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Diagnostic accuracy of DWI in patients with ovarian cancer: A meta-analysis
BACKGROUND: Diffusion weighted imaging (DWI) is recently developed for identifying different malignant tumors. In this article the diagnostic accuracy of DWI for ovarian cancer was evaluated by synthesis of published data. METHODS: A comprehensive literature search was conducted in PubMed/MEDLINE an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5428573/ https://www.ncbi.nlm.nih.gov/pubmed/28489739 http://dx.doi.org/10.1097/MD.0000000000006659 |
Sumario: | BACKGROUND: Diffusion weighted imaging (DWI) is recently developed for identifying different malignant tumors. In this article the diagnostic accuracy of DWI for ovarian cancer was evaluated by synthesis of published data. METHODS: A comprehensive literature search was conducted in PubMed/MEDLINE and Embase databases on the diagnostic performance of DWI for ovarian cancer published in English. Methodological quality was evaluated following Quality Assessment for Studies of Diagnostic Accuracy 2 (QUADAS 2) tool. We adopted the summary receiver operating characteristic (SROC) curve to assess the DWI accuracy. RESULTS: Twelve studies including 1142 lesions were analyzed in this meta-analysis to estimate the pooled Sen (sensitivity), Spe (specificity), PLR (positive likelihood ratio), NLR (negative likelihood ratio), and construct SROC (summary receiver operating characteristics) curve. The pooled Sen and Spe were 0.86 (95% confidence interval [CI], 0.83–0.89) and 0.81 (95%CI, 0.77–0.84), respectively. The pooled PLR and pooled NLR were 5.07 (95%CI, 3.15–8.16) and 0.17 (95%CI, 0.10–0.30), respectively. The pooled diagnostic odds ratio (DOR) was 35.23 (95%CI, 17.21–72.14). The area under the curve (AUC) was 0.9160. CONCLUSION: DWI had moderately excellent diagnostic ability for ovarian cancer and promised to be a helpful diagnostic tool for patients of ovarian cancer. |
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