ArticlePloS one2017
Joint approach based on clinical and imaging features to distinguish non-neoplastic from neoplastic pituitary stalk lesions.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Pituitary stalk biopsy - A systematic review of the safety and efficacy of stalk lesion biopsy.Pituitary · 2026Pooled it
- Intracranial germ cell tumors: an underrecognized diagnostic consideration in adults with sellar/suprasellar lesions.Journal of neuro-oncology · 2026Article
- Article
- Article
- Complications of Endoscopic Skull Base Surgery for Sellar and Parasellar Tumors in Pediatric Population; Neurosurgical Perspectives.Frontiers in oncology · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeDistinguishing non-neoplastic pituitary stalk lesions (non-NPSLs) from neoplastic pituitary stalk lesions (NPSLs) is a major concern in guiding treatment for a thickened pituitary stalk. Our study aimed to aid provide preoperative diagnostic assistance by combining clinical and magnetic resonance imaging (MRI) findings to distinguish non-NPSLs from NPSLs. MATERIALS AND
methodsWe recruited 158 patients with thickened pituitary stalk lesions visible on MRI. Laboratory findings included hypopituitarism, diabetes insipidus (DI), and hyperprolactinemia. MR images were assessed for anterior-posterior thickness (mm), diffuse pituitary stalk thickening, cystic changes, a high T1 signal, and glandular or extrasellar involvement. A diagnostic model was developed using a recursive partitioning logistic regression analysis. The model was validated in an independent dataset comprising 63 patients, and its diagnostic performance was compared with that of the original radiological reports.
resultsA univariate analysis found significant associations of DI (P = 0.006), absence of extrasellar involvement (P = 0.002), and lower stalk thickness (P = 0.031) with non-NPSLs. A diagnostic model was created using the following parameters (in order of priority): 1) lack of extrasellar involvement, 2) stalk thickness < 5.3 mm, and 3) presence of DI. The diagnostic performance (area under the curve; AUC) of this model in the independent set was 0.813, representing a significant improvement over the original radiological reports (AUC: 0.713, P = 0.029).
conclusionThe joint diagnostic approach based on clinical and imaging-based factors robustly distinguished non-NPSLs from NPSLs. This approach could guide treatment strategies and prevent unnecessary surgery in patients with non-NPSL.
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