Discriminant histological features in the diagnosis of chronic idiopathic inflammatory bowel disease: analysis of a large dataset by a novel data visualisation technique.
OBJECTIVE
The histopathological assessment of endoscopic colorectal biopsies is important in the distinction between normality and chronic idiopathic inflammatory bowel disease, and between ulcerative colitis and Crohn's disease, in subjects with symptoms of bowel dysfunction. This study aims to use carefully defined histopathological observations on a large study population to produce systems that improve classification into these diagnostic categories.


METHODS
Eight hundred and nine endoscopic colorectal biopsies with verified outcomes (165 normal, 473 ulcerative colitis, 171 Crohn's disease) were examined by a single experienced histopathologist and 20 defined features were recorded for each case using a novel graphical interface with reference images of each feature. These features, together with age and sex, were used to produce and test statistical classifiers using logistic regression and a novel growing cell structure technique.


RESULTS
The distinction between chronic idiopathic inflammatory bowel disease and normality was made with a good level of performance by both statistical classifiers (with areas under the receiver operating characteristic curves above 0.80). The growing cell structure system selected features as discriminant that agreed with the published literature. Logistic regression produced a more variable selection of discriminant features because of the high correlation between many features. The distinction between ulcerative colitis and Crohn's disease was performed less accurately, with areas under the receiver operating characteristic curves of about 0.70. Again the features selected as discriminant broadly agreed with those in the published literature.


CONCLUSIONS
Histopathological examination of endoscopic colorectal biopsies is an effective method of distinguishing between subjects with chronic idiopathic inflammatory bowel disease and normality, but less good at distinguishing between ulcerative colitis and Crohn's disease. The features selected as discriminant in this large statistical analysis broadly agree with those published in the literature from more qualitative studies.
Cross
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SS
Academic Unit of Pathology, Section of Oncology and Pathology, Division of Genomic Medicine, University of Sheffield, Sheffield S10 2UL, South Yorkshire, UK. s.s.cross@sheffield.ac.uk
Harrison
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RF
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001706:Biopsy; D003093:Colitis, Ulcerative / Q000473:pathology*; D003113:Colonoscopy; D003424:Crohn Disease / Q000473:pathology*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016017:Odds Ratio; D012372:ROC Curve