The application value of computed tomography and magnetic resonance imaging sinography/fistulography in evaluating chronic wounds: a prospective study
| Autor: | Hanqi Wang, Tongtong Chen, Shuliang Lu, Yalin Pan, Guilu Tao, Zhihui Li, Yong Lu, Haiying Lv, Fuhua Yan, Di Zhang, Aobuliaximu Yakupu, Liuping Chen, Xian Ma |
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| Rok vydání: | 2021 |
| Předmět: |
Advanced and Specialized Nursing
Chronic wound medicine.diagnostic_test business.industry Intraclass correlation Magnetic resonance imaging Computed tomography Magnetic Resonance Imaging Confidence interval Mri image Anesthesiology and Pain Medicine Evaluation methods medicine Humans Prospective Studies medicine.symptom Tomography X-Ray Computed business Nuclear medicine Prospective cohort study |
| Zdroj: | Annals of Palliative Medicine. 10:10567-10574 |
| ISSN: | 2224-5839 2224-5820 |
| DOI: | 10.21037/apm-21-2342 |
| Popis: | BACKGROUND Chronic wounds are a worldwide health problem, with traditional imaging techniques failing in their accurate evaluation. Therefore, an effective imaging evaluation method is needed for the diagnosis and treatment or chronic wounds. This study is to investigate the application value of computed tomography (CT) and magnetic resonance imaging (MRI) sinography/fistulography in assessing the morphology and deep features of chronic wounds. METHODS We prospectively enrolled 43 chronic wounds patients who received both CT and MRI sinography/fistulography. The morphology and deep features of chronic wound on CT and MRI images were independently evaluated by 2 experienced radiologists. Kappa value and intraclass correlation coefficient (ICC) were calculated to evaluate the interobserver agreement and the consistency between CT and MRI sinography/fistulography in assessing the shape, number of branches, and involvement of body cavity and bones of chronic wounds. RESULTS There were substantial to almost perfect interobserver agreements for both CT and MRI sinography/fistulography in evaluating the morphology and deep features of chronic wounds. The consistency between CT and MRI was almost perfect for the 2 readers in evaluating the shape (reader 1, kappa value =1.000; reader 2, kappa value =0.932) and the number of branches [reader 1, ICC =0.951 (95% confidence interval: 0.909-0.973, P |
| Databáze: | OpenAIRE |
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