Three-dimensional volumetric measurements in defining endoscope-guided giant adenoma surgery outcomes

Maximum two-dimensional (2D) diameter has been used to define giant pituitary adenoma (GPA) surgery outcomes as has volume using an ellipsoid approximation of volumetrics. Cross sectional length can be measured in several different planes. We sought to compare the accuracy of different 2D cross sectional measurements with the 3D volumetric measurements for predicting GPA surgery outcomes.

Retrospective analysis was performed on a prospectively collected database. Tumors with >3 cm diameter were identified and classified based on maximal cross sectional measurements in three separate co-axial planes, i.e. transverse (TV), antero-posterior (AP) and cranio-caudal (CC). Volume was calculated using both MRI-guided volumetrics and an ellipsoid approximation (TV × AP × CC/2). Univariate and multivariate analysis was used to evaluate the relationship between cross sectional and volumetric data and extent of resection (EOR).

In 62 subjects, median tumor volume using 3D volumetrics was 13.74 cm(3), which was overestimated by 16 % by the ellipsoid calculation (p = 0.0029), particularly for tumors >20 cm(3). Gross total resection (GTR) was 46.7 % and median EOR was 99.57 %. At 22-month follow-up, visual and anterior pituitary functions were stable (90 %) or improved (87 %). Pre-operative tumor volume >10 cm(3) (p = 0.02) and Knosp grade 3-4 (p = 0.04) were independent predictors of EOR. Knosp grade 3-4 (p < 0.0001), TV measurement >4 cm (p = 0.007) and maximum cross sectional length >4 cm (p = 0.04) were predictors of not achieving GTR. Only TV measurement (p = 0.02) predicted permanent diabetes insipidis. The smallest significant thresholds for predicting decreased GTR were TV measurement >25 mm, AP measurement >35 mm and volume >19 cm(3).

We propose a new volumetric threshold of 20 cm(3) as most accurate for predicting GTR in the EEA era. CC measurement is the least useful predictor. Cavernous sinus invasion remains the best predictor of incomplete resection.