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Pituitary stalk thickening: the role of an innovative MRI imaging analysis which may assist in determining clinical management

, : Pituitary stalk thickening: the role of an innovative MRI imaging analysis which may assist in determining clinical management. European Journal of Endocrinology 175(4): 255-263

Disease processes that affect the pituitary stalk are broad; the diagnosis and management of these lesions remains unclear. The aim was to assess the clinical, biochemical and histopathological characteristics of pituitary stalk lesions and their association with specific MRI features in order to provide diagnostic and prognostic guidance. Retrospective observational study of 36 patients (mean age 37years, range: 4-83) with pituitary stalk thickening evaluated at a university hospital in Oxford, UK, 2007-2015. We reviewed morphology, signal intensity, enhancement and texture appearance at MRI (evaluated with the ImageJ programme), along with clinical, biochemical, histopathological and long-term follow-up data. Diagnosis was considered certain 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 41.3months, range: 12-84). 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 pre- and post-gadolinium T1-weighted images (sensitivity: 88.9%, specificity: 91.7%). New techniques of MRI imaging analysis may identify clinically significant neoplastic lesions, thus directing future therapy. We propose possible textural heterogeneity criteria of the pituitary stalk on pre- and post-gadolinium T1 images with the aim of differentiating between neoplastic and non-neoplastic lesions with a high degree of accuracy.


PMID: 27418059

DOI: 10.1530/EJE-16-0455

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