ABSTRACT
The analysis of colonic contents is a valuable tool for the gastroenterologist and has multiple applications in clinical routine. When considering magnetic resonance imaging (MRI) modalities, T2 weighted images are capable of segmenting the colonic lumen, whereas fecal and gas contents can only be distinguished in T1 weighted images. In this paper, we present an end-to-end quasi-automatic framework that comprises all the steps needed to accurately segment the colon in T2 and T1 images and to extract colonic content and morphology data to provide the quantification of colonic content and morphology data. As a consequence, physicians have gained new insights into the effects of diets and the mechanisms of abdominal distension.
ABSTRACT
The study of the colonic volume is a procedure with strong relevance to gastroenterologists. Depending on the clinical protocols, the volume analysis has to be performed on MRI of the unprepared colon without contrast administration. In such circumstances, existing measurement procedures are cumbersome and time-consuming for the specialists. The algorithm presented in this paper permits a quasi-automatic segmentation of the unprepared colon on T2-weighted MRI scans. The segmentation algorithm is organized as a three-stage pipeline. In the first stage, a custom tubularity filter is run to detect colon candidate areas. The specialists provide a list of points along the colon trajectory, which are combined with tubularity information to calculate an estimation of the colon medial path. In the second stage, we delimit the region of interest by applying custom segmentation algorithms to detect colon neighboring regions and the fat capsule containing abdominal organs. Finally, within the reduced search space, segmentation is performed via 3D graph-cuts in a three-stage multigrid approach. Our algorithm was tested on MRI abdominal scans, including different acquisition resolutions, and its results were compared to the colon ground truth segmentations provided by the specialists. The experiments proved the accuracy, efficiency, and usability of the algorithm, while the variability of the scan resolutions contributed to demonstrate the computational scalability of the multigrid architecture. The system is fully applicable to the colon measurement clinical routine, being a substantial step towards a fully automated segmentation.
Subject(s)
Algorithms , Magnetic Resonance Imaging , Colon/diagnostic imagingABSTRACT
BACKGROUND: Some patients complain that eating lettuce, gives them gas and abdominal distention. Our aim was to determine to what extent the patients' assertion is sustained by evidence. METHODS: An in vitro study measured the amount of gas produced during the process of fermentation by a preparation of human colonic microbiota (n = 3) of predigested lettuce, as compared to beans, a high gas-releasing substrate, to meat, a low gas-releasing substrate, and to a nutrient-free negative control. A clinical study in patients complaining of abdominal distention after eating lettuce (n = 12) measured the amount of intestinal gas and the morphometric configuration of the abdominal cavity in abdominal CT scans during an episode of lettuce-induced distension as compared to basal conditions. KEY RESULTS: Gas production by microbiota fermentation of lettuce in vitro was similar to that of meat (P = .44), lower than that of beans (by 78 ± 15%; P < .001) and higher than with the nutrient-free control (by 25 ± 19%; P = .05). Patients complaining of abdominal distension after eating lettuce exhibited an increase in girth (35 ± 3 mm larger than basal; P < .001) without significant increase in colonic gas content (39 ± 4 mL increase; P = .071); abdominal distension was related to a descent of the diaphragm (by 7 ± 3 mm; P = .027) with redistribution of normal abdominal contents. CONCLUSION AND INFERENCES: Lettuce is a low gas-releasing substrate for microbiota fermentation and lettuce-induced abdominal distension is produced by an uncoordinated activity of the abdominal walls. Correction of the somatic response might be more effective than the current dietary restriction strategy.
Subject(s)
Abdominal Cavity/diagnostic imaging , Dilatation, Pathologic/etiology , Gases/metabolism , Gastrointestinal Microbiome/physiology , Lactuca/adverse effects , Abdominal Cavity/pathology , Abdominal Wall/diagnostic imaging , Abdominal Wall/physiopathology , Adult , Animals , Anthropometry , Biofeedback, Psychology , Cattle , Diagnosis, Differential , Diaphragm/diagnostic imaging , Diaphragm/physiopathology , Digestion , Dilatation, Pathologic/diagnostic imaging , Dilatation, Pathologic/therapy , Electromyography , Feces/microbiology , Female , Fermentation , Flatulence/diagnosis , Humans , In Vitro Techniques , Meat , Middle Aged , Muscle Contraction , Phaseolus , Saline Solution , Tomography, X-Ray Computed , Young AdultABSTRACT
BACKGROUND & AIMS: In patients with functional gut disorders, abdominal distension has been associated with descent of the diaphragm and protrusion of the anterior abdominal wall. We investigated mechanisms of abdominal distension in these patients. METHODS: We performed a prospective study of 45 patients (42 women, 24-71 years old) with functional intestinal disorders (27 with irritable bowel syndrome with constipation, 15 with functional bloating, and 3 with irritable bowel syndrome with alternating bowel habits) and discrete episodes of visible abdominal distension. Subjects were assessed by abdominothoracic computed tomography (n = 39) and electromyography (EMG) of the abdominothoracic wall (n = 32) during basal conditions (without abdominal distension) and during episodes of severe abdominal distension. Fifteen patients received a median of 2 sessions (range, 1-3 sessions) of EMG-guided, respiratory-targeted biofeedback treatment; 11 received 1 control session before treatment. RESULTS: Episodes of abdominal distension were associated with diaphragm contraction (19% ± 3% increase in EMG score and 12 ± 2 mm descent; P < .001 vs basal values) and intercostal contraction (14% ± 3% increase in EMG scores and 6 ± 1 mm increase in thoracic antero-posterior diameter; P < .001 vs basal values). They were also associated with increases in lung volume (501 ± 93 mL; P < .001 vs basal value) and anterior abdominal wall protrusion (32 ± 3 mm increase in girth; P < .001 vs basal). Biofeedback treatment, but not control sessions, reduced the activity of the intercostal muscles (by 19% ± 2%) and the diaphragm (by 18% ± 4%), activated the internal oblique muscles (by 52% ± 13%), and reduced girth (by 25 ± 3 mm) (P ≤ .009 vs pretreatment for all). CONCLUSIONS: In patients with functional gut disorders, abdominal distension is a behavioral response that involves activity of the abdominothoracic wall. This distension can be reduced with EMG-guided, respiratory-targeted biofeedback therapy.