Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus.
Background and Aims Previous studies show that microendoscopic images can be interpreted visually to identify the presence of neoplasia in patients with Barrett’s esophagus (BE), but this approach is subjective and requires clinical expertise. This study describes an approach for quantitative image...
| Publicado en: | Gastrointestinal Endoscopy Vol. 83; no. 1; pp. 107 - 115 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Jan2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=111739871&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 111739871 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00165107 4A9 jtl: Gastrointestinal Endoscopy issn: 00165107 maglogo: N pubinfo: dt: Jan2016 vid: 83 iid: 1 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 111739871 111739871 111739871 10.1016/j.gie.2015.06.045 111739871 ppf: 107 ppct: 8 formats: tig: atl: Quantitative analysis of high-resolution microendoscopic images for diagnosis of neoplasia in patients with Barrett’s esophagus. aug: au: Shin, Dongsuk Lee, Michelle H. Polydorides, Alexandros D. Pierce, Mark C. Vila, Peter M. Parikh, Neil D. Rosen, Daniel G. Anandasabapathy, Sharmila Richards-Kortum, Rebecca R. affil: Department of Bioengineering, Rice University, Houston, Texas, USA sug: subj: Barrett Esophagus Diagnosis Esophageal Neoplasms Diagnosis Endoscopy, Gastrointestinal Methods Digital Imaging Human Barrett Esophagus Pathology Esophageal Neoplasms Pathology Sensitivity and Specificity Pilot Studies ab: Background and Aims Previous studies show that microendoscopic images can be interpreted visually to identify the presence of neoplasia in patients with Barrett’s esophagus (BE), but this approach is subjective and requires clinical expertise. This study describes an approach for quantitative image analysis of microendoscopic images to identify neoplastic lesions in patients with BE. Methods Images were acquired from 230 sites from 58 patients by using a fiberoptic high-resolution microendoscope during standard endoscopic procedures. Images were analyzed by a fully automated image processing algorithm, which automatically selected a region of interest and calculated quantitative image features. Image features were used to develop an algorithm to identify the presence of neoplasia; results were compared with a histopathology diagnosis. Results A sequential classification algorithm that used image features related to glandular and cellular morphology resulted in a sensitivity of 84% and a specificity of 85%. Applying the algorithm to an independent validation set resulted in a sensitivity of 88% and a specificity of 85%. Conclusions This pilot study demonstrates that automated analysis of microendoscopic images can provide an objective, quantitative framework to assist clinicians in evaluating esophageal lesions from patients with BE. (Clinical trial registration number: NCT01384227 and NCT02018367 .) pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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