Mean arterial pressure-aneurysm neck ratio predicts the rupture risk of intracranial aneurysm by reflecting pressure at the dome.

Abstract

Background and purpose:

The unruptured intracranial aneurysm (UIA) has high disability and mortality rate after rupture, it is particularly important to assess the risk of UIA and to carry out individualized treatment. The objective of this research is to introduce a novel parameter to predict the rupture risk of UIA.

Methods:

A total of 649 patients with 964 intracranial aneurysms in our center were enrolled. A novel parameter named mean arterial pressure-aneurysmal neck ratio (MAPN) was defined. Ten baseline clinical features and twelve aneurysm morphological characteristics were extracted to generate the MAPN model. The discriminatory performance of the MAPN model was compared with the PHASES score and the UCAS score.

Results:

In hemodynamic analysis, MAPN was positively correlated with wall shear stress and aneurysm top pressure, with Pearson correlation coefficients of 0.887 and 0.791, respectively. The MAPN was larger in the ruptured group (36.62 ± 18.96 vs. 28.38 ± 14.58, P < 0.001). The area under the curve (AUC) of the MAPN was superior than the AUC of aspect ratio (AR) and the bottleneck factor (BN), they were 0.64 (P < 0.001; 95% CI, 0.588-0.692), 0.611 (P < 0.001; 95% CI, 0.559-0.663) and 0.607 (P < 0.001; 95% CI, 0.554-0.660), respectively. The MAPN model constructed by aneurysm size, aneurysm location, presence of secondary sacs and MAPN, demonstrated good discriminatory ability. The MAPN model exhibited superior performance compared with the UCAS score and the PHASES score (the AUC values were 0.799 [P < 0.001; 95% CI, 0.756-0.840], 0.763 [P < 0.001; 95% CI,0.719-0.807] and 0.741 [P < 0.001; 95% CI, 0.695-0.787], respectively; the sensitivities were 0.849, 0.758 and 0.753, respectively).

Conclusions:

Research demonstrates the potential of MAPN to augment the clinical decision-making process for assessing the rupture risk of UIAs.

• Authors: Jie Shen, Kaiyuan Huang, Yu Zhu, Yuxiang Weng, Feng Xiao, Rajneesh Mungur, Fan Wu, Jianwei Pan, Renya Zhan
• Journal: Frontiers in aging neuroscience (Front Aging Neurosci) Vol. 15 Pg. 1082800 ( 2023) ISSN: 1663-4365 [Print] Switzerland
• PMID: 36819719 (Publication Type: Journal Article)
• Copyright: Copyright © 2023 Shen, Huang, Zhu, Weng, Xiao, Mungur, Wu, Pan and Zhan.