Distinguishing patients with celiac disease by quantitative analysis of videocapsule endoscopy images

Robust spectral analysis of videocapsule images acquired from celiac disease patients

Background

Dominant frequency (DF) analysis of videocapsule endoscopy images is a new method to detect small intestinal periodicities that may result from mechanical rhythms such as peristalsis. Longer periodicity is related to greater image texture at areas of villous atrophy in celiac disease. However, extraneous features and spatiotemporal phase shift may mask DF rhythms.

Method

The robustness of Fourier and ensemble averaging spectral analysis to compute DF was tested. Videocapsule images from the distal duodenum of 11 celiac patients (frame rate 2/s and pixel resolution 576 × 576) were analyzed. For patients 1, 2, ... 11, respectively, a total of 10, 11, ..., 20 sequential images were extracted from a randomly selected time epoch. Each image sequence was artificially repeated to 200 frames, simulating periodicities of 0.2, 0.18, ..., 0.1Hz, respectively. Random white noise at four different levels, spatiotemporal phase shift, and frames with air bubbles were added. Power spectra were constructed pixel-wise over 200 frames, and an average spectrum was computed from the 576 × 576 individual spectra. The largest spectral peak in the average spectrum was the estimated DF. Error was defined as the absolute difference between actual DF and estimated DF.

Results

For Fourier analysis, the mean absolute error between estimated and actual DF was 0.032 ± 0.052Hz. Error increased with greater degree of random noise imposed. In contrast, all ensemble average estimates precisely predicted the simulated DF.

Conclusions

The ensemble average DF estimate of videocapsule images with simulated periodicity is robust to noise and spatiotemporal phase shift as compared with Fourier analysis. Accurate estimation of DF eliminates the need to impose complex masking, extraction, and/or corrective preprocessing measures.

A new transform for the analysis of complex fractionated atrial electrograms

BACKGROUND

Representation of independent biophysical sources using Fourier analysis can be inefficient because the basis is sinusoidal and general. When complex fractionated atrial electrograms (CFAE) are acquired during atrial fibrillation (AF), the electrogram morphology depends on the mix of distinct nonsinusoidal generators. Identification of these generators using efficient methods of representation and comparison would be useful for targeting catheter ablation sites to prevent arrhythmia reinduction.

METHOD

A data-driven basis and transform is described which utilizes the ensemble average of signal segments to identify and distinguish CFAE morphologic components and frequencies. Calculation of the dominant frequency (DF) of actual CFAE, and identification of simulated independent generator frequencies and morphologies embedded in CFAE, is done using a total of 216 recordings from 10 paroxysmal and 10 persistent AF patients. The transform is tested versus Fourier analysis to detect spectral components in the presence of phase noise and interference. Correspondence is shown between ensemble basis vectors of highest power and corresponding synthetic drivers embedded in CFAE.

RESULTS

The ensemble basis is orthogonal, and efficient for representation of CFAE components as compared with Fourier analysis (p ≤ 0.002). When three synthetic drivers with additive phase noise and interference were decomposed, the top three peaks in the ensemble power spectrum corresponded to the driver frequencies more closely as compared with top Fourier power spectrum peaks (p ≤ 0.005). The synthesized drivers with phase noise and interference were extractable from their corresponding ensemble basis with a mean error of less than 10%.

CONCLUSIONS

The new transform is able to efficiently identify CFAE features using DF calculation and by discerning morphologic differences. Unlike the Fourier transform method, it does not distort CFAE signals prior to analysis, and is relatively robust to jitter in periodic events. Thus the ensemble method can provide a useful alternative for quantitative characterization of CFAE during clinical study.

Automated Marsh-like classification of celiac disease in children using local texture operators

Automated classification of duodenal texture patches with histological ground truth in case of pediatric celiac disease is proposed. The classical focus of classification in this context is a two-class problem: mucosa affected by celiac disease and unaffected duodenal tissue. We extend this focus and apply classification according to a modified Marsh scheme into four classes. In addition to other techniques used previously for classification of endoscopic imagery, we apply local binary pattern (LBP) operators and propose two new operator types, one of which adapts to the different properties of wavelet transform subbands. The achieved results are promising in that operators based on LBP turn out to achieve better results compared to many other texture classification techniques as used in earlier work. Specifically, the proposed wavelet-based LBP scheme achieved the best overall accuracy of all feature extraction techniques considered in the two-class case and was among the best in the four-class scheme. Results also show that a classification into four classes is feasible in principle however when compared to the two-class case we note that there is still room for improvement due to various reasons discussed.

Quantitative assessment of endoscopic images for degree of villous atrophy in celiac disease

BACKGROUND

The degree of villous atrophy in celiac disease is difficult to assess at endoscopy. We sought to develop a quantitative technique for the evaluation of villous atrophy in endoscopic images.

METHOD

In ten celiac patients as identified by standard endoscopy with biopsy, and ten control patients, standard and videocapsule endoscopic images of the duodenum were digitized. Subimages 7.5 × 7.5 mm(2) in area from random locations within each image were assessed by measuring the length of mucosal fissures per unit area (L), and correlating L with the histologic grade of villous atrophy as determined by modified Marsh criteria.

RESULTS

Mean L values for standard endoscopic images were 37.8, 43.3, 64.1, and 83.5 mm for Marsh grades II, IIIa, IIIb, and IIIc, respectively. Mean L values for videocapsule images were 49.1, 50.0, 64.7, and 72.4 mm for Marsh grades II, IIIa, IIIb, and IIIc, respectively. Significant differences in the means existed between celiac images (Marsh scores II-IIIc) versus controls (p < 0.001) for both endoscopic and videocapsule images. There were no significant differences between measurements obtained from endoscopic versus videocapsule images.

CONCLUSIONS

Quantified image analysis correlates with the histologic grade of villous atrophy, is automated, and lacks observer bias, thus lending itself to standardization.

Quantitative assessment of endoscopic images for degree of villous atrophy in celiac disease

BACKGROUND

The degree of villous atrophy in celiac disease is difficult to assess at endoscopy. We sought to develop a quantitative technique for the evaluation of villous atrophy in endoscopic images.

METHOD

In ten celiac patients as identified by standard endoscopy with biopsy, and ten control patients, standard and videocapsule endoscopic images of the duodenum were digitized. Subimages 7.5 × 7.5 mm(2) in area from random locations within each image were assessed by measuring the length of mucosal fissures per unit area (L), and correlating L with the histologic grade of villous atrophy as determined by modified Marsh criteria.

RESULTS

Mean L values for standard endoscopic images were 37.8, 43.3, 64.1, and 83.5 mm for Marsh grades II, IIIa, IIIb, and IIIc, respectively. Mean L values for videocapsule images were 49.1, 50.0, 64.7, and 72.4 mm for Marsh grades II, IIIa, IIIb, and IIIc, respectively. Significant differences in the means existed between celiac images (Marsh scores II-IIIc) versus controls (p < 0.001) for both endoscopic and videocapsule images. There were no significant differences between measurements obtained from endoscopic versus videocapsule images.

CONCLUSIONS

Quantified image analysis correlates with the histologic grade of villous atrophy, is automated, and lacks observer bias, thus lending itself to standardization.

Classification of videocapsule endoscopy image patterns: comparative analysis between patients with celiac disease and normal individuals

BACKGROUND

Quantitative disease markers were developed to assess videocapsule images acquired from celiac disease patients with villous atrophy, and from control patients.

METHOD

Capsule endoscopy videoclip images (576 x 576 pixels) were acquired at 2/second frame rate (11 celiacs, 10 controls) at regions: 1. bulb, 2. duodenum, 3. jejunum, 4. ileum and 5. distal ileum. Each of 200 images per videoclip (= 100s) were subdivided into 10 x 10 pixel subimages for which mean grayscale brightness level and its standard deviation (texture) were calculated. Pooled subimage values were grouped into low, intermediate, and high texture bands, and mean brightness, texture, and number of subimages in each band (nine features in all) were used for quantifying regions 1-5, and to determine the three best features for threshold and incremental learning classification. Classifiers were developed using 6 celiac and 5 control patients' data as exemplars, and tested on 5 celiacs and 5 controls.

RESULTS

Pooled from all regions, the threshold classifier had 80% sensitivity and 96% specificity and the incremental classifier had 88% sensitivity and 80% specificity for predicting celiac versus control videoclips in the test set. Trends of increasing texture from regions 1 to 5 occurred in the low and high texture bands in celiacs, and the number of subimages in the low texture band diminished (r(2) > 0.5). No trends occurred in controls.

CONCLUSIONS

Celiac videocapsule images have textural properties that vary linearly along the small intestine. Quantitative markers can assist in screening for celiac disease and localize extent and degree of pathology throughout the small intestine.

Classification of videocapsule endoscopy image patterns: comparative analysis between patients with celiac disease and normal individuals

Background

Quantitative disease markers were developed to assess videocapsule images acquired from celiac disease patients with villous atrophy, and from control patients.

Method

Capsule endoscopy videoclip images (576 × 576 pixels) were acquired at 2/second frame rate (11 celiacs, 10 controls) at regions: 1. bulb, 2. duodenum, 3. jejunum, 4. ileum and 5. distal ileum. Each of 200 images per videoclip (= 100s) were subdivided into 10 × 10 pixel subimages for which mean grayscale brightness level and its standard deviation (texture) were calculated. Pooled subimage values were grouped into low, intermediate, and high texture bands, and mean brightness, texture, and number of subimages in each band (nine features in all) were used for quantifying regions 1-5, and to determine the three best features for threshold and incremental learning classification. Classifiers were developed using 6 celiac and 5 control patients' data as exemplars, and tested on 5 celiacs and 5 controls.

Results

Pooled from all regions, the threshold classifier had 80% sensitivity and 96% specificity and the incremental classifier had 88% sensitivity and 80% specificity for predicting celiac versus control videoclips in the test set. Trends of increasing texture from regions 1 to 5 occurred in the low and high texture bands in celiacs, and the number of subimages in the low texture band diminished (r² > 0.5). No trends occurred in controls.

Conclusions

Celiac videocapsule images have textural properties that vary linearly along the small intestine. Quantitative markers can assist in screening for celiac disease and localize extent and degree of pathology throughout the small intestine.