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Enhancing the Differentiation between Intestinal Behçet’s Disease and Crohn’s Disease through Quantitative Computed Tomography Analysis
Behçet’s disease (BD) behaves similarly to Crohn’s disease (CD) when the bowel is involved. Computed tomography enterography (CTE) can accurately show intestinal involvement and obtain body composition data. The objective of this study was to evaluate whether CTE could improve the ability to disting...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10604024/ https://www.ncbi.nlm.nih.gov/pubmed/37892941 http://dx.doi.org/10.3390/bioengineering10101211 |
Sumario: | Behçet’s disease (BD) behaves similarly to Crohn’s disease (CD) when the bowel is involved. Computed tomography enterography (CTE) can accurately show intestinal involvement and obtain body composition data. The objective of this study was to evaluate whether CTE could improve the ability to distinguish between intestinal BD and CD. This study evaluated clinical, laboratory, endoscopic, and CTE features on first admission. Body composition analysis was based on the CTE arterial phase. The middle layers of the L1–L5 vertebral body were selected. The indicators assessed included: the area ratio of visceral adipose tissue (VAT)/subcutaneous adipose tissue (SAT) (VSR) in each layer, the total volume ratio of VAT/SAT, the quartile of VAT attenuation in each layer and the coefficient of variation (CV) of the VAT area for each patient was also calculated. Two models were developed based on the above indicators: one was a traditional model (age, gender, ulcer distribution) and the other was a comprehensive model (age, gender, ulcer distribution, proximal ileum involvement, asymmetrical thickening of bowel wall, intestinal stenosis, VSR(L4), and CV). The areas under the receiver operating characteristic (ROC) curve of the traditional (sensitivity: 80.0%, specificity: 81.0%) and comprehensive (sensitivity: 95.0%, specificity: 87.2%) models were 0.862 and 0.941, respectively (p = 0.005). |
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