Skip to Main Content (Press Enter)

Logo UNIPV
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture

UNIFIND
Logo UNIPV

|

UNIFIND

unipv.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  1. Pubblicazioni

Patient-specific aortic endografting simulation: from diagnosis to prediction

Articolo
Data di Pubblicazione:
2013
Abstract:
Traditional surgical repair of ascending aortic pseudoaneurysm is complex, technically challenging, and associated with significant mortality. Although new minimally invasive procedures are rapidly arising thanks to the innovations in catheter-based technologies, the endovascular repair of the ascending aorta is still limited because of the related anatomical challenges. In this context, the integration of the clinical considerations with dedicated bioengineering analysis, combining the vascular features and the prosthesis design, might be helpful to plan the procedure and predict its outcome. Moving from such considerations, in the present study we describe the use of a custom-made stent-graft to perform a fully endovascular repair of an asymptomatic ascending aortic pseudoaneurysm in a patient, who was a poor candidate for open surgery. We also discuss the possible contribution of a dedicated medical images analysis and patient-specific simulation as support to procedure planning. In particular, we have compared the simulation prediction based on pre-operative images with post-operative outcomes. The agreement between the computer-based analysis and reality encourages the use of the proposed approach for a careful planning of the treatment strategy and for an appropriate patient selection, aimed at achieving successful outcomes for endovascular treatment of ascending aortic pseudoaneurysms as well as other aortic diseases.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Auricchio, Ferdinando; Conti, Michele; Marconi, S.; Reali, Alessandro; Tolenaar, J.; Trimarchi, S.
Autori di Ateneo:
AURICCHIO FERDINANDO
CONTI MICHELE
MARCONI STEFANIA
REALI ALESSANDRO
Link alla scheda completa:
https://iris.unipv.it/handle/11571/757632
Pubblicato in:
COMPUTERS IN BIOLOGY AND MEDICINE
Journal
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 25.12.1.0