Login / Signup

Can safe and radical resection of all types of parasagittal meningiomas be achievable? -the introduction of a simplified surgical strategy.

Nan ZhangTao YangFarrukh HameedXiang ZhangYang YaoDongxue LiChangwen LiShaojie YuYong XuChengyu XiaXianming Fu
Published in: Neurological research (2020)
Background: Surgery of parasagittal meningiomas (PSMs) is still technically challenging, for the balance between radical resection and preservation of venous circulation. In this article, we'd systemically introduce the technical nuances of a simplified strategy for radical resection of all types of PSMs. All the cases were operated by one single neurosurgeon from a single institution.Methods: Clinical charts of patients with PSMs between 2014 and 2020were retrospectively reviewed. A simplified classification method was adopted, which was based on the relationship between the tumor and superior sagittal sinus (SSS). Surgery aiming at radical resection and venous flow preservation was performed. Only in case of total occlusion of SSS, we performed tumor resection without reconstruction of the venous sinus.Results: Clinical data obtained in 55 consecutive patients (47 primary and 8 recurrent cases) were analyzed, among which 20 were with patent sinus, 27 were with partially occluded sinus and 8 were with completely occluded sinus. Forty-two (76.4%) and 13 patients (23.6%) had the same and improved functional status as compared to that of pre-operation, respectively. Four patients (7.3%) experienced transient neurological deterioration but improved to the normal level in the long-term follow-up. All patients achieved Simpson I/II radical resection. No patients suffered from post-operative recurrence in the follow-up duration of 27.05 ± 19.55 (2-91) months.Conclusion: Radical and safe resection of all types of PSMs is achievable and not difficult if the simplified surgical strategy mentioned in the article is adopted, no matter to which extent the sinus is invaded.
Keyphrases
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • prognostic factors
  • peritoneal dialysis
  • machine learning
  • deep learning
  • patient reported outcomes
  • cerebral ischemia
  • data analysis