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Updates on lung neuroendocrine neoplasm classification.

Giulia Vocino TruccoLuisella RighiMarco VolanteMauro Papotti
Published in: Histopathology (2023)
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.
Keyphrases
  • prognostic factors
  • deep learning
  • machine learning
  • artificial intelligence
  • pulmonary hypertension
  • big data
  • healthcare
  • public health
  • mental health
  • single cell
  • low grade
  • human health
  • high grade
  • climate change