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Record W3209674794 · doi:10.5281/zenodo.4590294

Virtual cohort of adult healthy four-chamber heart meshes from CT images

2021· dataset· en· W3209674794 on OpenAlexaff
Cristóbal Rodero, Marina Strocchi, M Marciniak, Stefano Longobardi, John Whitaker, Mark O’Neill, Karli Gillette, Christoph M. Augustin, Gernot Plank, Edward J. Vigmond, Pablo Lamata, Steven Niederer

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsSt. Thomas Hospital
FundersEuropean CommissionResearch Councils UKWellcome
KeywordsPolygon meshCohortMedicineComputer scienceComputer graphics (images)Nuclear medicineComputer visionArtificial intelligenceInternal medicine

Abstract

fetched live from OpenAlex

<strong>Dataset Description: </strong>We present the first database of four-chamber healthy heart models suitable for electro-mechanical (EM) simulations. Our database consists of twenty four-chamber heart models generated from end-diastolic CT acquired from patients who went to the emergency room with acute chest pains. Since no cardiac conditions were detected in follow-up, these patients were taken as representative of "healthy" (or asymptomatic) hearts. These meshes were used for EM simulations and to build a statistical shape model (SSM). The output of the simulations and the weights of the SSM are also provided. <strong>Cardiac meshes: </strong>We segmented end-diastolic CT. The segmentation was then upsampled and smoothed. The final multi-label segmentation was used to generate a tetrahedral mesh. The resulting meshes had an average edge length of 1 mm. The elements of all the twenty meshes are labelled as follows: Left ventricle myocardium Right ventricle myocardium Left atrium myocardium Right atrium myocardium Aorta wall Pulmonary artery wall Mitral valve plane Tricuspid valve plane Aortic valve plane Pulmonary valve plane Left atrium appendage "inlet" Left superior pulmonary vein inlet Left inferior pulmonary vein inlet Right inferior pulmonary vein inlet Right superior pulmonary vein inlet Superior vena cava inlet Inferior vena cava inlet Left atrial appendage border Right inferior pulmonary vein border Left inferior pulmonary vein border Left superior pulmonary vein border Right superior pulmonary vein border Superior vena cava border Inferior vena cava border Ventricular fibres were generated using a rule-based method, with a fibre orientation varying transmurally from endocardium to epicardium from 80˚ to -60˚, respectively. We defined a system of universal ventricular coordinates on the meshes: an apico-basal coordinate (Z) varying continuously from 0 at the apex to 1 at the base (defined with the mitral and tricuspid valve); a transmural coordinate (\(\rho\)) varying continuously from 0 at the endocardium to 1 at the epicardium; a rotational coordinate (\(\phi\)) varying continuously from – π at the left ventricular free wall, 0 at the septum and then back to + π at the left ventricular free wall; intra-ventricular coordinate (V) defined at -1 at the left ventricle and +1 at the right ventricle. This coordinate system was assigned to the ventricles in the four-chamber meshes and all the other labels were assigned with -10. <strong> </strong>We provide a zipped folder for each mesh, A VTK file for each mesh was included (in ASCII) as an UNSTRUCTURED GRID. In all the cases the following fields were included: POINTS, with the coordinates of the points in mm. CELL_TYPES, having all of the points the value 10 since they are tetrahedra. CELLS, with the indices of the vertices of every element. CELL_DATA, corresponding to the meshing tags. VECTORS, with the directions of the fibres. POINT_DATA, with four LOOKUP_TABLE subfields corresponding to the UVC in the order \(\rho\), \(\phi\), Z and V. <strong>Cardiac simulations: </strong>For the cardiac EM simulations we used CARP (Cardiac Arrhythmia Research Package). We used the reaction-eikonal model for electrophysiology, stimulating as initial condition the bottom third (Z &lt; 0.33) of the endocardium. We simulated the large deformation mechanics in a Lagrangian reference system. The ventricular myocardium was modelled as a hyperelastic transversely isotropic material with Guccione's strain energy function. The remaining tissues were modelled as non-contracting neo-Hookean materials. Simulations of meshes #09 and #10 failed to converge. Details on the specific parametrisation can be found in the supplements of the reference paper. We provide comma-separated-values files with the output of the simulations used in the reference paper for validation purposes. The simulations of the cases that did not converge were not included. The acronyms used in the names of columns are: EDP: End-diastolic pressure EDV: End-diastolic volume Myo_vol: Myocardial volume of the ventricle (as sum of its elements) ESV: End-systolic volume SV: Stroke volume EF: Ejection fraction V1: Volume at time of peak flow EF1: First-Phase Ejection Fraction ESP: End-systolic pressure dPdtmax: Maximum increase of pressure dPdtmin: Maximum decrease of pressure PeakP: Peak pressure tpeak: Time to peak pressure ET: Ejection time ICT: Isovolumic contraction time IRT: Isovolumic relaxation time tsys: Duration of systole QRS: QRS duration AT1090: Time taken to activate from 10% to 90% of the mesh AT: Activation time of the left ventricle Besides the output value name, in each column is specified the ventricle where that output was extracted from with the suffixes "_LV" or "_RV". <strong>Statistical shape model: </strong>All the meshes but #20 were used to build a statistical shape model of four-chambers cardiac meshes. In short, we rigidly aligned the meshes and extracted the surfaces, representing them as deRham currents. The registration between meshes and computation of the average shape (also called atlas or template) was done using a Large Deformation Diffeomorphic Metric Mapping method. Each one of the meshes can be approximated as a linear combination of the shape modes, extracted using Principal Component Analysis on the space where the meshes are located. More details on the Statistical Shape Model are provided in the supplement of the reference paper. The average heart and extreme cases are provided in the repository named "Virtual cohort of extreme and average four-chamber heart meshes from statistical shape model". We have added 1000 more meshes from the same statistical shape model, modifying the weights from the PCA randomly within the 2SD range. These meshes are provided in the repository named "Virtual cohort of 1000 synthetic heart meshes from the adult human healthy population". We provide the weights of the modes for each of the 19 meshes in a comma-separated-values file.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0200.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.282
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations3
Published2021
Admission routes1
Has abstractyes

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