Three-dimensional parametric modeling of bicuspid aortopathy and comparison with computational flow predictions

Francesco Scardulla, Salvatore Pasta, Cesare Scardulla, Michele Pilato, Diego Bellavia, Giuseppe M. Raffa, Giovanni Gentile, Salvatore Pasta, Giuseppe M. Raffa, Angelo Luca, Diego Bellavia, Giovanni Domenico Gentile

Risultato della ricerca: Articlepeer review

11 Citazioni (Scopus)


Bicuspid aortic valve (BAV)-associated ascending aneurysmal aortopathy (namely âbicuspid aortopathyâ) is a heterogeneous disease making surgeon predictions particularly challenging. Computational flow analysis can be used to evaluate the BAV-related hemodynamic disturbances, which likely lead to aneurysm enlargement and progression. However, the anatomic reconstruction process is time consuming so that predicting hemodynamic and structural evolution by computational modeling is unfeasible in routine clinical practice. The aim of the study was to design and develop a parametric program for three-dimensional (3D) representations of aneurysmal aorta and different BAV phenotypes starting from several measures derived by computed-tomography angiography (CTA). Assuming that wall shear stress (WSS) has an important implication on bicuspid aortopathy, computational flow analyses were then performed to estimate how different would such an important parameter be, if a parametric aortic geometry was used as compared to standard geometric reconstructions obtained by CTA scans. Morphologic parameters here documented can be used to rapidly model the aorta and any phenotypes of BAV. t-test and BlandâAltman plot demonstrated that WSS obtained by flow analysis of parametric aortic geometries was in good agreement with that obtained from the flow analysis of CTA-related geometries. The proposed program offers a rapid and automated tool for 3D anatomic representations of bicuspid aortopathy with promising application in routine clinical practice by reducing the amount of time for anatomic reconstructions.
Lingua originaleEnglish
pagine (da-a)E92-E102
Numero di pagine11
RivistaArtificial Organs
Stato di pubblicazionePublished - 2017

All Science Journal Classification (ASJC) codes

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  • ???subjectarea.asjc.2700.2701???
  • ???subjectarea.asjc.2500.2502???
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