Carolina Malagelada

New insight into intestinal motor function via noninvasive endoluminal image analysis.

BACKGROUND & AIMS Evaluation of small bowel motility by intestinal manometry is invasive and requires expertise for interpretation. Our aim was to use capsule technology for evaluation of small bowel motor function based on a fully computerized image analysis program. METHODS Thirty-six consecutive patients with severe intestinal motor disorders (19 fulfilling manometric criteria of intestinal dysmotility and 17 not) and 50 healthy subjects received the endoscopic capsule (Pillcam; Given Imaging, Yokneam, Israel). Endoluminal image analysis was performed with a computer vision program specifically developed for the detection of contractile patterns (phasic luminal closure and radial wrinkles by wall texture analysis), noncontractile patterns (tunnel and wall appearance by Laplacian filtering), intestinal content (by color decomposition analysis), and endoluminal motion (by chromatic stability). Automatic classification of normal and abnormal intestinal motility was performed by means of a machine-learning technique. RESULTS As compared with healthy subjects, patients exhibited less contractile activity (25% less phasic luminal closures, P < .05) and more noncontractile patterns (151% more tunnel pattern, P < .05), static sequences (56% more static images, P < .01), and turbid intestinal content (94% more static turbid images, P < .01). On cross validation, the classifier identified as abnormal all but 1 patient with manometric criteria of dysmotility and as normal all healthy subjects. Out of the 17 patients without manometric criteria of dysmotility, 11 were identified as abnormal and 6 as normal. CONCLUSIONS Our study shows that endoluminal image analysis, by means of computer vision and machine-learning techniques, constitutes a reliable, noninvasive, and automated diagnostic test of intestinal motor disorders.

Colonic Responses to Gas Loads in Subgroups of Patients With Abdominal Bloating

OBJECTIVES:We sought to evaluate colonic gas accommodation, ileocecal competence, and colonic clearance in subgroups patients with abdominal bloating.METHODS:Thirty-six patients complaining of abdominal bloating (12 constipation-predominant irritable bowel syndrome (IBS-C), 12 diarrhea-predominant irritable bowel syndrome (IBS-D), and 12 functional bloating) and 18 healthy controls were studied. Abdominal perception and girth were measured during: (i) 1 h continuous infusion of gas at 24 ml/min into the rectum (accommodation period) and (ii) 30 min free rectal gas evacuation (clearance period). In eight patients and eight healthy subjects, the gas infused was labeled with radioactive xenon (74 MBq 133Xe), and gas distribution was determined by scintigraphy.RESULTS:Colonic gas accommodation produced significantly more abdominal symptoms and distension in patients than in healthy subjects (3.8±0.2 vs. 2.4±0.3 perception score; P<0.001; 10.9±0.6 vs. 8.3±0.5 mm girth increment; P=0.009). Scintigraphy showed no differences in colonic gas distribution and no ileal gas reflux, but patients exhibited impaired gas clearance from the proximal colon (63%±10% clearance in 30 min vs. 80%±2% in health; P=0.042), resulting in more residual gas (506±46 vs. 174±47 ml; P<0.001), perception (1.9±0.2 vs. 1.0±0.2 score; P=0.015), and girth increment (4.2±0.7 vs. 2.2±0.5 mm; P=0.024); IBS-C patients exhibited increased sensation and objective distension, as opposed to sensation only in IBS-D and distension only in functional bloating.CONCLUSIONS:Patients with abdominal bloating have normal colonic accommodation and ileocecal competence but impaired gas clearance from the proximal colon after retrograde infusion, and the consequences of this dysfunction are related to bowel habit.

Categorization and Segmentation of Intestinal Content Frames for Wireless Capsule Endoscopy

Wireless capsule endoscopy (WCE) is a device that allows the direct visualization of gastrointestinal tract with minimal discomfort for the patient, but at the price of a large amount of time for screening. In order to reduce this time, several works have proposed to automatically remove all the frames showing intestinal content. These methods label frames as {intestinal content - clear} without discriminating between types of content (with different physiological meaning) or the portion of image covered. In addition, since the presence of intestinal content has been identified as an indicator of intestinal motility, its accurate quantification can show a potential clinical relevance. In this paper, we present a method for the robust detection and segmentation of intestinal content in WCE images, together with its further discrimination between turbid liquid and bubbles. Our proposal is based on a twofold system. First, frames presenting intestinal content are detected by a support vector machine classifier using color and textural information. Second, intestinal content frames are segmented into {turbid, bubbles, and clear} regions. We show a detailed validation using a large dataset. Our system outperforms previous methods and, for the first time, discriminates between turbid from bubbles media.

Functional gut disorders or disordered gut function? Small bowel dysmotility evidenced by an original technique

Background  This study aimed to determine the proportion of cases with abnormal intestinal motility among patients with functional bowel disorders. To this end, we applied an original method, previously developed in our laboratory, for analysis of endoluminal images obtained by capsule endoscopy. This novel technology is based on computer vision and machine learning techniques.

Nitrergic and purinergic mechanisms evoke inhibitory neuromuscular transmission in the human small intestine

Inhibitory neuromuscular transmission in the human colon is due to nitrergic and purinergic (P2Y1‐mediated) inputs. The aim of this study was to determine the mechanisms of neuromuscular transmission in different regions of the human small intestine.

Intestinal motor activity, endoluminal motion and transit.

Abstract  A programme for evaluation of intestinal motility has been recently developed based on endoluminal image analysis using computer vision methodology and machine learning techniques. Our aim was to determine the effect of intestinal muscle inhibition on wall motion, dynamics of luminal content and transit in the small bowel. Fourteen healthy subjects ingested the endoscopic capsule (Pillcam, Given Imaging) in fasting conditions. Seven of them received glucagon (4.8 μg kg−1 bolus followed by a 9.6 μg kg−1 h−1 infusion during 1 h) and in the other seven, fasting activity was recorded, as controls. This dose of glucagon has previously shown to inhibit both tonic and phasic intestinal motor activity. Endoluminal image and displacement was analyzed by means of a computer vision programme specifically developed for the evaluation of muscular activity (contractile and non‐contractile patterns), intestinal contents, endoluminal motion and transit. Thirty‐minute periods before, during and after glucagon infusion were analyzed and compared with equivalent periods in controls. No differences were found in the parameters measured during the baseline (pretest) periods when comparing glucagon and control experiments. During glucagon infusion, there was a significant reduction in contractile activity (0.2 ± 0.1 vs 4.2 ± 0.9 luminal closures per min, P < 0.05; 0.4 ± 0.1 vs 3.4 ± 1.2% of images with radial wrinkles, P < 0.05) and a significant reduction of endoluminal motion (82 ± 9 vs 21 ± 10% of static images, P < 0.05). Endoluminal image analysis, by means of computer vision and machine learning techniques, can reliably detect reduced intestinal muscle activity and motion.

Linear radial patterns characterization for automatic detection of tonic intestinal contractions

This work tackles the categorization of general linear radial patterns by means of the valleys and ridges detection and the use of descriptors of directional information, which are provided by steerable filters in different regions of the image. We successfully apply our proposal in the specific case of automatic detection of tonic contractions in video capsule endoscopy, which represent a paradigmatic example of linear radial patterns.

Diabetic neuropathy in the gut: pathogenesis and diagnosis

The activity of the digestive tract is usually regulated to match its content: physiological stimuli in the gut induce modulatory reflexes that control digestive function so that digestion is normally not perceived. However, under certain circumstances, digestive stimuli may activate sensory afferents and give rise to conscious sensations. Both reflex and sensory signals are modulated by a balance of excitatory and inhibitory mechanisms. Patients with diabetes may develop a neuropathy affecting the control of gastric and/or intestinal motor function and the sensory innervation as well. During fasting the stomach is contracted and relaxes to accommodate a meal. After ingestion the stomach progressively recontracts and this contraction gently produces gastric emptying. Impairment of excitatory pathways affects the contraction of the stomach, which may result in delayed gastric emptying and vomiting of retained food. Conversely, alteration of the inhibitory neural pathways results in impaired relaxation of the stomach in response to a meal; in this case increased wall tension may produce early satiation, fullness and nausea. Diabetic neuropathy may distort the control of intestinal motility, which can lead to diverse symptoms such as diarrhoea, constipation, intestinal distension and abdominal pain. Neuropathy in diabetes may also affect the sensory nerves of the gut, and depending on which pathways are involved, perception may be increased or reduced. In summary, in patients with diabetic neuropathy, disorders of gut motor function are associated with sensory abnormalities, and the combination of impaired pathways determines the clinical consequences. This review summarises a presentation given at the ‘Diagnosis and treatment of autonomic diabetic neuropathy in the gut’ symposium at the 2015 annual meeting of the EASD. It is accompanied by another mini-review on a topic from this symposium (by Hans Törnblom, DOI: 10.1007/s00125-015-3829-9) and a commentary by the Session Chair, Péter Kempler (DOI: 10.1007/s00125-015-3826-y).

Digestive, cognitive and hedonic responses to a meal.

Gut dysfunctions may be associated to digestive symptoms. We hypothesized that the gut can also originate pleasant sensations, and wished to demonstrate the hedonic component of the digestive response to a meal.

Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis

We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function.