Application of 1.5 T magnetic resonance imaging in endometrial cancer

Predictive value of T2-weighted imaging and dynamic contrast-enhanced MRI for assessing cervical invasion in patients with endometrial cancer: a meta-analysis

PURPOSE

To obtain the diagnostic accuracy of T2-weighted imaging (T2WI), and dynamic contrast-enhanced MRI (DCE-MRI) in the preoperative assessment of cervical invasion in patients with endometrial cancer (EC).

METHODS

Databases including PubMed, Embase, Cochrane Library, Web of Science, and Clinical Trials were searched for relevant articles published from January 2000 to August 2020. Pooled estimation data were obtained by statistical analysis.

RESULTS

In total, 24 articles were included. For assessing cervical invasion of EC, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for T2WI were 0.70 (0.61-0.77), 0.92 (0.89-0.94), 8.7 (6.5-11.6), 0.33 (0.25-0.43), 26 (17-41), and 0.92 (0.89-0.94), respectively. For DCE-MRI, the pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.75 (0.60-0.85), 0.95 (0.89-0.98), 14.7 (6.6-32.9), 0.27 (0.16-0.44), 55 (18-165), and 0.92 (0.89-0.94), respectively; for T2WI combined with DCE-MRI, they were 0.58 (0.41-0.73), 0.98 (0.95-0.99), 28.1 (12.8-62.1), 0.43 (0.30-0.63), 65 (29-146), and 0.94 (0.91-0.96), respectively.

CONCLUSIONS

DCE-MRI demonstrated higher diagnostic performance than T2WI in the prediction of cervical invasion in patients with EC. T2WI combined with DCE-MRI improved the pooled specificity, PLR, DOR, and AUC compared to T2WI alone or DCE-MRI alone.

Diagnostic Accuracy of MRI for Detecting Cervical Invasion in Patients with Endometrial Carcinoma: A Meta-Analysis

Objectives: To evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in the preoperative assessment of cervical invasion and to analyse the influence of different imaging protocols in patients with endometrial carcinoma. Methods: An extensive search of articles about MRI for assessing cervical invasion in patients with endometrial carcinoma was performed on PubMed, Embase, Web of Science, Cochrane Library, and Clinical Trials from January 2000 to July 2020. Two reviewers independently evaluated the methodological quality of each study by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Diagnostic accuracy results and additional useful information were extracted. The pooled estimation data was obtained by statistical analysis. Results: A total of 42 eligible studies were included in the meta-analysis. Significant evidence of heterogeneity was found for detecting cervical invasion (I2 = 74.1%, P = 0.00 for sensitivity and I2 = 56.2%, P = 0.00 for specificity). The pooled sensitivity and specificity of MRI were 0.58 and 0.95 respectively. The use of higher field strength (3.0 T) demonstrated higher pooled sensitivity (0.74). Using diffusion weighted imaging (DWI) alone presented higher pooled sensitivity (0.86) than using other sequences. The studies that used dynamic contrast-enhanced MRI (DCE-MRI) alone showed higher sensitivity (0.80) and specificity (0.96) than those that used T2-weighted imaging (T2WI) alone. Conclusions: MRI shows high specificity for detecting cervical infiltration in endometrial carcinoma. Using DWI or a 3.0-T device may improve the pooled sensitivity. DCE-MRI demonstrates higher pooled sensitivity and specificity than T2WI.

Prediction of lymph node and distant metastasis in patients with endometrial carcinoma: a new model based on demographics, biochemical factors, and tumor histology

OBJECTIVE

To develop a model that might predict the probability of lymph node and distant metastasis (stages IIIC-IV) in endometrial carcinoma.

METHODS

We studied 774 patients with endometrial carcinoma treated in a single institution. Demographic factors, biochemical factors and preoperative tumor characteristics, identified as potential risk factors for advanced carcinoma in unadjusted analyses, were used to create a logistic regression model with lymph node and distant metastasis as the dependent variable. Statistically significant odds ratios in the regression model were rounded to the nearest whole number. These rounded values were the estimated weights for each factor that were summed to generate a score that might predict the probability of stage IIIC-IV carcinoma.

RESULTS

Biochemical factors and preoperative tumor characteristics predicted lymph node and distant metastasis in the regression model, whereas demographic factors were without effect. The score combining weighted risk factors was: (2 × leukocytosis)+(3 × thrombocytosis)+(7 × elevated CA125)+(4 × high-risk histology). The area under curve (AUC) for this total score was 0.823, with 71.6% sensitivity, 75.2% specificity, 25.9% positive predictive value, and 95.7% negative predictive value, using 6 as cut-point. After excluding stage IV carcinomas from the dataset, the AUC was 0.813 for the total score in predicting nodal involvement (P=0.82 vs. total score in predicting stage IIIC-IV carcinomas in the complete dataset).

CONCLUSIONS

Based on the high negative predictive value, this prediction model could be applied for identifying patients who may not benefit from lymphadenectomy for endometrial carcinoma staging.