Open AccessRole of CT enterography in assessment of Crohn's disease activity: Correlation with histopathologic diagnosis
Author(s) -
Ahmed Mostafa Mohamed,
Shimaa A. Amin,
Maha A. El-Shinnawy,
Amr Elfouly,
Aber Halim Baki
Publication year - 2012
Publication title -
the egyptian journal of radiology and nuclear medicine /the egyptian journal of radiology and nuclear medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.19
H-Index - 13
eISSN - 2090-4762
pISSN - 0378-603X
DOI - 10.1016/j.ejrnm.2012.05.005
Subject(s) - medicine , mcnemar's test , vasa recta , radiology , disease , crohn's disease , lymph , gastroenterology , pathology , statistics , mathematics , medullary cavity
AimTo evaluate the radiological signs of gastro-intestinal inflammation at CT enterography and to assess its accuracy in determining the degree of activity in patients with Crohn's disease (CD).MethodsCT enterography was performed in 26 CD patients and evaluated for the following parameters: mucosal enhancement, abnormal wall thickening, engorged vasa recta, increased density of the mesenteric fat and enlarged mesenteric lymph nodes. Correlations between CT findings and histopathologic results were made using McNemar test.ResultsThere was no significant statistical difference in mucosal enhancement and wall thickening between moderate and severe disease (P=0.631 and 0.138, respectively) whereas engorged vasa recta, fat edema and lymph node enlargement had successfully discriminated between moderate and severe histological findings (P=0.009, <0.001 and 0.045, respectively). Moderate disease was diagnosed correctly by CTE in 50% of cases while severe disease was diagnosed in 100% of cases. When we reconditioned the presence of two CTE severity criteria to diagnose severe disease, the sensitivity to predict moderate disease activity increased to 80%.ConclusionCT enterography is a sensitive and specific non-invasive imaging modality for evaluating the degree of activity of Crohn's disease, and should be considered in its diagnostic and management algorithms