along with all associated parameters, is publicly available. The original cardiac segmentations are part of Krueger M. et al. Personalization of atrial anatomy and electrophysiology as a basis for clinical modeling of radio-frequency ablation of atrial fibrillation <a href="https://doi.org/10.1109/tmi.2012.2201948">doi:10.1109/TMI.2012.2201948</a></div> <div> </div> <h2>Folder structure</h2> <div>The code is located in the `src` folder, the meshes in the `data` folder and the reentries in the `results` folder. </div> <div>```</div> <div>KIT_2/</div> <div>|-- src/</div> <div> |-- run.py</div> <div> |-- induceReentry.py</div> <div> |-- getStimPoints.py</div> <div> |-- element_tag.csv</div> <div> |-- al_mk_H.par</div> <div> |-- requirements.txt</div> <div> |-- reproduceReentry.py</div> <div>|-- data/</div> <div> |-- meshes/</div> <div> |-- P1/ </div> <div> |-- monoatrial/ </div> <div> |-- biatrial/</div> <div>.</div> <div>.</div> <div>.</div> <div> |-- P8 </div> <div> |-- monoatrial/ </div> <div> |-- biatrial/</div> <div>|-- results/</div> <div>|-- MESH_SCENARIO_STATE_CHAMBER/ (e.g P1_bi_M_LA) </div> <div>|-- point_X_beat_Y</div> <div>| </div> <div>|-- README.md</div> <div>```</div> <div> </div> <div>`src`: contains the source files needed to run PEERP protocol </div> <div> <ul> <li>`run.py` This is the main function to run the pacing protocol (not needed to run if reentries are only reproduced, check reproduceReentry.py)</li> <li>`induceReentry.py` Contains a list of pacing protocols. The PEERP protocol is included here</li> <li>`getStimPoints.py` Extract the stimulation points</li> <li>`element_tag.csv` Region tag numbering</li> <li>`al_mk_H.par` Par file with ionic scaling factors for three states; H:Healthy, M:Mild, S:Severe</li> <li>`requirements.txt` Packages to create the virtual enviroment. (This was my output of ```pip3 list> requirements.txt```)</li> <li>`reproduceReentry.py` Reentries can be reproduced given a selected folder where the .par and .roe files are stored.</li> </ul> </div> <div> </div> <div>`data`: contains the `meshes` folder with the bilayer meshes in openCARP (.elem, .lon and .pts) and .vtk format. Synthetic fibrotic distributions are included in the the .regele files.</div> <div> <ul> <li>`meshes/P1/monoatrial/LA_stim_points.txt` stimulation points for the PEERP protocol</li> <li>`meshes/P1/monoatrial/LA_bilayer_with_fiber_elems_not_conductive_M.regele` Element ids corresponding to synthetic fibrotic distribution with respect to remodeling states M and S. H state was modelled without fibrosis</li> </ul> </div> <div> </div> <h2>Reproduce the reentries </h2> <div>You can generate the .igb file of a specific reentry by selecting the corresponding folder in the results directory. An example is given to reproduce the reentry in P1_bi_M_LA/point_0_beat_2/reproduce_reentry.igb. Select the folder `--par_file_directory`and set `--tend` to define the duration of the simulation in miliseconds.</div> <div>_HINT: We recommend keeping the folder structure so that the other parameters, such as: mesh, scenario, state and chamber, can be read from the --par_file_directory. Otherwise, the meshes and results directories need to be modified._</div> <div>```</div> <div>cd src/</div> <div>reproduceReentry.py --par_file_directory ../results/P1_bi_M_LA/point_0_beat_2 --tend 1500</div> <div> </div> <div>```</div> <div></div> <div> </div> <div> </div> <h2>Preparation before running the PEERP pacing protocol</h2> <div> </div> <div>Follow the next steps if you want to run the PEERP pacing protocol, either for the provided meshes or for your own meshes. To run the PEERP protocol in a controlled environment, it is recommended, before running the run.py, to create a virtual environment. Go to your terminal and type: </div> <div>```</div> <div>cd src/</div> <div>python3 -m venv ./myEnv</div> <div>source ./myEnv/bin/activate</div> <div>pip3 install -r requirements.txt</div> <div>```</div> <div> </div> <div>You need to add carputils to your `PATH`. You can run the code in the terminal or use and IDE to debug the code. </div> <div>Note: I am using PyCharm 2020.3. and in Settings --> Python interpreter --> show all and then in the (+) symbol, add the path to carputils there:</div> <div> </div> <div>Otherwise you can add this extra lines at the beginning of `run.py``:</div> <div>```</div> <p># Replace '/path/to/carputils' with the actual path to your carputils package</p> <p>carputils_path = '/path/to/carputils'</p> <p># Add the carputils path to sys.path</p> <div>sys.path.append(carputils_path)</div> <div>```</div> <h2>Run the PEERP protocol</h2> <div> </div> <div>The following example runs the PEERP from a single stimulation point. If you want to run PEERP over all the points, simply add the flag --run_all_points 1 </div> <div>```</div> <div>cd src/</div> <div>python3 run.py --giL 0.4166 --geL 1.458 --cv 0.8 --mesh monoatrial --protocol PEERP --pacing 122718 --stim_file LA_stim_points.txt --geometry LA_bilayer_with_fiber_um --cell_bcl 500 --model Courtemanche --ionic_prop_file al_mk_S.par --max_n_beats_PEERP 1 --overwrite-behaviour overwrite</div> <div>```</div> <div> </div> <h2>Running your own experiment and making your own changes</h2> <div>Extract the stimulation points on your mesh, where the PEERP protocol will be run: </div> <div>```</div> <div>python3 getStimPoints.py --mesh monoatrial --tolerance 20000 --stim_file LA_stim_points.txt --chamber LA</div> <div>```</div> <div> </div> <div>Tune conduction velocity (CV) and conductivites. The code expects the intracellular end extracellular longitudinal conductivity values as an input. We used `tuneCV` to fit CV=0.7m/s with dx=0.4mm and dt=20us</div> <div>If you want to adjust the values, run in the terminal:</div> <div>```</div> <div>tuneCV --resolution 400 --model Courtemanche --velocity 0.7 --converge True --sourceModel monodomain --surf True --dt 20</div> <div>```</div> <div>You can provide the location of the start of the activation by selecting the desired point ID:</div> <div> <ul> <li>Load the mesh in Paraview (or Meshalyzer)</li> <li>click on the ? symbol</li> <li>save the ID and change the `--pacing` argument </li> </ul> </div> <div> </div> <div>Call `run.py` with a new mesh. The protocol starts by prepacing the mesh and then using the last beat as initial condition tu run the PEERP.</div> <div>Be aware that for a monoatrial mesh you might need to give the new id for the location of the earliest activation. Change `12345` to your desired point ID.</div> <div>```</div> <div>python3 run.py --mesh newMesh --pacing 12345 --protocol prepace --stim_file LA_stim_points.txt</div> <div>```</div> <div> </div> <div>Run the protocol with different electrical remodelling stage. You can change the .par file or select one file from the three provided: </div> <div>```</div> <div>python3 run.py --mesh newMesh --pacing 12345 --protocol PEERP --stim_file LA_stim_points.txt --args.ionic_prop 'l_mk_M.par'</div> <div>```</div> <div> </div> <div>You can also try to run a biatrial example. The biatrial mesh is also provided. You need to extract the points on the RA surface using `getStimPoints.py`, to run the RA experiment: </div> <div>```</div> <div>cd src</div> <div>python3 getStimPoints.py --mesh biatrial --tolerance 20000 --stim_file RA_stim_points.txt --chamber RA</div> <div>```</div> <div>Then run PEERP twice, one per each chamber:</div> <div> </div> <div>```</div> <div>python3 run.py --mesh biatrial --geometry LA_RA_bilayer_with_fiber --pacing 12345 --stim_file LA_endo_2cm.txt --args.ionic_prop 'l_mk_M.par'</div> <div>python3 run.py --mesh biatrial --geometry LA_RA_bilayer_with_fiber --stim_file LA_stim_points.txt --args.ionic_prop 'l_mk_M.par'</div> <p> </p>
Finite element models of human left atria with fibrotic remodeling
Open the record for dataset details and reuse information.
Pacing of the Atria in Sick Sinus Syndrome Trial Preventive Strategies for Atrial Fibrillation
ClinicalTrials.gov study NCT00161538. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Transcriptome and Proteome Mapping in the Sheep Atria Reveal Molecular Features of Atrial Fibrillation Progression
GEO Series GSE138255. Ovis aries. 91 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome of Nkx2-5-null atria
GEO Series GSE52080. Mus musculus. 5 samples. Type: Expression profiling by high throughput sequencing.
Valvular heart disease and atrial fibrillation regulate microRNA expression profiles in left and right atria differently
GEO Series GSE28954. Homo sapiens. 34 samples. Type: Non-coding RNA profiling by array.
PANCR, the PITX2 adjacent noncoding RNA, is specifically expressed in human left atria and regulates PITX2c expression
GEO Series GSE67844. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
RNA-Seq based gene expression profiling of mouse Meis1-Meis2 double KO or wild-type atria and ventricles (Embryo).
GEO Series GSE213356. Mus musculus. 16 samples. Type: Expression profiling by high throughput sequencing.
Single Cell Landscape of Left Atria Reveals Amphiregulin and Insulin-like Growth Factor 1 as Surrogate Markers in Patients with Atrial Fibrillation.
GEO Series GSE261170. Homo sapiens. 15 samples. Type: Expression profiling by high throughput sequencing.
Measurement of Left and Right Atria From CT Scans of Cardiac Rhythm Disorder Cases
ClinicalTrials.gov study NCT01165593. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Triple Atria Extrastimuli vs Pulmonary Vein Isolation Alone in Persistent Atrial Fibrillation
ClinicalTrials.gov study NCT05870306. IPD Sharing: YES. Countries: 1. Publications: 0.
Haemodynamics and Function of the Atria in Congenital Heart Disease by Cardiovascular Magnetic Resonance
ClinicalTrials.gov study NCT02161471. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Examination of Fibrillation Atria Using Magnetic Resonance Imaging and Endocardial High-density Mapping
ClinicalTrials.gov study NCT05539313. IPD Sharing: YES. Countries: 1. Publications: 0.
RNA-Seq based gene expression profiling of mouse Meis1-Meis2 double KO or wild-type atria and ventricles
GEO Series GSE213358. Mus musculus. 32 samples. Type: Expression profiling by high throughput sequencing.
Gene profiling of heart atria in PI3K and Mst1 mouse models
GEO Series GSE12420. Mus musculus. 32 samples. Type: Expression profiling by array.
Expression data from normal atria and ventricles
GEO Series GSE5266. Rattus norvegicus. 8 samples. Type: Expression profiling by array.
Region-specific gene expression profiles in left atria of patients with valvular atrial fibrillation
GEO Series GSE41177. Homo sapiens. 38 samples. Type: Expression profiling by array.
Expression data from Sus scrofa atria
GEO Series GSE43072. Sus scrofa. 6 samples. Type: Expression profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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