Assessment of Small Bowel Motility in Patients With Chronic Intestinal Pseudo-Obstruction Using Cine-MRI

Ohkubo, Hidenori; Kessoku, Takaomi; Fuyuki, Akiko; Iida, Hiroshi; Inamori, Masahiko; Fujii, Takuma; Kawamura, Harunobu; Hata, Yasuo; Manabe, Noriaki; Chiba, Tetsuhiro; Kwee, Thomas C.; Haruma, Ken; Matsuhashi, Nobuyuki; Nakajima, Atsushi; Takahara, Taro

doi:10.1038/ajg.2013.57

Cited by 68 publications

(61 citation statements)

References 30 publications

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“…The higher sensitivity of our method might be precisely related to the fact that it takes into consideration a combination of parameters reflecting wall dynamics and movement of content to classify abnormalities. External imaging of the abdomen by magnetic resonance has been recently applied for the evaluation of intestinal mechanical function and also shows promising results in the identification of indexes of abnormal small bowel function in functional patients (13,14).…”

Section: Discussionmentioning

confidence: 99%

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

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et al. 2015

American Journal of Physiology-Gastrointestinal and Liver Physi

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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 ϭ 205) and healthy subjects (n ϭ 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 Ͻ 0.001 vs. 3 healthy subjects) and clustered into hypo-and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n ϭ 38) exhibited less luminal closure sequences (41 Ϯ 2% of the recording time vs. 61 Ϯ 2%; P Ͻ 0.001) and more static sequences (38 Ϯ 3 vs. 20 Ϯ 2%; P Ͻ 0.001); in contrast, patients with hyperdynamic behavior (n ϭ 13) had an increased proportion of luminal closure sequences (73 Ϯ 4 vs. 61 Ϯ 2%; P ϭ 0.029) and more high-motion sequences (3 Ϯ 1 vs. 0.5 Ϯ 0.1%; P Ͻ 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.functional bowel disorders; capsule endoscopy; intestinal motility; computer vision analysis; machine learning WE HAVE DEVELOPED AN ORIGINAL method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. A series of features, such as phasic luminal closures, noncontractile patterns, e.g., smooth wall or open tunnel view, amount of chyme, and motion of the walls and content, are quantitatively measured. Each subject is then defined by a combination of values derived from these various dimensions. Definition of normality in this multidimensional space is performed by machine learning techniques: providing a large series of normal cases, the program draws the hyperplane that defines the normal range and, hence, automatically learns to discriminate what is normal and what is not (24). This may constitute a particularly valuable diagnostic tool on account of the enormous amount of data obtained in a large sample of healthy individuals and the automated algorithms that eliminate the piecemeal assessment of normality for each separate feature as well as the subjectivity of the data analyst, common to many physiological gut tests.

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Section: Discussionmentioning

confidence: 99%

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

Malagelada

Drozdzal

Seguí

et al. 2015

American Journal of Physiology-Gastrointestinal and Liver Physi

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“…1–4 Analysis of the data remains primarily subjective in clinical routine, but the ability to apply quantitative techniques makes this a potentially powerful methodology to explore gastrointestinal physiology in disease as well as an emerging application as a biomarker for drug efficacy. 5–7 …”

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“…By tracking bowel diameter, a characteristic curve can be produced with the number of contractions expressed per minute (CPM) to give an intuitive and broadly accepted metric for small bowel motility (SBM). 2–4,9,11,13–15 To date, several studies have reported a relationship between CPM and dysmotility in disease, either compared with a histopathological standard or “normal” reference bowel loops. 2–4,12 An array of additional metrics derived both from bowel diameter measures and more abstract processing techniques have further been implemented with varying degrees of effectiveness in disease and health.…”

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confidence: 99%

“…2–4,9,11,13–15 To date, several studies have reported a relationship between CPM and dysmotility in disease, either compared with a histopathological standard or “normal” reference bowel loops. 2–4,12 An array of additional metrics derived both from bowel diameter measures and more abstract processing techniques have further been implemented with varying degrees of effectiveness in disease and health. 2,4,5,8,10,14,16 …”

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“…2–4,12 An array of additional metrics derived both from bowel diameter measures and more abstract processing techniques have further been implemented with varying degrees of effectiveness in disease and health. 2,4,5,8,10,14,16 …”

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The challenge of segmental small bowel motility quantitation using MR enterography

Menys¹,

Plumb²,

Atkinson³

et al. 2014

BJR

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Objective:Analysis of “cine” MRI using segmental regions of interest (ROIs) has become increasingly popular for investigating bowel motility; however, variation in motility in healthy subjects both within and between scans remains poorly described.Methods:20 healthy individuals (mean age, 28 years; 14, males) underwent MR enterography to acquire dynamic motility scans in both breath hold (BH) and free breathing (FB) on 2 occasions. Motility data were quantitatively assessed by placing four ROIs per subject in different small bowel segments and applying two measures: (1) contractions per minute (CPM) and (2) Jacobian standard deviation (SD) motility score. Within-scan (between segment) variation was assessed using intraclass correlation (ICC), and repeatability was assessed using Bland–Altman limits of agreement (BA LoA).Results:Within-scan segmental variation: BH CPM and Jacobian SD metrics between the four segments demonstrated ICC R = 0.06, p = 0.100 and R = 0.20, p = 0.027 and in FB, the CPM and Jacobian SD metrics demonstrated ICC R = −0.26, p = 0.050 and R = 0.19, p = 0.030. Repeatability: BH CPM for matched segments ranged between 0 and 14 contractions with BA LoA of ±8.36 and Jacobian SD ranged between 0.09 and 0.51 with LoA of ±0.33. In FB data, CPM ranged between 0 and 10 contractions with BA LoA of ±7.25 and Jacobian SD ranged between 0.16 and 0.63 with LoA = ±0.28.Conclusion:The MRI-quantified small bowel motility in normal subjects demonstrates wide intersegmental variation and relatively poor repeatability over time.Advances in knowledge:This article presents baseline values for healthy individuals of within- and between-scan motility that are essential for understanding how this process changes in disease.

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Intestinal Obstruction and Pseudo‐obstruction

Halland

Kashyap

2016

Practical Gastroenterology and Hepatology Board Review Toolkit

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Assessment of Small Bowel Motility in Patients With Chronic Intestinal Pseudo-Obstruction Using Cine-MRI

Cited by 68 publications

References 30 publications

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

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

The challenge of segmental small bowel motility quantitation using MR enterography

Intestinal Obstruction and Pseudo‐obstruction

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