title: An algorithmic approach to the diagnosis of pancreatic neoplasms.
abstract: BACKGROUND
  The pancreas gives rise to an array of distinct neoplasms that can be solid, cystic, or intraductal and can recapitulate the various lines of differentiation present in the normal gland.
  
  
  OBJECTIVE
  To develop an algorithmic approach to the diagnosis of pancreatic neoplasms that simplifies their pathologic evaluation.
  
  
  METHODS
  We reviewed literature related to the classification of pancreatic neoplasms on the basis of their gross, histologic, and immunohistochemical features.
  
  
  CONCLUSIONS
  By using a series of dichotomous decisions, the differential diagnosis of a pancreatic neoplasm can be narrowed, and in cases of the more common neoplasms, accurate classification can be achieved. Uncommon neoplasms not accounted for by this approach are also discussed, and the additional diagnostic information needed for complete pathologic reporting is presented.
authors.affiliation: Department of Pathology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA. klimstrd@mskcc.org
authors.forename: David S
authors.initials: DS
authors.lastname: Klimstra
authors.forename: Martha B
authors.initials: MB
authors.lastname: Pitman
authors.forename: Ralph H
authors.initials: RH
authors.lastname: Hruban
mesh_terms: D000465:Algorithms; D002454:Cell Differentiation; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008297:Male; D010190:Pancreatic Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000473:pathology*