SFEBES2016 Poster Presentations Neuroendocrinology and pituitary (34 abstracts)
Context: Disease processes that affect the pituitary stalk are broad, ranging from indolent lesions requiring simple observation to severe lesions with significant implications. Diagnosis and management of these lesions remains unclear.
Objective: The aim of this study was to assess the clinical presentation, biochemical and pathology characteristics of pituitary stalk thickening lesions and their association with specific MRI features in order to provide diagnostic and prognostic tools to guide the clinician in the management of these difficult patients.
Design and methods: We conducted a retrospective observational study of 36 patients (mean age 37 years, range 483) with pituitary stalk thickening evaluated at a university hospital in Oxford, UK, from 2007 to 2015. We reviewed morphology, signal intensity, enhancement and texture appearance at MRI (evaluated with ImageJ program), along with clinical, biochemical, pathology and long-term follow-up data.
Results: Histological diagnosis was available for 22 patients: 46% neoplastic, 32% inflammatory and 22% congenital lesions. In the remaining 14 patients, a diagnosis of a non-neoplastic disorder was assumed on the basis of long-term follow-up (mean 41.3 months, range: 1284). Diabetes insipidus and headache were common features in 47 and 42% at presentation, with secondary hypogonadism the most frequent anterior pituitary defect. Neoplasia was suggested on size criteria or progression with 30% sensitivity. However, textural analysis of MRI scans revealed a significant correlation between the tumour pathology and pituitary stalk heterogeneity in sagittal pre- and post-gadolinium and in coronal pre- and post-gadolinium T1-weighted image (sensitivity: 89%, specificity: 92%).
Conclusions: New techniques of MRI imaging analysis may identify clinically significant neoplastic lesions, helping to direct future therapy. We propose possible textural heterogeneity criteria of the pituitary stalk on sagittal and coronal pre- and post-gadolinium T1 images with the aim of differentiating between neoplastic and non-neoplastic lesions with high accuracy.
07 Nov 2016 - 09 Nov 2016