Your browser doesn't support javascript.
loading
Digital twinning of cardiac electrophysiology for congenital heart disease.
Salvador, Matteo; Kong, Fanwei; Peirlinck, Mathias; Parker, David W; Chubb, Henry; Dubin, Anne M; Marsden, Alison L.
Afiliación
  • Salvador M; Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA.
  • Kong F; Cardiovascular Institute, Stanford University , Stanford, CA, USA.
  • Peirlinck M; Pediatric Cardiology, Stanford University , Stanford, CA, USA.
  • Parker DW; Institute for Computational and Mathematical Engineering, Stanford University , Stanford, CA, USA.
  • Chubb H; Cardiovascular Institute, Stanford University , Stanford, CA, USA.
  • Dubin AM; Pediatric Cardiology, Stanford University , Stanford, CA, USA.
  • Marsden AL; Department of Biomechanical Engineering, Delft University of Technology , Delft, The Netherlands.
J R Soc Interface ; 21(215): 20230729, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38835246
ABSTRACT
In recent years, blending mechanistic knowledge with machine learning has had a major impact in digital healthcare. In this work, we introduce a computational pipeline to build certified digital replicas of cardiac electrophysiology in paediatric patients with congenital heart disease. We construct the patient-specific geometry by means of semi-automatic segmentation and meshing tools. We generate a dataset of electrophysiology simulations covering cell-to-organ level model parameters and using rigorous mathematical models based on differential equations. We previously proposed Branched Latent Neural Maps (BLNMs) as an accurate and efficient means to recapitulate complex physical processes in a neural network. Here, we employ BLNMs to encode the parametrized temporal dynamics of in silico 12-lead electrocardiograms (ECGs). BLNMs act as a geometry-specific surrogate model of cardiac function for fast and robust parameter estimation to match clinical ECGs in paediatric patients. Identifiability and trustworthiness of calibrated model parameters are assessed by sensitivity analysis and uncertainty quantification.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Electrocardiografía / Cardiopatías Congénitas / Modelos Cardiovasculares Límite: Child / Humans Idioma: En Revista: J R Soc Interface Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Electrocardiografía / Cardiopatías Congénitas / Modelos Cardiovasculares Límite: Child / Humans Idioma: En Revista: J R Soc Interface Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido