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Histopathology
Article . 2023 . Peer-reviewed
License: CC BY
Data sources: Crossref
Histopathology
Article . 2023
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Updates on lung neuroendocrine neoplasm classification

Authors: Vocino Trucco, Giulia; Righi, Luisella; Volante, Marco; Papotti, Mauro;

Updates on lung neuroendocrine neoplasm classification

Abstract

Lung neuroendocrine neoplasms (NENs) are a heterogeneous group of pulmonary neoplasms showing different morphological patterns and clinical and biological characteristics. The World Health Organisation (WHO) classification of lung NENs has been recently updated as part of the broader attempt to uniform the classification of NENs. This much‐needed update has come at a time when insights from seminal molecular characterisation studies revolutionised our understanding of the biological and pathological architecture of lung NENs, paving the way for the development of novel diagnostic techniques, prognostic factors and therapeutic approaches. In this challenging and rapidly evolving landscape, the relevance of the 2021 WHO classification has been recently questioned, particularly in terms of its morphology‐orientated approach and its prognostic implications. Here, we provide a state‐of‐the‐art review on the contemporary understanding of pulmonary NEN morphology and the potential contribution of artificial intelligence, the advances in NEN molecular profiling with their impact on the classification system and, finally, the key current and upcoming prognostic factors.

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Keywords

Pancreatic Neoplasms, Neuroendocrine Tumors, Lung Neoplasms, artificial intelligence; classification; lung; molecular profile; neuroendocrine neoplasm, Artificial Intelligence, Humans, Lung, Carcinoma, Neuroendocrine

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Average
Top 10%
Green
hybrid
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