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Digital analyses of nuclear features can help discriminate among non-invasive follicular thyroid neoplasm with papillary-like nuclear features, papillary thyroid carcinoma follicular subtype, and follicular carcinoma in cytological specimens.

Fábio Massahito YamamotoLeonardo Carnevalli LianoDeolino João Camilo-JúniorJose Candido Caldeira Xavier
Published in: Cytopathology : official journal of the British Society for Clinical Cytology (2023)
Our analysis of the digital images, with a focus on nuclear parameters, found significantly difference among cytological specimens from cases of NIFTP, PTCFS and FC. Thus, this tool has the potential to provide additional information that may help in the diagnosis of NIFTP, even during the preoperative period. Additional studies are needed to create protocols, evaluate the applicability of nuclear morphological and morphometric parameters-focusing on digital pathology-and create algorithms and tools to assist cytopathologists with their diagnostic routines.
Keyphrases
  • fine needle aspiration
  • deep learning
  • machine learning
  • lymph node
  • patients undergoing
  • healthcare
  • squamous cell carcinoma
  • optical coherence tomography
  • low grade
  • risk assessment