A Probabilistic Method for Estimation of Bowel Wall Thickness in MR Colonography
MRI has recently been applied as a tool to quantitatively evaluate the response to therapy in patients with Crohn's disease, and is the preferred choice for repeated imaging. Bowel wall thickness on MRI is an important biomarker of underlying inflammatory activity, being abnormally increased in...
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Published in | PloS one Vol. 12; no. 1; p. e0168317 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Public Library of Science
10.01.2017
Public Library of Science (PLoS) |
Subjects | |
Online Access | Get full text |
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Summary: | MRI has recently been applied as a tool to quantitatively evaluate the response to therapy in patients with Crohn's disease, and is the preferred choice for repeated imaging. Bowel wall thickness on MRI is an important biomarker of underlying inflammatory activity, being abnormally increased in the acute phase and reducing in response to successful therapy; however, a poor level of interobserver agreement of measured thickness is reported and therefore a system for accurate, robust and reproducible measurements is desirable. We propose a novel method for estimating bowel wall-thickness to improve the poor interobserver agreement of the manual procedure. We show that the variability of wall thickness measurement between the algorithm and observer measurements (0.25mm ± 0.81mm) has differences which are similar to observer variability (0.16mm ± 0.64mm). |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Alex Menys is CEO of Motilent Limited a medical imaging analysis company. Conceptualization: TH. Data curation: AM AJ GB. Formal analysis: TH AM. Funding acquisition: DH ST SH SP. Investigation: AM. Methodology: TH. Project administration: AM. Resources: AM ST. Software: TH. Supervision: DH. Validation: TH AM. Visualization: TH. Writing – original draft: TH. Writing – review & editing: AM DA SH DH ST. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0168317 |