Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis
Abstract. Background:. It is crucial to differentiate accurately glioma recurrence and pseudoprogression which have entirely different prognosis and require different treatment strategies. This study aimed to assess the diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging (DCE...
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2021
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oai:doaj.org-article:78225579ec494f2f96b8f0173df90f032021-11-25T07:57:19ZDiagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis0366-69992542-564110.1097/CM9.0000000000001445https://doaj.org/article/78225579ec494f2f96b8f0173df90f032021-11-01T00:00:00Zhttp://journals.lww.com/10.1097/CM9.0000000000001445https://doaj.org/toc/0366-6999https://doaj.org/toc/2542-5641Abstract. Background:. It is crucial to differentiate accurately glioma recurrence and pseudoprogression which have entirely different prognosis and require different treatment strategies. This study aimed to assess the diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for distinguishing glioma recurrence and pseudoprogression. Methods:. According to particular criteria of inclusion and exclusion, related studies up to May 1, 2019, were thoroughly searched from several databases including PubMed, Embase, Cochrane Library, and Chinese biomedical databases. The quality assessment of diagnostic accuracy studies was applied to evaluate the quality of the included studies. By using the “mada” package in R, the heterogeneity, overall sensitivity, specificity, and diagnostic odds ratio were calculated. Moreover, funnel plots were used to visualize and estimate the publication bias in this study. The area under the summary receiver operating characteristic (SROC) curve was computed to display the diagnostic efficiency of DCE-MRI. Results:. In the present meta-analysis, a total of 11 studies covering 616 patients were included. The results showed that the pooled sensitivity, specificity, and diagnostic odds ratio were 0.792 (95% confidence interval [CI] 0.707–0.857), 0.779 (95% CI 0.715–0.832), and 16.219 (97.5% CI 9.123–28.833), respectively. The value of the area under the SROC curve was 0.846. In addition, the SROC curve showed high sensitivities (>0.6) and low false positive rates (<0.5) from most of the included studies, which suggest that the results of our study were reliable. Furthermore, the funnel plot suggested the existence of publication bias. Conclusions:. While the DCE-MRI is not the perfect diagnostic tool for distinguishing glioma recurrence and pseudoprogression, it was capable of improving diagnostic accuracy. Hence, further investigations combining DCE-MRI with other imaging modalities are required to establish an efficient diagnostic method for glioma patients.Jun QiuZhen-Chao TaoKe-Xue DengPeng WangChuan-Yu ChenFang XiaoYi LuoShu-Ya YuanHao ChenHuan HuangXin ChenYuan-Yuan JiWolters KluwerarticleMedicineRENChinese Medical Journal, Vol 134, Iss 21, Pp 2535-2543 (2021) |
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DOAJ |
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Medicine R Jun Qiu Zhen-Chao Tao Ke-Xue Deng Peng Wang Chuan-Yu Chen Fang Xiao Yi Luo Shu-Ya Yuan Hao Chen Huan Huang Xin Chen Yuan-Yuan Ji Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| description |
Abstract. Background:. It is crucial to differentiate accurately glioma recurrence and pseudoprogression which have entirely different prognosis and require different treatment strategies. This study aimed to assess the diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for distinguishing glioma recurrence and pseudoprogression.
Methods:. According to particular criteria of inclusion and exclusion, related studies up to May 1, 2019, were thoroughly searched from several databases including PubMed, Embase, Cochrane Library, and Chinese biomedical databases. The quality assessment of diagnostic accuracy studies was applied to evaluate the quality of the included studies. By using the “mada” package in R, the heterogeneity, overall sensitivity, specificity, and diagnostic odds ratio were calculated. Moreover, funnel plots were used to visualize and estimate the publication bias in this study. The area under the summary receiver operating characteristic (SROC) curve was computed to display the diagnostic efficiency of DCE-MRI.
Results:. In the present meta-analysis, a total of 11 studies covering 616 patients were included. The results showed that the pooled sensitivity, specificity, and diagnostic odds ratio were 0.792 (95% confidence interval [CI] 0.707–0.857), 0.779 (95% CI 0.715–0.832), and 16.219 (97.5% CI 9.123–28.833), respectively. The value of the area under the SROC curve was 0.846. In addition, the SROC curve showed high sensitivities (>0.6) and low false positive rates (<0.5) from most of the included studies, which suggest that the results of our study were reliable. Furthermore, the funnel plot suggested the existence of publication bias.
Conclusions:. While the DCE-MRI is not the perfect diagnostic tool for distinguishing glioma recurrence and pseudoprogression, it was capable of improving diagnostic accuracy. Hence, further investigations combining DCE-MRI with other imaging modalities are required to establish an efficient diagnostic method for glioma patients. |
| format |
article |
| author |
Jun Qiu Zhen-Chao Tao Ke-Xue Deng Peng Wang Chuan-Yu Chen Fang Xiao Yi Luo Shu-Ya Yuan Hao Chen Huan Huang Xin Chen Yuan-Yuan Ji |
| author_facet |
Jun Qiu Zhen-Chao Tao Ke-Xue Deng Peng Wang Chuan-Yu Chen Fang Xiao Yi Luo Shu-Ya Yuan Hao Chen Huan Huang Xin Chen Yuan-Yuan Ji |
| author_sort |
Jun Qiu |
| title |
Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| title_short |
Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| title_full |
Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| title_fullStr |
Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| title_full_unstemmed |
Diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| title_sort |
diagnostic accuracy of dynamic contrast-enhanced magnetic resonance imaging for distinguishing pseudoprogression from glioma recurrence: a meta-analysis |
| publisher |
Wolters Kluwer |
| publishDate |
2021 |
| url |
https://doaj.org/article/78225579ec494f2f96b8f0173df90f03 |
| work_keys_str_mv |
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