Medial sphenoid wing meningioma classification


see Sphenoid Wing Meningioma Classification.


Al-Mefty based his classification of anterior clinoid region meningiomas on the origin of the tumor and whether arachnoid membrane is present 1) However, the presence of arachnoid membrane cannot be clearly observed preoperatively 2).


Behari et al. proposed a scoring system for predicting the extent of surgical resection in giant mSWM 3).

However, their study only included 20 patients with giant mSWM (≥ 5 cm in maximum dimension), which may lead to biased results. Moreover, they did not show any statistical analyses of their scoring system. McCracken et al. developed a scoring system for evaluating the degree of encasement of arteries surrounded by the SWM on MRI to predict postoperative ischemic complications 4).

Guduk et al. proposed a new scoring system, which included the largest tumor diameter, proximal arterial encasement, distal arterial encasement, and bone invasion pattern, to predict the extent of resection based on preoperative MRI or CT findings 5).

The evolution of 3D multimodality fusion imaging has made more accurate guidance for neurosurgery possible. It can clearly reveal the anatomic relationship of the tumor and its surrounding structures and assist in the selection of operative approach and tumor resection. Most of the feeding arteries, perforating arteries, and veins were encased or displaced by the deep-seated meningiomas, which may affect interpretation in 2D images 6).

Wang et al. described a reliable preoperative scoring system that enables surgeons to predict extent of resection and postoperative outcomes for mSWM based on 3D multimodality fusion imaging. It may aid neurosurgeons in preoperative planning for mSWM and counseling the patient about potential morbidity 7).


Nakamura et al. divided mSWM into 2 groups based on the presence or absence of CS invasion to provide clinical data concerning the visual outcome and recurrence rate 8)

see Cavernous Sinus Meningioma Classification.

see Tuberculum Sellae Meningioma Classification.


Giant medial sphenoid meningioma.

Meningioma en plaque of the sphenoid ridge.

Anterior clinoid region meningioma.

Tuberculum sellae meningioma classification.


1)
Al-Mefty O. Clinoidal meningiomas. J Neurosurg. 1990 Dec;73(6):840-9. doi: 10.3171/jns.1990.73.6.0840. PMID: 2230967.
2) , 7)
Wang Z, Liang X, Yang Y, Gao B, Wang L, You W, Chen Z, Wang Z. A new scoring system for predicting extent of resection in medial sphenoid wing meningiomas based on three-dimensional multimodality fusion imaging. Chin Neurosurg J. 2020 Nov 2;6(1):35. doi: 10.1186/s41016-020-00214-0. PMID: 33292782; PMCID: PMC7604967.
3)
Behari S, Giri PJ, Shukla D, Jain VK, Banerji D. Surgical strategies for giant medial sphenoid wing meningiomas: a new scoring system for predicting extent of resection. Acta Neurochir (Wien). 2008 Sep;150(9):865-77; discussion 877. doi: 10.1007/s00701-008-0006-6. Epub 2008 Aug 27. PMID: 18754074.
4)
McCracken DJ, Higginbotham RA, Boulter JH, Liu Y, Wells JA, Halani SH, Saindane AM, Oyesiku NM, Barrow DL, Olson JJ. Degree of Vascular Encasement in Sphenoid Wing Meningiomas Predicts Postoperative Ischemic Complications. Neurosurgery. 2017 Jun 1;80(6):957-966. doi: 10.1093/neuros/nyw134. PMID: 28327941.
5)
Güdük M, Özduman K, Pamir MN. Sphenoid Wing Meningiomas: Surgical Outcomes in a Series of 141 Cases and Proposal of a Scoring System Predicting Extent of Resection. World Neurosurg. 2019 May;125:e48-e59. doi: 10.1016/j.wneu.2018.12.175. Epub 2019 Jan 11. PMID: 30639480.
6)
Sato M, Tateishi K, Murata H, Kin T, Suenaga J, Takase H, Yoneyama T, Nishii T, Tateishi U, Yamamoto T, Saito N, Inoue T, Kawahara N. Three-dimensional multimodality fusion imaging as an educational and planning tool for deep-seated meningiomas. Br J Neurosurg. 2018 Oct;32(5):509-515. doi: 10.1080/02688697.2018.1485877. Epub 2018 Jun 26. PMID: 29943649.
8)
Nakamura M, Roser F, Jacobs C, Vorkapic P, Samii M. Medial sphenoid wing meningiomas: clinical outcome and recurrence rate. Neurosurgery. 2006 Apr;58(4):626-39, discussion 626-39. doi: 10.1227/01.NEU.0000197104.78684.5D. PMID: 16575326.
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