Confocal laser endomicroscopy in coeliac disease

Abstract

Coeliac disease (CD), also known as gluten-sensitive enteropathy, is a chronic disorder with characteristic small intestinal mucosal changes associated with nutrient malabsorption. To date, CD is still diagnosed using histology. The treatment of CD is to follow a gluten-free diet (GFD). The detection of mucosal healing in treated CD patients is important because it can determine the possibility of developing long-term manifestations of CD, such as intestinal lymphoma. According to current guidelines, duodenal biopsy is the most accurate method available for detection of mucosal healing. However, there are difficulties in early detection of healing because it may take up to three years for the biopsy to show healing. Confocal laser endomicroscopy (CLE) is a novel endoscopic method that permits on-site microscopy of the gastrointestinal mucosa. It improves the accuracy of targeted biopsies and enhances the diagnostic outcome in CD, allowing high-resolution in vivo histological analysis. Although computer-aided diagnosis (CAD) has been studied in different medical imaging techniques including computed tomography (CT), magnetic resonance imaging (MRI) and histology slides, its role has not yet been established for CLE images. Aims and methods The main goal of our first study was to design computer-based image-processing (computer-assisted-design [CAD]) techniques for use in the diagnosis of different stages of CD during endoscopy. The aim of this work was to design algorithms that could be implemented by computer software developers who need meticulous step-by-step procedures. My main contribution was to qualitatively define the characteristics of CAD images: this approach differed to previous studies which had mostly used quantitative descriptions in the diagnosis of CD in its different stages. This work is important as quantitative descriptions are non-subjective and can be used by non-experts such as computer software developers, whereas qualitative descriptions are subjective and can only be used by expert medical doctors with significant knowledge in the field. The main goal of our second study was to develop more complex criteria that can detect the severity of CD as well as detecting early signs of healing which cannot be detected using current methods of assessment. We assessed the possibility of enterocyte regeneration as the first sign of mucosal healing using confocal endomicroscopy and histology. These new features can significantly improve CD diagnostic capacity. Results Using the leave-one-out cross-validation scheme, in the first study, 80 images were used for derivative and validation cohorts. Results for our first cohort were 96% sensitivity (probability of detecting images with either villous atrophy [VA] or crypt hypertrophy [CH]) and 89% specificity (probability of detecting normal images). In the validation cohort, a new set of images was used. Due to their overall lower quality, this set of images was more challenging. Results for this cohort were 91% accuracy, 97% sensitivity, 79% specificity, 93% sensitivity and 87% specificity. In the second study, 800 CLE images were produced from 17 subjects. These images were paired with 80 forceps biopsies for analysis. The receiver operating characteristic (ROC) area, using a cut-off of ‘1’, showed the area under the curve (AUC) of 0.94 (95% confidence interval [CI]: 0.83–1.00) for CLE and 0.94 (95% CI: 0.82–1.00) for histopathology. Conclusion In conclusion, we have shown that our algorithm for the automated diagnosis of CD is highly accurate and can be incorporated into the CLE processor for real-time CD diagnosis. In our first study, we proved that CLE accurately detects the enterocyte and goblet cellular regeneration that is representative of CD treatment response. Through CLE, detailed mucosal information is provided, thus enabling endoscopists to make accurate CD diagnoses as well as instantaneously assessing the healing process in treated patients. Future directions The results of our second study can be incorporated into the already developed algorithm and increase the diagnostic capacity of CAD systems. There is also the possibility of detecting fluorescein leakage in the intestinal mucosa of CD patients. Although this leakage has been studied broadly in inflammatory bowel disease, its diagnostic role in CD has never been studied. This could be the major extension to the work reported in this thesis.