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The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease

To establish a multi-parametric regression model from four modes of ultrasound to predict the activity of Crohn's disease (CD) noninvasively. Score of 150 of the Crohn’s Disease Activity Index (CDAI) was taken as the cut-off value to divide the involved bowel segments of 51 patients into the ac...

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Autores principales: Jing, Jigang, Wu, Yuting, Zhang, Hu, Zhang, Yan, Mu, Jingxi, Luo, Yan, Zhuang, Hua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794219/
https://www.ncbi.nlm.nih.gov/pubmed/33420168
http://dx.doi.org/10.1038/s41598-020-79944-1
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author Jing, Jigang
Wu, Yuting
Zhang, Hu
Zhang, Yan
Mu, Jingxi
Luo, Yan
Zhuang, Hua
author_facet Jing, Jigang
Wu, Yuting
Zhang, Hu
Zhang, Yan
Mu, Jingxi
Luo, Yan
Zhuang, Hua
author_sort Jing, Jigang
collection PubMed
description To establish a multi-parametric regression model from four modes of ultrasound to predict the activity of Crohn's disease (CD) noninvasively. Score of 150 of the Crohn’s Disease Activity Index (CDAI) was taken as the cut-off value to divide the involved bowel segments of 51 patients into the active and inactive group. Eleven parameters from four modes of ultrasound (B-mode ultrasonography, color Doppler flow imaging, contrast-enhanced ultrasonography and shear wave elastography) were compared between the two groups to investigate the relationship between multimodal ultrasonic features and CD activity. P < 0.05 was considered statistically significant. Parameters with AUC larger than 0.5 was selected to establish the prediction model of CDAI. Totally seven ultrasound parameters (bowel wall thickness, mesenteric fat thickness, peristalsis, texture of enhancement, Limberg grade, bowel wall perforation and bowel wall stratification) were significantly different between active and inactive group. A regression model was established based on the seven parameters as followed: CDAI = 211.325 + 3.186BWT − 53.003BWS + 6.280BWP + 0.392MFT + 22.239PS + 79.012LG + 72.793TE. (R(2) = 0.72, P = 0.037). The multimodal ultrasound parametric regression model was designed to predict CDAI score invasively. The model has the potential to provide an alternative method for quantifying the CD activity.
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spelling pubmed-77942192021-01-11 The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease Jing, Jigang Wu, Yuting Zhang, Hu Zhang, Yan Mu, Jingxi Luo, Yan Zhuang, Hua Sci Rep Article To establish a multi-parametric regression model from four modes of ultrasound to predict the activity of Crohn's disease (CD) noninvasively. Score of 150 of the Crohn’s Disease Activity Index (CDAI) was taken as the cut-off value to divide the involved bowel segments of 51 patients into the active and inactive group. Eleven parameters from four modes of ultrasound (B-mode ultrasonography, color Doppler flow imaging, contrast-enhanced ultrasonography and shear wave elastography) were compared between the two groups to investigate the relationship between multimodal ultrasonic features and CD activity. P < 0.05 was considered statistically significant. Parameters with AUC larger than 0.5 was selected to establish the prediction model of CDAI. Totally seven ultrasound parameters (bowel wall thickness, mesenteric fat thickness, peristalsis, texture of enhancement, Limberg grade, bowel wall perforation and bowel wall stratification) were significantly different between active and inactive group. A regression model was established based on the seven parameters as followed: CDAI = 211.325 + 3.186BWT − 53.003BWS + 6.280BWP + 0.392MFT + 22.239PS + 79.012LG + 72.793TE. (R(2) = 0.72, P = 0.037). The multimodal ultrasound parametric regression model was designed to predict CDAI score invasively. The model has the potential to provide an alternative method for quantifying the CD activity. Nature Publishing Group UK 2021-01-08 /pmc/articles/PMC7794219/ /pubmed/33420168 http://dx.doi.org/10.1038/s41598-020-79944-1 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Jing, Jigang
Wu, Yuting
Zhang, Hu
Zhang, Yan
Mu, Jingxi
Luo, Yan
Zhuang, Hua
The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title_full The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title_fullStr The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title_full_unstemmed The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title_short The establishment of a regression model from four modes of ultrasound to predict the activity of Crohn's disease
title_sort establishment of a regression model from four modes of ultrasound to predict the activity of crohn's disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794219/
https://www.ncbi.nlm.nih.gov/pubmed/33420168
http://dx.doi.org/10.1038/s41598-020-79944-1
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