Endoscopic Endonasal Excision of Large and Giant Pituitary Adenomas: Radiological and Intraoperative Correlates of the Extent of Resection.


Department of Neurosurgery, Ibn Sina Hospital, Kuwait City, Kuwait. Electronic address: [Email]


BACKGROUND : Despite the superb visualization offered by the endoscopic endonasal transsphenoidal approach, the resection rates of large and giant pituitary adenomas have remained much lower than those of smaller macroadenomas. Various tumor characteristics can influence the extent of resection (EOR) and have been variably reported. Additional understanding of these factors is mandatory to improve the results. We analyzed the radiological and intraoperative tumor characteristics influencing the EOR in a cohort of patients with large and giant pituitary macroadenomas undergoing endoscopic endonasal transsphenoidal excision under our care.
METHODS : Twenty-eight patients were included. Magnetic resonance images were retrospectively analyzed for pre- and postoperative tumor volumetric analysis; preoperative tumor volume calculation using the formula (A × B × C/2); preoperative radioanatomical characteristics, including tumor shape, radiological structure, contrast enhancement, and extension; and the EOR. Intraoperative data were retrieved and included.
RESULTS : The preoperative calculated tumor volume was 38.14 ± 23.02 cm3 and the preoperative measured tumor volume was 50.345 ± 17.36 cm3. A statistically significant difference was found between the calculated and measured tumor volumes for the whole cohort and for tumors with a maximum diameter >3.9 cm. A statistically significant difference in the EOR was found at a volume threshold of 26.2 cm3. Large cysts, heterogeneous enhancement, Knosp grade ≤2, soft tumor consistency, and tumor hemorrhage were significantly associated with gross total resection.
CONCLUSIONS : Volumetric analysis should replace 2-dimensional methods in determining the size of large and giant pituitary adenomas. Specific tumor characteristics were associated with the EOR and could help in predicting the EOR for these tumors.



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