title: Identifying intestinal metaplasia at the squamocolumnar junction by using optical coherence tomography.
abstract: BACKGROUND
  Optical coherence tomography (OCT) is an optical imaging method that produces high-resolution cross-sectional images of the esophagus. The accuracy of OCT for differentiating tissue types at the squamocolumnar junction (SCJ) has not been established.
  
  
  OBJECTIVE
  The purpose of this study was to identify and validate OCT image criteria for distinguishing metaplastic from nonmetaplastic tissue at the SCJ.
  
  
  METHODS
  A total of 196 biopsy-correlated OCT images of the SCJ were acquired from 113 patients undergoing upper endoscopy. A pathologist blinded to the OCT results reviewed each pathology specimen and determined the presence of the following histopathology: gastric cardia, squamous mucosa, pancreatic metaplasia, and intestinal metaplasia. An algorithm for diagnosing specialized intestinal metaplasia (SIM) was created by reviewing a training set of 40 biopsy-correlated OCT images. Two blinded investigators prospectively tested the algorithm on a validation set of 123 images.
  
  
  RESULTS
  OCT images of squamous mucosa were characterized by a layered appearance without epithelial glands; gastric cardia, by vertical pit and gland structure, a well-defined epithelial surface reflectivity, and relatively poor image penetration; and SIM by an irregular architecture and good image penetration. The OCT criteria were 85% sensitive and 95% specific for SIM when applied retrospectively to the training set. When applied to the validation set, the algorithm was 81% sensitive for both OCT readers and 66% and 57% specific for diagnosing SIM. The interobserver agreement was good (kappa = 0.53).
  
  
  CONCLUSIONS
  OCT imaging can identify SIM at the SCJ with an accuracy similar to that of endoscopy.
authors.affiliation: Gastrointestinal Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
authors.forename: John A
authors.initials: JA
authors.lastname: Evans
authors.forename: Brett E
authors.initials: BE
authors.lastname: Bouma
authors.forename: Jason
authors.initials: J
authors.lastname: Bressner
authors.forename: Milen
authors.initials: M
authors.lastname: Shishkov
authors.forename: Gregory Y
authors.initials: GY
authors.lastname: Lauwers
authors.forename: Mari
authors.initials: M
authors.lastname: Mino-Kenudson
authors.forename: Norman S
authors.initials: NS
authors.lastname: Nishioka
authors.forename: Guillermo J
authors.initials: GJ
authors.lastname: Tearney
mesh_terms: D000465:Algorithms; D001471:Barrett Esophagus / Q000175:diagnosis / Q000473:pathology; D002299:Cardia / Q000473:pathology; D004848:Epithelium / Q000473:pathology; D005764:Gastroesophageal Reflux / Q000175:diagnosis / Q000473:pathology*; D020397:Goblet Cells / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007413:Intestinal Mucosa / Q000473:pathology*; D008679:Metaplasia; D015588:Observer Variation; D010179:Pancreas / Q000473:pathology; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D041623:Tomography, Optical Coherence