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A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis
PURPOSE: To establish a clinical radiomics nomogram to differentiate Crohn’s disease (CD) from intestinal tuberculosis (ITB). PATIENTS AND METHODS: Ninety-three patients with CD and 67 patients with ITB were recruited (111 in training cohort and 49 in test cohort). The region of interest (ROI) for t...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651213/ https://www.ncbi.nlm.nih.gov/pubmed/34887674 http://dx.doi.org/10.2147/JIR.S344563 |
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author | Zhu, Chao Yu, Yongmei Wang, Shihui Wang, Xia Gao, Yankun Li, Cuiping Li, Jianying Ge, Yaqiong Wu, Xingwang |
author_facet | Zhu, Chao Yu, Yongmei Wang, Shihui Wang, Xia Gao, Yankun Li, Cuiping Li, Jianying Ge, Yaqiong Wu, Xingwang |
author_sort | Zhu, Chao |
collection | PubMed |
description | PURPOSE: To establish a clinical radiomics nomogram to differentiate Crohn’s disease (CD) from intestinal tuberculosis (ITB). PATIENTS AND METHODS: Ninety-three patients with CD and 67 patients with ITB were recruited (111 in training cohort and 49 in test cohort). The region of interest (ROI) for the lesions in the ileocecal region was delineated on computed tomography enterography and radiomics features extracted. Radiomics features were filtered by the gradient boosting decision tree (GBDT), and a radiomics score was calculated by using the radiomics signature-based formula. We constructed a clinical radiomics model and nomogram combining clinical factors and radiomics score through multivariate logistic regression analysis, and the internal validation was undertaken by ten-fold cross validation. Analyses of receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the prediction performance. DeLong test was applied to evaluate the performance of the clinical, radiomics and combined model. RESULTS: The clinical radiomics nomogram, which was based on the 9 radiomics signature and two clinical factors, indicated that the clinical radiomics model had an area under the ROC curve (AUC) value of 0.96 (95% confidence interval [CI]: 0.93–0.99) in the training cohort and 0.93 (95% CI: 0.86–1.00) in validation cohort. The clinical radiomics model was superior to the clinical model and radiomics model, and the difference was significant (P = 0.006, 0.004) in the training cohort. DCA confirmed the clinical utility of clinical radiomics nomogram. CONCLUSION: CTE-based radiomics model has a good performance in distinguishing CD from ITB. A nomogram constructed by combining radiomics and clinical factors can help clinicians accurately diagnose and select appropriate treatment strategies between CD and ITB. |
format | Online Article Text |
id | pubmed-8651213 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-86512132021-12-08 A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis Zhu, Chao Yu, Yongmei Wang, Shihui Wang, Xia Gao, Yankun Li, Cuiping Li, Jianying Ge, Yaqiong Wu, Xingwang J Inflamm Res Original Research PURPOSE: To establish a clinical radiomics nomogram to differentiate Crohn’s disease (CD) from intestinal tuberculosis (ITB). PATIENTS AND METHODS: Ninety-three patients with CD and 67 patients with ITB were recruited (111 in training cohort and 49 in test cohort). The region of interest (ROI) for the lesions in the ileocecal region was delineated on computed tomography enterography and radiomics features extracted. Radiomics features were filtered by the gradient boosting decision tree (GBDT), and a radiomics score was calculated by using the radiomics signature-based formula. We constructed a clinical radiomics model and nomogram combining clinical factors and radiomics score through multivariate logistic regression analysis, and the internal validation was undertaken by ten-fold cross validation. Analyses of receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the prediction performance. DeLong test was applied to evaluate the performance of the clinical, radiomics and combined model. RESULTS: The clinical radiomics nomogram, which was based on the 9 radiomics signature and two clinical factors, indicated that the clinical radiomics model had an area under the ROC curve (AUC) value of 0.96 (95% confidence interval [CI]: 0.93–0.99) in the training cohort and 0.93 (95% CI: 0.86–1.00) in validation cohort. The clinical radiomics model was superior to the clinical model and radiomics model, and the difference was significant (P = 0.006, 0.004) in the training cohort. DCA confirmed the clinical utility of clinical radiomics nomogram. CONCLUSION: CTE-based radiomics model has a good performance in distinguishing CD from ITB. A nomogram constructed by combining radiomics and clinical factors can help clinicians accurately diagnose and select appropriate treatment strategies between CD and ITB. Dove 2021-12-03 /pmc/articles/PMC8651213/ /pubmed/34887674 http://dx.doi.org/10.2147/JIR.S344563 Text en © 2021 Zhu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Zhu, Chao Yu, Yongmei Wang, Shihui Wang, Xia Gao, Yankun Li, Cuiping Li, Jianying Ge, Yaqiong Wu, Xingwang A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title | A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title_full | A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title_fullStr | A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title_full_unstemmed | A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title_short | A Novel Clinical Radiomics Nomogram to Identify Crohn’s Disease from Intestinal Tuberculosis |
title_sort | novel clinical radiomics nomogram to identify crohn’s disease from intestinal tuberculosis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651213/ https://www.ncbi.nlm.nih.gov/pubmed/34887674 http://dx.doi.org/10.2147/JIR.S344563 |
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