Quantitative Analysis of Small Intestinal Motility in 3D Cine-MRI Using Centerline-Aware Motion Estimation.

Crohn's disease dynamic MRI image alignment motility small intestine

Journal

Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850

Informations de publication

Date de publication:
29 Aug 2024
Historique:
revised: 31 07 2024
received: 11 04 2024
accepted: 01 08 2024
medline: 31 8 2024
pubmed: 31 8 2024
entrez: 29 8 2024
Statut: aheadofprint

Résumé

Currently available tools for noninvasive motility quantification of the small intestine are limited to dynamic 2D MRI scans, which are limited in their ability to differentiate between types of intestinal motility. To develop a method for quantification and characterization of small intestinal motility in 3D, capable of differentiating motile, non-motile and peristaltic motion patterns. Prospective. Fourteen healthy volunteers (127 small intestinal segments) and 10 patients with Crohn's disease (87 small intestinal segments). 3.0 T, 3D balanced fast field echo sequence, 1 volume per second. Using deformable image registration between subsequent volumes, the local velocity within the intestinal lumen was quantified. Average velocity and average absolute velocity along intestinal segments were used with linear classifiers to differentiate motile from non-motile intestines, as well as erratic motility from peristalsis. The mean absolute velocity of small intestinal content was compared between healthy volunteers and Crohn's disease patients, and the discriminative power of the proposed motility metrics for detecting motility and peristalsis was determined. The consensus of two observers was used as referenced standard. Student's t-test to assess differences between groups; area under the receiver operating characteristic curve (AUC) to assess discriminative ability. P < 0.001 was considered significant. A significant difference in the absolute velocity of intestinal content between Crohn's patients and healthy volunteers was observed (median [IQR] 1.06 [0.61, 1.56] mm/s vs. 1.84 [1.37, 2.43] mm/s), which was consistent with manual reference annotations of motile activity. The proposed method had a strong discriminative performance for detecting non-motile intestines (AUC 0.97) and discernible peristalsis (AUC 0.81). Analysis of 3D cine-MRI using centerline-aware motion estimation has the potential to allow noninvasive characterization of small intestinal motility and peristaltic motion in 3D. 3 TECHNICAL EFFICACY: Stage 2.

Sections du résumé

BACKGROUND BACKGROUND
Currently available tools for noninvasive motility quantification of the small intestine are limited to dynamic 2D MRI scans, which are limited in their ability to differentiate between types of intestinal motility.
PURPOSE OBJECTIVE
To develop a method for quantification and characterization of small intestinal motility in 3D, capable of differentiating motile, non-motile and peristaltic motion patterns.
STUDY TYPE METHODS
Prospective.
SUBJECTS METHODS
Fourteen healthy volunteers (127 small intestinal segments) and 10 patients with Crohn's disease (87 small intestinal segments).
FIELD STRENGTH/SEQUENCE UNASSIGNED
3.0 T, 3D balanced fast field echo sequence, 1 volume per second.
ASSESSMENT RESULTS
Using deformable image registration between subsequent volumes, the local velocity within the intestinal lumen was quantified. Average velocity and average absolute velocity along intestinal segments were used with linear classifiers to differentiate motile from non-motile intestines, as well as erratic motility from peristalsis. The mean absolute velocity of small intestinal content was compared between healthy volunteers and Crohn's disease patients, and the discriminative power of the proposed motility metrics for detecting motility and peristalsis was determined. The consensus of two observers was used as referenced standard.
STATISTICAL TESTS METHODS
Student's t-test to assess differences between groups; area under the receiver operating characteristic curve (AUC) to assess discriminative ability. P < 0.001 was considered significant.
RESULTS RESULTS
A significant difference in the absolute velocity of intestinal content between Crohn's patients and healthy volunteers was observed (median [IQR] 1.06 [0.61, 1.56] mm/s vs. 1.84 [1.37, 2.43] mm/s), which was consistent with manual reference annotations of motile activity. The proposed method had a strong discriminative performance for detecting non-motile intestines (AUC 0.97) and discernible peristalsis (AUC 0.81).
DATA CONCLUSION CONCLUSIONS
Analysis of 3D cine-MRI using centerline-aware motion estimation has the potential to allow noninvasive characterization of small intestinal motility and peristaltic motion in 3D.
EVIDENCE LEVEL METHODS
3 TECHNICAL EFFICACY: Stage 2.

Identifiants

pubmed: 39207185
doi: 10.1002/jmri.29571
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024 The Author(s). Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

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Auteurs

Louis D van Harten (LD)

Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands.

Catharina S de Jonge (CS)

Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands.

Femke Struik (F)

Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

Jaap Stoker (J)

Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Amsterdam Gastroenterology Endocrinology Metabolism, Amsterdam, The Netherlands.

Ivana Išgum (I)

Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands.
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

Classifications MeSH