title: Performance assessment of isolation methods for geometrical cerebral aneurysm analysis.
abstract: Geometrical aneurysm quantification is considered an important topic for the study of aneurysm formation, growth, risk of rupture and also in treatment planning. Usually, quantification involves aneurysm isolation, consisting in the operation of detecting the boundary between the aneurysm dome and its feeding arteries. This operation is sometimes performed manually, but it is a tedious task, subject to user variability. To obtain reproducible measurements, automatic techniques have been proposed. In this paper, we compare different aneurysm isolation techniques, two automatic and one manual-based on a cutting plane. All of them are compared against the results obtained by manual delineations of 26 real cases. We show from the results that automatic methods have good performance, providing results similar to manual methods in average. We also show that automatic methods improve reproducibility compared to direct measurements performed on volume rendering views. Each automatic method presents strengths and weaknesses in particular cases such as small aneurysms, aneurysms with multiple parent vessels or terminal aneurysms, but their reproducibility makes them suitable for robust population studies. Finally, based on this study, we have proposed a criterion that allows to use a combination of the two methods studied and that outperforms each of them individually.
authors.affiliation: Center for Computational Imaging and Simulation Technologies in Biomedicine CISTIB, Universitat Pompeu Fabra, and CIBER-BBN, Barcelona, Spain. ruben.cardenes@upf.edu
authors.forename: Rubén
authors.initials: R
authors.lastname: Cárdenes
authors.forename: Ignacio
authors.initials: I
authors.lastname: Larrabide
authors.forename: Luis San
authors.initials: LS
authors.lastname: Román
authors.forename: Alejandro F
authors.initials: AF
authors.lastname: Frangi
mesh_terms: D002533:Cerebral Angiography / Q000379:methods; D003198:Computer Simulation; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D002532:Intracranial Aneurysm / Q000000981:diagnostic imaging / Q000473:pathology*; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D015203:Reproducibility of Results