Surgically resected cystic lesions in the sellar-suprasellar region: Value of qualitative, semiquantitative, and quantitative imaging variables in the diagnostic work-up

Abstract

Objectives

To identify reliable imaging variables for differentiating cystic lesions by integrating qualitative, semiquantitative, and quantitative features.

Materials & Methods

A retrospective analysis of 100 histologically confirmed cystic sellar-suprasellar lesions was performed using preoperative CT and MRI. Qualitative (topography, type, shape, intracystic components, edema, calcifications), semiquantitative (wall thickness), and quantitative (intracystic signal intensity from T2- and pre-contrast T1-weighted MRI) features were assessed. Multivariable models were developed by combining the most reliable imaging variables specific to each cystic lesion category.

Results

Lesions were categorized as Rathke’s cysts (RCC, 39), papillary (PCP, 14) and adamantinomatous craniopharyngiomas (ACP, 21), pituitary neuroendocrine tumors (PitNets, 18), arachnoid cysts (AC, 8). No clinical presentation was pathognomonic. Multivariable models showed high diagnostic accuracy: 82 % for RCC identifying wall thickness < 1 mm (OR 7.160, p = 0.009) and low T2_min (OR 1.043, p = 0.006) as key predictors; 89 % for PCP despite the absence of distinct independent predictors; 89 % for ACP with parietal calcifications identified as the strongest predictor (OR 0.043, p < 0.001); 90 % for PitNets identifying wall thickness > 2 mm as the strongest predictor (OR 0.52, p < 0.001); and 97 % for AC identifying wall thickness < 1 mm (OR 10.983, p = 0.019) and high T2_min (OR 0.947, p = 0.039) as key predictors.

Conclusion

No single variable was sufficient for diagnosis but integrating specific and sensitive imaging features improved cystic lesion differentiation, aiding accurate diagnosis and management.