Literature DB >> 32741199

Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging for malignant ovarian tumors: a systematic review and meta-analysis.

Mingxiang Wei1, Fan Bo1, Hui Cao1, Wei Zhou1, Wenli Shan1, Genji Bai1.   

Abstract

BACKGROUND: Accurate preoperative diagnosis of malignant ovarian tumors (MOTs) is particularly important for selecting the optimal treatment strategy and avoiding overtreatment.
PURPOSE: To evaluate the diagnostic efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for MOTs.
MATERIAL AND METHODS: A systematic search was performed in PubMed, Embase, the Cochrane Library, and Web of Science databases to find relevant original articles up to October 2019. The included studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Studies on the diagnosis of MOTs with quantitative or semi-quantitative DCE-MRI were analyzed separately. The bivariate random-effects model was used to assess the diagnostic authenticity. Meta-regression analyses were performed to analyze the potential heterogeneity.
RESULTS: For semi-quantitative DCE-MRI, the pooled sensitivity, specificity, positive likelihood ratio (LR), negative LR, diagnostic odds ratio (DOR), and the area under the summary receiver operating characteristic curves (AUC) were 85% (95% confidence interval [CI] 0.75-0.92), 85% (95% CI 0.77-0.91), 5.8 (95% CI 3.8-8.8), 0.17 (95% CI 0.10-0.30), 33 (95% CI 18-61), and 0.92 (95% CI 0.89-0.94), respectively. For quantitative DCE-MRI, the pooled sensitivity, specificity, positive LR, negative LR, DOR, and AUC were 88% (95% CI 0.65-0.96), 93% (95% CI 0.78-0.98), 12.3 (95% CI 3.4-43.9), 0.13 (95% CI 0.04-0.45), 91 (95% CI 10-857), and 0.96 (95% CI 0.94-0.98), respectively.
CONCLUSION: DCE-MRI has great diagnostic value for MOTs. Semi-quantitative DCE-MRI may be a relatively mature approach; however, quantitative DCE-MRI appears to be more promising than semi-quantitative DCE-MRI.

Entities:  

Keywords:  Dynamic contrast-enhanced magnetic resonance imaging; diagnosis; meta-analysis; ovary

Mesh:

Substances:

Year:  2020        PMID: 32741199     DOI: 10.1177/0284185120944916

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  4 in total

1.  Nomograms of Combining MRI Multisequences Radiomics and Clinical Factors for Differentiating High-Grade From Low-Grade Serous Ovarian Carcinoma.

Authors:  Cuiping Li; Hongfei Wang; Yulan Chen; Chao Zhu; Yankun Gao; Xia Wang; Jiangning Dong; Xingwang Wu
Journal:  Front Oncol       Date:  2022-06-07       Impact factor: 5.738

2.  A Nomogram Combining MRI Multisequence Radiomics and Clinical Factors for Predicting Recurrence of High-Grade Serous Ovarian Carcinoma.

Authors:  Cuiping Li; Hongfei Wang; Yulan Chen; Mengshi Fang; Chao Zhu; Yankun Gao; Jianying Li; Jiangning Dong; Xingwang Wu
Journal:  J Oncol       Date:  2022-05-04       Impact factor: 4.501

3.  Diagnostic Value of Two-Dimensional Transvaginal Ultrasound Combined with Contrast-Enhanced Ultrasound in Ovarian Cancer.

Authors:  Rong Hu; Gulina Shahai; Hui Liu; Yuling Feng; Hong Xiang
Journal:  Front Surg       Date:  2022-05-27

Review 4.  Serous borderline ovarian tumours: an extensive review on MR imaging features.

Authors:  Hilal Sahin; Asli Irmak Akdogan; Janette Smith; Jeries Paolo Zawaideh; Helen Addley
Journal:  Br J Radiol       Date:  2021-07-08       Impact factor: 3.629

  4 in total

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