An algorithm for sellar reconstruction following endoscopic transsphenoidal surgery for pituitary adenoma: A review of 582 cases.

Publication/Presentation Date

9-1-2022

Abstract

BACKGROUND: Several sellar reconstruction algorithms stratify patients based on risk of postoperative cerebrospinal fluid (CSF) leak. Many proposed algorithms employ techniques that are overly complex and confer morbidity. We review our experience with sellar reconstruction following transsphenoidal pituitary surgery and propose a highly effective, yet simple and low morbidity, algorithm.

METHODS: A retrospective review of 582 patients who underwent transsphenoidal surgery for pituitary adenoma by a single neurosurgeon between 2005 and 2020 was performed. Patients without an intraoperative CSF leak and without a patulous diaphragm were repaired with an oxidized cellulose onlay (group 1). Patients with a low-flow intraoperative CSF leak or a patulous diaphragm were repaired with a synthetic dural substitute inlay (group 2). Patients with a persistent leak around the inlay repair or a high-flow leak were reconstructed with a synthetic dural substitute inlay and a nasoseptal flap onlay (group 3).

RESULTS: There was an overall leak rate of 1.5% (9/582) to 1.0% (2/197) in group 1, 1.7% (6/347) in group 2, and 2.6% (1/38) in group 3. Group 3 had the highest rate of postoperative morbidity, including sinusitis (23.7% vs. 8.6% and 15.0% in groups 1 and 2, p = 0.018) and crusting (42.1% vs. 4.6% and 6.3% in groups 1 and 2, p < 0.001). All techniques healed equally well radiographically.

CONCLUSION: The proposed algorithm for sellar reconstruction is highly effective and minimizes complexity and morbidity, primarily utilizing single-layer reconstructions without the addition of packing material or lumbar drainage.

Volume

12

Issue

9

First Page

1120

Last Page

1130

ISSN

2042-6984

Disciplines

Diagnosis | Medicine and Health Sciences | Other Analytical, Diagnostic and Therapeutic Techniques and Equipment | Radiology

PubMedID

35075798

Department(s)

Department of Radiology and Diagnostic Medical Imaging

Document Type

Article

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