Intracavernous Branches of the Internal Carotid Artery Through an Endoscopic Endonasal Approach: Anatomical Study and Review of the Literature

Autor: Carlos Asencio-Cortés, Rosa Mirapeix, Juan Ángel Aibar-Durán, Juan R. Gras-Cabrerizo, Fernando Muñoz-Hernández, Joan R. Montserrat-Gili
Rok vydání: 2021
Předmět:
Zdroj: World Neurosurgery. 151:e332-e342
ISSN: 1878-8750
DOI: 10.1016/j.wneu.2021.04.046
Popis: Objective The endoscopic endonasal transcavernous (EET) approach is an increasingly popular approach for the cavernous sinus and surrounding structure lesions as well as a surgical corridor to pre-mesencephalic cisterns. This endoscopic study describes the main intracavernous branches of the internal carotid artery, providing nuances to improve the safety of this approach. Material and Methods Forty-six fresh cavernous sinus (23 heads) were injected with colored silicon and studied via an EET approach; 6 were excluded due to insufficient injection. The internal carotid artery, the meningohyphophyseal trunk (MHT) and its branches, and the inferolateral trunk were dissected, and branching patterns identified and classified. Results The MHT was identified in 82.5% of cases. Two main MHT types were identified: complete, with 3 main branches, and incomplete, with fewer than 3. The main branches encountered were the inferior hypophyseal artery, present in 92.5% of cases, the dorsal meningeal artery (DMA), present in 87.5%, and the tentorial artery, present in 87.5%. The DMA was classified as prominent medial (48.6%), prominent lateral (20%), or bifurcation type (25.7%). Complete and incomplete MHT were further classified as complete MHT (A, B, and C) and incomplete MHT (A, B, C, and D) according to the combination of the different DMA types with other branches. The inferolateral trunk was a branch of the MHT in 7% of cases. Conclusions The MHT is a highly prevalent intracavernous branch, with 7 identifiable patterns based on DMA morphology and branch combination. This knowledge could guide surgeons in performing a safer EET approach.
Databáze: OpenAIRE
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