Paper Info
Title
Multivariate Analysis For Predicting Internal Carotid (IC) And Middle Cerebral (MC) Aneurysmal Rupture By Hemodynamic Parameters.
Abstract
Currently, aneurysmal rupture can hardly be predicted and the search for an objective and precise indicator is ongoing. The objective of this study was to find a rupture prediction indicator (RPI) based on hemodynamic parameters of unruptured aneurysms focusing on the internal carotid (IC) and middle cerebral (MC) arteries. Computational fluid dynamics simulations were performed and hemodynamic parameters were calculated using three-dimensional C-arm computed tomography (3D C-arm CT) images of a total of 137 unruptured aneurysms (69 IC and 68 MC artery aneurysms) with known outcomes of rupture or unrupture. Multivariate analysis was applied to build an RPI model. The final RPI models contained the pressure-loss coefficient at the time maximum (TMAXPLc). Ruptured aneurysms were found to have lower TMAXPLc than unruptured aneurysms. The mean values were 1.002 (95%CI 0.827 to 1.177) and 1.466 (95%CI 1.352 to 1.579), respectively (P=0.002). TMAXPLc may thus be a useful parameter for rupture prediction of IC and MC artery aneurysms.
Year
DOI
Venue
2018
10.1109/EMBC.2018.8512450
EMBC
Field
DocType
Volume
Hemodynamics,Artery,Computer vision,Ruptured aneurysms,Computer science,Aneurysm,Computed tomography,Artificial intelligence,Radiology,Multivariate analysis
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
10
Name
Order
Citations
PageRank
Takashi Suzuki183.31
Hiroyuki Takao244.88
Soichiro Fujimura301.35
Katharina Otani400.68
Yuya Uchiyama501.35
Kazutoshi Tanaka653.97
Toshihiro Ishibashi713.11
Hiroya Mamori801.35
Y. Murayama924.89
makoto yamamoto1003.04