Automated Aortic Anatomy Analysis: from Image to Clinical Indicators.
Journal
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
ISSN: 2694-0604
Titre abrégé: Annu Int Conf IEEE Eng Med Biol Soc
Pays: United States
ID NLM: 101763872
Informations de publication
Date de publication:
Jul 2023
Jul 2023
Historique:
medline:
12
12
2023
pubmed:
12
12
2023
entrez:
12
12
2023
Statut:
ppublish
Résumé
Most cerebrovascular diseases (including strokes and aneurysms) are treated endovascularly with catheters that are navigated from the groin through the vessels to the brain. Many patients have complex anatomy of the aortic arch and supra-aortic vessels, which can make it difficult to select the best catheters for navigation, resulting in longer procedures and more complications or failures. To this end, we propose a framework dedicated to the analysis of the aortic arch and supra-aortic trunks. This framework can automatically compute anatomical and geometrical features from meshes segmented beforehand via CNN-based pipeline. These features such as arch type, tortuosity and angulations describe the navigational difficulties encountered during catheterization. Quantitative and qualitative validation was performed by experienced neuroradiologists, leading to reliable vessel characterization.Clinical relevance- This method allows clinicians to determine the type and the anatomy of the aortic arch and its supra-aortic trunks before endovascular procedures. This is essential in interventional neuroradiology, such as navigation with catheters in this complex area.
Identifiants
pubmed: 38082844
doi: 10.1109/EMBC40787.2023.10340921
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM