Quantitative image analysis of celiac disease

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis

A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biopsies. Recently, considerable effort has been undertaken to make use of image material by developing semi- or fully-automated systems to improve the diagnostic workup. Recently, focus was especially laid on developing state-of-the-art deep learning architectures, exploiting the endoscopist's expert knowledge and on making systems fully automated and thereby completely observer independent. In this work, we summarize recent trends in the field of computer-aided celiac disease diagnosis based on upper endoscopy and discuss about recent progress, remaining challenges, limitations currently prohibiting a deployment in clinical practice and future efforts to tackle them.

Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease

Celiac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic method for villi detection from confocal endoscopy images, whose appearance change in case of villous atrophy. Starting from a set of manual seeds, a first rough segmentation of the villi is obtained by means of mathematical morphology operations. A merge and split procedure is then performed, to ensure that each seed originates a different region in the final segmentation. A border refinement process is finally performed, evolving the shape of each region according to local gradient intensities. Mean and median Dice coefficients for 290 villi originating from 66 images when compared to manually obtained ground truth are 80.71% and 87.96% respectively.

Celiac disease: From pathophysiology to treatment

Celiac disease, also known as "celiac sprue", is a chronic inflammatory disorder of the small intestine, produced by the ingestion of dietary gluten products in susceptible people. It is a multifactorial disease, including genetic and environmental factors. Environmental trigger is represented by gluten while the genetic predisposition has been identified in the major histocompatibility complex region. Celiac disease is not a rare disorder like previously thought, with a global prevalence around 1%. The reason of its under-recognition is mainly referable to the fact that about half of affected people do not have the classic gastrointestinal symptoms, but they present nonspecific manifestations of nutritional deficiency or have no symptoms at all. Here we review the most recent data concerning epidemiology, pathogenesis, clinical presentation, available diagnostic tests and therapeutic management of celiac disease.

Coeliac disease and the videocapsule: what have we learned till now

Celiac disease is diagnosed in part by finding areas of pathology in the small bowel (SB) mucosa. This can often be difficult because the pathologic alterations, including atrophy of the small intestinal villi, can often be sparse and subtle. Some of the quantitative methods for detecting and measuring the presence of villous atrophy from videocapsule endoscopy (VCE) images are presented and discussed. These methods consist of static features of measurement including texture, gray level, and presence and abundance of fissures contained within each acquired image. The methods also consist of dynamic measurements including spectral analysis, and determining motion from a sequence of endoscopic images as obtained from a VCE clip. Thus far, several methods have been found useful to characterize the SB mucosa of untreated celiac disease patients versus control patients lacking villous atrophy, which have revealed significant differences in texture, frequency, and motion on analysis of VCE. In untreated celiac patients undergoing endoscopy, there tends to be greater magnitude of changes and spatial differences in textural descriptors, longer periodic components, indicating slower periodic activity, and differences in feature location, suggesting alterations in motility at areas of pathology as compared to patients without villous atrophy. Improvements in the quantitative analysis of VCE imaging in celiac patients is important to detect pathology in suspected patients, so that biopsies can be obtained from pertinent regions of the small intestinal mucosa. Improvements are also necessary so that patients with celiac disease can be monitored to evaluate the progress of mucosal healing after onset of treatment.

Recommendations to quantify villous atrophy in video capsule endoscopy images of celiac disease patients

AIM

To quantify the presence of villous atrophy in endoscopic images for improved automation.

METHODS

There are two main categories of quantitative descriptors helpful to detect villous atrophy: (1) Statistical and (2) Syntactic. Statistical descriptors measure the small intestinal substrate in endoscope-acquired images based on mathematical methods. Texture is the most commonly used statistical descriptor to quantify villous atrophy. Syntactic descriptors comprise a syntax, or set of rules, for analyzing and parsing the substrate into a set of objects with boundaries. The syntax is designed to identify and distinguish three-dimensional structures based on their shape.

RESULTS

The variance texture statistical descriptor is useful to describe the average variability in image gray level representing villous atrophy, but does not determine the range in variability and the spatial relationships between regions. Improved textural descriptors will incorporate these factors, so that areas with variability gradients and regions that are orientation dependent can be distinguished. The protrusion syntactic descriptor is useful to detect three-dimensional architectural components, but is limited to identifying objects of a certain shape. Improvement in this descriptor will require incorporating flexibility to the prototypical template, so that protrusions of any shape can be detected, measured, and distinguished.

CONCLUSION

Improved quantitative descriptors of villous atrophy are being developed, which will be useful in detecting subtle, varying patterns of villous atrophy in the small intestinal mucosa of suspected and known celiac disease patients.

Extraction and processing of videocapsule data to detect and measure the presence of villous atrophy in celiac disease patients

BACKGROUND

Videocapsule endoscopy is a relative new method to analyze the gastrointestinal tract for the presence of pathologic features. It is of relevance to detect villous atrophy in the small bowel, which is a defining symptom of celiac disease.

METHOD

In this tutorial, methods to extract and process videocapsule endoscopy data are elucidated. The algorithms, computer code, and paradigms to analyze image series are described in detail. The topics covered include extraction of data, analysis of texture, eigenanalysis, spectral analysis, three-dimensional projection, and estimation of motility. The basic paradigms to implement these processes are provided.

RESULTS

Examples of successful quantitative analysis implementations for selected untreated celiac disease patients with villous atrophy versus control patients with normal villi were illustrated. Based on the implementations, it was evident that celiac patients tended to have a rougher small intestinal texture as compared with control patients. From three-dimensional projection, celiac patients exhibited larger surface protrusions emanating from the small intestinal mucosa, which may represent clumps of atrophied villi. The periodicity of small intestinal contractions tends to be slower when villous atrophy is present, and the estimated degree of motility is reduced as compared with control image series. Basis image construction suggested that fissuring and mottling of the mucosal surface is predominant in untreated celiac patients, and mostly absent in controls.

CONCLUSIONS

Implementation of computerized methods, as described in this tutorial, will likely be useful for the automated detection and measurement of villous atrophy, and to map its extent along the small intestine of celiac patients.