Computer-Assisted diagnosis for quantitative image-based analysis of crohn's disease in CT enterography

  • Authors:

  • Janne Näppi;June-Goo Lee;Joel G. Fletcher;Hiroyuki Yoshida

  • Affiliations:

  • Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts;Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts;Department of Radiology, Mayo Clinic, Rochester, MN;Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts

  • Venue:
  • MICCAI'10 Proceedings of the Second international conference on Virtual Colonoscopy and Abdominal Imaging: computational challenges and clinical opportunities
  • Year:
  • 2010

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Abstract

Crohn's disease is an inflammatory disease that can cause a wide variety of symptoms and is increasing in prevalence. We developed a computer-assisted diagnosis (CADx) scheme for quantitative image-based analysis of Crohn's disease in CT enterography (CTE). The CADx scheme extracts regions of interest automatically from CTE data, analyzes the small bowel automatically by use of mural features, and uses a support vector machine to predict the presence of active Crohn's disease. For pilot evaluation, two radiologists diagnosed the CTE data of 54 patients with known or suspected Crohn's disease. An unblinded gastroenterologist established the truth about the patients. The CADx scheme was then trained with the CTE data of 46 patients where the radiologists agreed on their diagnosis, and it was tested with the 8 difficult cases where the radiologists disagreed on their diagnosis. A bootstrapping analysis of the per-patient performance of the CADx scheme in predicting the presence of active Crohn's disease yielded an area under receiver-operating characteristic (ROC) curve of 0.92±0.05. The result indicates that the CADx scheme could provide a useful decision-making tool for CTE.