The 2017 World Health Organization (WHO) classification proposes to type and subtype primary adenohypophyseal tumours according to their cell lineages with the aim to establish more uniform tumour groups. The definition of atypical adenoma was removed in favour of high-risk adenoma, and the assessment of proliferative activity and invasion was recommended to diagnose aggressive tumours. Recently, the International Pituitary Pathology Club proposed to replace adenoma with the term of pituitary neuroendocrine tumour (PitNET) to better reflect the similarities between adenohypophyseal and neuroendocrine tumours of other organs. The European Pituitary Pathology Group (EPPG) endorses this terminology and develops practical recommendations for standardised reports of PitNETs that are addressed to histo- and neuropathologists. This brief report presents the results of EPPG’s consensus for the reporting of PitNETs and proposes a diagnostic algorithm.

A standardised diagnostic approach to pituitary neuroendocrine tumours (PitNETs): a European Pituitary Pathology Group (EPPG) proposal

Asioli S.;Roncaroli F.
2019

Abstract

The 2017 World Health Organization (WHO) classification proposes to type and subtype primary adenohypophyseal tumours according to their cell lineages with the aim to establish more uniform tumour groups. The definition of atypical adenoma was removed in favour of high-risk adenoma, and the assessment of proliferative activity and invasion was recommended to diagnose aggressive tumours. Recently, the International Pituitary Pathology Club proposed to replace adenoma with the term of pituitary neuroendocrine tumour (PitNET) to better reflect the similarities between adenohypophyseal and neuroendocrine tumours of other organs. The European Pituitary Pathology Group (EPPG) endorses this terminology and develops practical recommendations for standardised reports of PitNETs that are addressed to histo- and neuropathologists. This brief report presents the results of EPPG’s consensus for the reporting of PitNETs and proposes a diagnostic algorithm.
2019
Villa C.; Vasiljevic A.; Jaffrain-Rea M.L.; Ansorge O.; Asioli S.; Barresi V.; Chinezu L.; Gardiman M.P.; Lania A.; Lapshina A.M.; Poliani L.; Reiniger L.; Righi A.; Saeger W.; Soukup J.; Theodoropoulou M.; Uccella S.; Trouillas J.; Roncaroli F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/708013
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