Assessment of Intramural Segment Compression in Anomalous Coronary Arteries through Patient-Specific Finite Element Modeling

Author:

Rosato Antonio1ORCID,Lo Rito Mauro2ORCID,Anglese Serena1ORCID,Ceserani Valentina3,Pascaner Ariel Fernando3ORCID,Secchi Francesco45,Conti Michele3ORCID

Affiliation:

1. 3D and Computer Simulation Laboratory, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy

2. Department of Congenital Cardiac Surgery, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy

3. Department of Civil Engineering and Architecture, University of Pavia, 27100 Pavia, Italy

4. Department of Biomedical Sciences for Health, Università degli Studi di Milano, 20122 Milan, Italy

5. Department of Radiology, IRCCS Policlinico San Donato, 20097 San Donato Milanese, Italy

Abstract

Background: Anomalous Aortic Origin of a Coronary Artery (AAOCA) is a congenital condition that can lead to ischemia and sudden cardiac death. Current diagnostic tools are unable to fully quantify the pathological behavior that occurs mainly with physical effort. Methods: Patients’ computed tomography scans and centerline-based geometric quantities were used to develop three-dimensional computer-aided design models of the main anatomical variants of AAOCA. Blood pressure ranging from rest to extreme effort was simulated through structural finite element analyses, and the pressurized geometries were analyzed to evaluate coronary lumen cross-sectional areas and variations at the different loading conditions. Results: We simulated 39 subjects, demonstrating the ability to reproduce accurately the patient-specific anatomy of different AAOCA variants and capture pathological behaviors. AAOCAs with intramural courses showed compression along the proximal segment with a caliber reduction ranging from 0.14% to 18.87% at different pressure levels. The percentage of proximal narrowing relative to the distal segment was greater than any other type of anomalous course and exceeded 50% with simulated exertion. Conclusions: The present study proposes a computational pipeline to investigate conditions not reproducible in clinical practice, providing information to support decision-making in the management of AAOCA patients.

Funder

Italian Ministry of Health

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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