Thoracic endovascular aortic repair of the ascending aorta is becoming an option for patients considered unfit for open surgery. Such an endovascular procedure requires careful pre-operative planning and the customization of prosthesis design. The patient-specific tailoring of the procedure may call for dedicated tools to investigate virtual treatment scenarios. Given such considerations, the present study shows a computational framework for choosing and deploying stent-grafts via Finite Element Analysis, by supporting the device sizing and selection in a real case dealing with the endovascular treatment of a pseudoaneurysm. In particular, three devices with various lengths and materials were examined. Two off-the-shelf devices were computationally tested: one composed of Stainless Steel rings with a nominal length of 60 mm and another one with Nitinol rings and a distal free flow extension, with a nominal length of 70 mm. In third place, a custom-made stent-graft, also with Nitinol rings and containing both proximal and distal bare extensions with a nominal length of 75 mm, was deployed. The latter solution based on patient morphology and virtually benchmarked in this simulation framework, enhanced the apposition to the wall by reducing the distance between the skirt and the vessel from more than 6 mm to less than 2 mm in the distal sealing zone. Our experience shows that in-silico simulations can help choosing the right endograft for the ascending aorta as well as the right deployment sequence. This process may also encourage vendors to develop new devices for cases where open repair is unfeasible.

Computational simulation of TEVAR in the ascending aorta for optimal endograft selection: A patient-specific case study

R. M. Romarowski;M. Conti;S. Morganti;GRASSI, VANESSA;F. Auricchio
2018-01-01

Abstract

Thoracic endovascular aortic repair of the ascending aorta is becoming an option for patients considered unfit for open surgery. Such an endovascular procedure requires careful pre-operative planning and the customization of prosthesis design. The patient-specific tailoring of the procedure may call for dedicated tools to investigate virtual treatment scenarios. Given such considerations, the present study shows a computational framework for choosing and deploying stent-grafts via Finite Element Analysis, by supporting the device sizing and selection in a real case dealing with the endovascular treatment of a pseudoaneurysm. In particular, three devices with various lengths and materials were examined. Two off-the-shelf devices were computationally tested: one composed of Stainless Steel rings with a nominal length of 60 mm and another one with Nitinol rings and a distal free flow extension, with a nominal length of 70 mm. In third place, a custom-made stent-graft, also with Nitinol rings and containing both proximal and distal bare extensions with a nominal length of 75 mm, was deployed. The latter solution based on patient morphology and virtually benchmarked in this simulation framework, enhanced the apposition to the wall by reducing the distance between the skirt and the vessel from more than 6 mm to less than 2 mm in the distal sealing zone. Our experience shows that in-silico simulations can help choosing the right endograft for the ascending aorta as well as the right deployment sequence. This process may also encourage vendors to develop new devices for cases where open repair is unfeasible.
2018
Medical Research, General Topics covers a wide array of topics in medical and biomedical research, with a specific emphasis on human disease, human tissues, and all levels of research into the pathogenesis of clinically significant conditions. Specific medical fields that are characterized by the inclusion of material from several other specializations are also covered here; these include general and internal medicine, tropical medicine, pediatrics, gerontology, epidemiology, and public health. Resources dealing with specific clinical interventions are excluded and are placed in the Medical Research: Diagnosis & Treatment category. Resources that emphasize the specific disease types, or specific systems affected are also excluded and are categorized according to the pathogen or system pathophysiology.
Medical Research, Organs & Systems includes resources dealing with the normal and disease states of single organs, tissues, or single physiological systems, exclusive of the heart, vascular and immune systems. Systems covered here include hepatology, pulmonary function/physiology, gastroenterology, otolaryngology, respiratory system, andrology, gynecology and reproduction, dermatology, and dentistry/odontology. Resources dealing with general physiology, classes of disease that immediately affect many or all body systems, and medical research focused on specific types of medical intervention are excluded.
Inglese
103
140
147
8
Ascending aorta; Computational simulations; Finite element analysis; TEVAR; Computer Science Applications1707 Computer Vision and Pattern Recognition; Health Informatics
www.elsevier.com/locate/compbiomed
https://www.sciencedirect.com/science/article/pii/S0010482518303135
no
7
info:eu-repo/semantics/article
262
Romarowski, R. M.; Conti, M.; Morganti, S.; Grassi, Vanessa; Marrocco-Trischitta, M. M.; Trimarchi, S.; Auricchio, F.
1 Contributo su Rivista::1.1 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11571/1247266
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