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Enregistrement W3209674794 · doi:10.5281/zenodo.4590294

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

2021· dataset· en· W3209674794 sur 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

Notice bibliographique

RevueZenodo (CERN European Organization for Nuclear Research) · 2021
Typedataset
Langueen
DomaineMedicine
ThématiqueRadiomics and Machine Learning in Medical Imaging
Établissements canadiensSt. Thomas Hospital
Organismes subventionnairesEuropean CommissionResearch Councils UKWellcome
Mots-clésPolygon meshCohortMedicineComputer scienceComputer graphics (images)Nuclear medicineComputer visionArtificial intelligenceInternal medicine

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,018
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0200,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,282
Écart entre enseignants0,261 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2021
Routes d'admission1
Résumé présentoui

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