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Tesi etd-03182026-100759


Tipo di tesi
Tesi di laurea magistrale
Autore
PAPINI, ANDREA
URN
etd-03182026-100759
Titolo
Development of a mesh morphing-based tool for estimating the strain field in cardiovascular districts
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA BIOMEDICA
Relatori
relatore Prof. Tognetti, Alessandro
relatore Prof.ssa Celi, Simona
correlatore Ing. Verdirame, Ilaria
Parole chiave
  • FEM
  • left atrial appendage
  • mesh morphing
  • strain field
  • thoracic aorta
Data inizio appello
09/04/2026
Consultabilità
Non consultabile
Data di rilascio
09/04/2096
Riassunto (Inglese)
Cardiovascular wall mechanical properties are closely associated with the onset and progression of severe diseases affecting the thoracic aorta and left atrium (LA), including aneurysm and cardioembolic stroke. Alterations in wall mechanics may lead to aortic rupture and influence tissue–device interaction, as in percutaneous left atrial appendage occlusion procedures in patients with atrial fibrillation. Despite their clinical relevance, current assessment mainly relies on echocardiographic imaging, which provides limited spatial and temporal resolution and is restricted to planar representations. Therefore, the estimation of in vivo deformation and strain fields from medical imaging may provide additional patient-specific information for improved risk stratification and treatment planning.
This study evaluates a non-rigid registration framework based on mesh morphing techniques to reconstruct displacement and strain fields from ECG-gated CT. The method was validated using FEM-derived deformations on idealized geometries to identify optimal operative conditions, and then applied to patient-specific models of the thoracic aorta and LA. Results show accurate reconstruction of deformation fields, with node-to-node errors below CT spatial resolution. Strain patterns are consistent with physiological behavior, while increasing geometric complexity leads to higher registration errors.
These findings suggest that non-invasive estimation of patient-specific mechanics may support identification of regions prone to disease progression and improve procedural planning.
Riassunto (Italiano)
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