Systematic review and meta-analysis of imaging differential diagnosis of benign and malignant ovarian tumors

Abstract

Background: With the increasing incidence of gynecological ovarian tumors, the differential diagnosis of benign and malignant ovarian tumors is of great significance for subsequent treatment. Currently, ovarian examinations commonly use computed tomography (CT) or magnetic resonance imaging (MRI). This study sought to compare the value of CT and MRI in differentiating between benign and malignant ovarian tumors.

Methods: The PubMed, Cochrane Central Register of Controlled Trials, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang, and Weipu databases were searched for published articles using the following terms "CT" or "Computed Tomography" or "MRI" or "Magnetic Resonance imaging" and "ovarian cancer" or "ovarian tumor" or "ovarian neoplasm" or "adnexal mass" or "adnexal lesion". The articles were screened and the data were extracted based on the inclusion and exclusion criteria. The Quality Assessment of Diagnostic Accuracy Studies-2 recommended by the Cochrane Collaboration was used to assess the methodological quality of the included studies, and the network meta-analysis was performed by Stata 15.0.

Results: The results showed that the overall sensitivity and specificity of CT were 0.79 [95% confidence intervals (CI): 0.70-0.87] and 0.87 (95% CI: 0.80-0.92), respectively. The overall sensitivity and specificity of MRI were 0.94 (95% CI: 0.91-0.95) and 0.91 (95% CI: 0.90-0.93), respectively. The area under the curve of the CT and MRI summary receiver operating characteristics were 0.9016 and 0.9764, respectively. The positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CT were 5.26 (95% CI: 2.78-9.93), 0.26 (95% CI: 0.13-0.50), and 22.19 (95% CI: 7.54-65.30), respectively. The positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of MRI were 8.69 (95% CI: 5.06-14.92), 0.07 (95% CI: 0.04-0.13), and 146.19 (95% CI: 68.88-310.24), respectively.

Conclusions: Compared to CT, MRI has a stronger ability to differentiate between benign and malignant ovarian tumors. It's a promising non-radiological imaging technique and a more favorable choice for patients with ovarian tumors. However, in the future, large-sample, multi-center prospective studies need to be conducted to compare the performance of MRI and CT in distinguishing between benign and malignant ovarian tumors.

Keywords: Ovarian tumor; computed tomography (CT); differential diagnosis; magnetic resonance imaging (MRI).

Figure 1

Flow diagram of the search, screening, and inclusion process.

Figure 2

Literature quality evaluation details.

Figure 3

Sensitivity of studies: forest plot of sensitivities of 4 studies. Statistical method: inverse variance of the random-effects model. CI, confidence interval.

Figure 4

Specificity of studies: forest plot of specificities of 4 studies. Statistical method: inverse variance of the random-effects model. CI, confidence interval.

Figure 5

SROC curve for individual studies on the CT differential diagnosis of benign and malignant ovarian tumors. SROC, summary receiving operation characteristic; AUC, area under the curve; SE, standard error; CT: computed tomography.

Figure 6

Forest plot of positive LR. Comparison of positive LR between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. LR, Likelihood ratio; CI, confidence interval.

Figure 7

Forest plot of negative LR. Comparison of negative LR between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. LR, Likelihood ratio; CI, confidence interval.

Figure 8

Forest plot of diagnostic odds ratio. Comparison of diagnostic odds ratio between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. OR, odds ratio; CI, confidence interval.

Figure 9

Sensitivity of studies: forest plot of sensitivities of 7 studies. Statistical method: inverse variance of the random-effects model. CI, confidence interval.

Figure 10

Specificity of studies: forest plot of specificities of 7 studies. Statistical method: inverse variance of the random-effects model. CI, confidence interval.

Figure 11

SROC curve for individual studies on MRI differential diagnosis of benign and malignant ovarian tumors. SROC, summary receiving operation characteristic; AUC, area under the curve; SE, standard error.

Figure 12

Forest plot of positive LR. Comparison of positive LR between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. LR, Likelihood ratio; CI, confidence interval.

Figure 13

Forest plot of negative LR. Comparison of negative LR between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. LR, Likelihood ratio; CI, confidence interval.

Figure 14

Forest plot of diagnostic odds ratio. Comparison of diagnostic odds ratio between the benign group and the malignant group. Statistical method: inverse variance of the random-effects model. OR, odds ratio; CI, confidence interval.

Figure 15

The intensity and distribution of the quality risk of the articles included in the study.