Cargando…

Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis

INTRODUCTION: The TAVR procedure is associated with a substantial risk of thrombosis. Current guidelines recommend catheter-based aortic valve implantation for prohibitive-high-risk patients with severe aortic valve stenosis but acknowledge that the aetiology and mechanism of thrombosis are unclear....

Descripción completa

Detalles Bibliográficos
Autores principales: Nappi, Francesco, Mazzocchi, Laura, Avtaar Singh, Sanjeet Singh, Morganti, Simone, Sablayrolles, Jean-Louis, Acar, Christophe, Auricchio, Ferdinando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217904/
https://www.ncbi.nlm.nih.gov/pubmed/30426001
http://dx.doi.org/10.1155/2018/1346308
_version_ 1783368373073084416
author Nappi, Francesco
Mazzocchi, Laura
Avtaar Singh, Sanjeet Singh
Morganti, Simone
Sablayrolles, Jean-Louis
Acar, Christophe
Auricchio, Ferdinando
author_facet Nappi, Francesco
Mazzocchi, Laura
Avtaar Singh, Sanjeet Singh
Morganti, Simone
Sablayrolles, Jean-Louis
Acar, Christophe
Auricchio, Ferdinando
author_sort Nappi, Francesco
collection PubMed
description INTRODUCTION: The TAVR procedure is associated with a substantial risk of thrombosis. Current guidelines recommend catheter-based aortic valve implantation for prohibitive-high-risk patients with severe aortic valve stenosis but acknowledge that the aetiology and mechanism of thrombosis are unclear. METHODS: From 2015 to 2018, 607 patients with severe aortic valve stenosis underwent either self-expandable or balloon-expandable catheter-based aortic valve implantation at our institute. A complementary study was designed to support computed tomography as a predictor of complications using an advanced biomodelling process through finite element analysis (FEA). The primary evaluation of study was the thrombosis of the valve at 12 months. RESULTS: At 12 months, 546 patients had normal valvular function. 61 patients had THVT while 6 showed thrombosis and dislodgement with deterioration to NYHA Class IV requiring rehospitalization. The FEA biomodelling revealed a strong link between solid uncrushed calcifications, delayed dislodgement of TAVR and late thrombosis. We observed an interesting phenomenon of fibrosis/calcification originating at the level of the misplaced valve, which was the primary cause of coronary obstruction. CONCLUSION: The use of cardiac CT and predictive biomodelling should be integrated into routine practice for the selection of TAVR candidates and as a predictor of negative outcomes given the lack of accurate investigations available. This would assist in effective decision-making and diagnosis especially in a high-risk cohort of patients.
format Online
Article
Text
id pubmed-6217904
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-62179042018-11-13 Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis Nappi, Francesco Mazzocchi, Laura Avtaar Singh, Sanjeet Singh Morganti, Simone Sablayrolles, Jean-Louis Acar, Christophe Auricchio, Ferdinando Biomed Res Int Clinical Study INTRODUCTION: The TAVR procedure is associated with a substantial risk of thrombosis. Current guidelines recommend catheter-based aortic valve implantation for prohibitive-high-risk patients with severe aortic valve stenosis but acknowledge that the aetiology and mechanism of thrombosis are unclear. METHODS: From 2015 to 2018, 607 patients with severe aortic valve stenosis underwent either self-expandable or balloon-expandable catheter-based aortic valve implantation at our institute. A complementary study was designed to support computed tomography as a predictor of complications using an advanced biomodelling process through finite element analysis (FEA). The primary evaluation of study was the thrombosis of the valve at 12 months. RESULTS: At 12 months, 546 patients had normal valvular function. 61 patients had THVT while 6 showed thrombosis and dislodgement with deterioration to NYHA Class IV requiring rehospitalization. The FEA biomodelling revealed a strong link between solid uncrushed calcifications, delayed dislodgement of TAVR and late thrombosis. We observed an interesting phenomenon of fibrosis/calcification originating at the level of the misplaced valve, which was the primary cause of coronary obstruction. CONCLUSION: The use of cardiac CT and predictive biomodelling should be integrated into routine practice for the selection of TAVR candidates and as a predictor of negative outcomes given the lack of accurate investigations available. This would assist in effective decision-making and diagnosis especially in a high-risk cohort of patients. Hindawi 2018-10-22 /pmc/articles/PMC6217904/ /pubmed/30426001 http://dx.doi.org/10.1155/2018/1346308 Text en Copyright © 2018 Francesco Nappi et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Clinical Study
Nappi, Francesco
Mazzocchi, Laura
Avtaar Singh, Sanjeet Singh
Morganti, Simone
Sablayrolles, Jean-Louis
Acar, Christophe
Auricchio, Ferdinando
Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title_full Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title_fullStr Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title_full_unstemmed Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title_short Complementary Role of the Computed Biomodelling through Finite Element Analysis and Computed Tomography for Diagnosis of Transcatheter Heart Valve Thrombosis
title_sort complementary role of the computed biomodelling through finite element analysis and computed tomography for diagnosis of transcatheter heart valve thrombosis
topic Clinical Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6217904/
https://www.ncbi.nlm.nih.gov/pubmed/30426001
http://dx.doi.org/10.1155/2018/1346308
work_keys_str_mv AT nappifrancesco complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT mazzocchilaura complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT avtaarsinghsanjeetsingh complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT morgantisimone complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT sablayrollesjeanlouis complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT acarchristophe complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis
AT auricchioferdinando complementaryroleofthecomputedbiomodellingthroughfiniteelementanalysisandcomputedtomographyfordiagnosisoftranscatheterheartvalvethrombosis