Added Predictive Values of Proton Density Magnetic Resonance Imaging on Posterior Communicating Artery Aneurysms and Surrounding Soft Tissues with Simple Classification
- Author:
Sun YOON
1
;
Min Jeoung KIM
;
Hyun Jin HAN
;
Keun Young PARK
;
Joonho CHUNG
;
Yong Bae KIM
Author Information
- Publication Type:Clinical Article
- From:Journal of Korean Neurosurgical Society 2023;66(4):418-425
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective:: Deciphering the anatomy of posterior communicating artery (PCoA) aneurysms in relation to surrounding structures is essential to determine adjuvant surgical procedures. However, it is difficult to predict surgical structures through preoperative imaging studies. We aimed to present anatomical structures using preoperative high-resolution three-dimensional proton densityweighted turbo spin-echo magnetic resonance (PDMR) imaging with simple classification.
Methods:: From January 2020 to April 2022, 30 patients underwent PDMR before microsurgical clipping for unruptured PCoA aneurysms in a single tertiary institute. We retrospectively reviewed the radiographic images and operative data of these patients. The structural relationship described by PDMR and intraoperative findings were compared. Subsequently, we classified aneurysms into two groups and analyzed the rate of adjuvant surgical procedures and contact with the surrounding structures.
Results:: Correlations between preoperative PDMR predictions and actual intraoperative findings for PCoA aneurysm contact to the oculomotor nerve, temporal uncus, and anterior petroclinoid fold (APCF) reported a diagnostic accuracy of 0.90, 0.87, and 0.90, respectively. In 12 patients (40.0%), an aneurysm dome was located on the plane of the oculomotor triangle and was classified as the infratentorial type. Compared to the supratentorial type PCoA aneurysm, adjuvant procedures were required more frequently (66.7% vs. 22.2%, p=0.024) for infratentorial type PCoA aneurysm clipping.
Conclusion:: Preoperative PCoA aneurysm categorization using PDMR can be helpful for predicting surgical complexity and planning of microsurgical clipping.
