Computer-assisted automated image recognition of celiac disease using confocal endomicroscopy

Celiac disease (CD) is an immune-mediated enteropathy triggered by exposure to gluten and similar proteins which affects genetically susceptible persons, increasing their risk of different complications such as malignant lymphomas, small-bowel neoplasia, oropharyngeal tumors, osteoporosis, and bone fractures. In the clinical practice, the diagnosis of CD is made with a diagnostic intestinal biopsy and the concomitant presence of a positive celiac serology. Small bowels mucosa damage due to CD involves various degrees of endoscopically relevant lesions, that are not easily recognized: their overall sensitivity and positive predictive values are poor even when zoom endoscopy is used. Confocal laser endomicroscopy (CLE) has recently revealed to be a useful technique for in vivo virtual histology of small bowels mucosa, but requires skilled and specifically trained operators. We present a computer-based method for the automatic diagnosis of CD-related lesions on the basis of appearance features of confocal images. Comparing the automatic results with the histological gold standard, the proposed method classifies confocal images with accuracy comparable to human observer, suggesting the possibility of real time diagnosis of CD during endoscopy and a noninvasive method to replace biopsy.