Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus.

Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Research Abstract Details 

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Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Abstract Text:

Edmond Sabo,Andrew H Beck,Elizabeth A Montgomery,Baishali Bhattacharya,Patricia Meitner,Ji Yi Wang,Murray B Resnick,

The aims of this study were to use computerized morphometry in order to differentiate between the degree of dysplasia and to predict progression to invasive adenocarcinoma in Barrett's esophagus (BE). Biopsies from 97 patients with BE graded by a consensus forum of expert gastrointestinal pathologists were available for morphometrical analysis. The study group included 36 biopsies negative for dysplasia (ND), none of which progressed to carcinoma; 16 indefinite for dysplasia (IND) and 21 low-grade dysplasia (LGD), of which three progressed in each group and 24 high-grade dysplasia (HGD), of which 15 progressed to invasive carcinoma. Computerized morphometry was used for measuring indices of size, shape, texture, symmetry and architectural distribution of the epithelial nuclei. Low-grade dysplasia was best differentiated from the ND group by nuclear pseudostratification (P=0.036), pleomorphism (P<0.01), and chromatin texture (margination, P<0.01) and from the HGD group by nuclear area (P<0.01), pleomorphism (P<0.01), chromatin texture (margination, P<0.01), symmetry (P<0.01), and orientation (P=0.027). These results were validated on a new set of cases (n=55) using a neural network model, resulting in an accuracy of 89% for differentiating between the ND and LGD groups and 86% for differentiating between the LGD and HGD groups. Within the HGD group, univariate significant predictors of the progression interval to carcinoma were: indices of nuclear texture (heterogeneity: P=0.0019, s.d.-OD: P=0.005) and orientation: P=0.022. Nuclear texture (heterogeneity) was the only independent predictor of progression (P=0.004, hazard=11.54) by Cox's multivariate test. This study proposes that computerized morphometry is a valid tool for determining the grade of dysplasia in BE. Moreover, histomorphometric quantification of nuclear texture is a powerful tool for predicting progression to invasive adenocarcinoma in patients with HGD.

Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Publishing Authors By Initials

E Sabo,AH Beck,EA Montgomery,B Bhattacharya,P Meitner,JY Wang,MB Resnick,

For similar neoplasms: precancerous conditions research abstracts see: neoplasms: precancerous conditions research

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Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Journal Published:

PUBLICATION TYPE: Validation Studies

Journal: Laboratory investigation; a journal of technical m

VOLUME: 86

Page Numbers: 1261-71

Journal Abbreviation: Lab. Invest.

ISSN: 0023-6837

DAY: 30

MONTH: 10

YEAR: 2006

Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Information

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LANGUAGE: eng

NlmUniqueID: 376617

Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus. Keywords Mesh Terms:

KEYWORDS: Precancerous Conditions

MESH TERMS: pathology

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Grant and Affiliation Information for Computerized morphometry as an aid in determining the grade of dysplasia and progression to adenocarcinoma in Barrett's esophagus.

AFFILIATION: Department of Pathology, Rhode Island Hospital and Brown University School of Medicine, Providence, RI 02903, USA. esabo@lifespan.org

Country: United States

AGENCY: United States NCRR

GRANT: P20 RR17695

ACRONYM: RR

MEDLINETA: Lab Invest

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