The Diagnostic Performance of DCE-MRI in Evaluating the Pathological Response to Neoadjuvant Chemotherapy in Breast Cancer: A Meta-Analysis

Abstract

Background: Neoadjuvant chemotherapy (NAC) is commonly utilized in preoperative treatment for local breast cancer, and it gives high clinical response rates and can result in pathologic complete response (pCR) in 6-25% of patients. In recent years, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been increasingly used to assess the pathological response of breast cancer to NAC. In present analysis, we assess the diagnostic performance of DCE-MRI in evaluating the pathological response of breast cancer to NAC. Materials and Methods: A systematic search in PubMed, the Cochrane Library, and Web of Science for original studies was performed. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to assess the methodological quality of the included studies. Patient, study, and imaging characteristics were extracted, and sufficient data to reconstruct 2 × 2 tables were obtained. Data pooling, heterogeneity testing, forest plot construction, meta-regression analysis and sensitivity analysis were performed using Stata version 12.0 (StataCorp LP, College Station, TX). Results: Eighteen studies (969 patients with breast cancer) were included in the present meta-analysis. The pooled sensitivity and specificity of DCE-MRI were 0.80 (95% confidence interval [CI]: 0.70, 0.88) and 0.84 (95% [CI]: 0.79, 0.88), respectively. Meta-regression analysis found no significant factors affecting heterogeneity. Sensitivity analysis showed that studies that set pathological complete response (pCR) (n = 14) as a responder showed a tendency for higher sensitivity compared with those that set pCR and near pCR together (n = 5) as a responder (0.83 vs. 0.72), and studies (n = 14) that used DCE-MRI to early predict the pathological response of breast cancer had a higher sensitivity (0.83 vs. 0.71) and equivalent specificity (0.80 vs. 0.86) compared to studies (n = 5) that assessed the response after NAC completion. Conclusion: Our results indicated that DCE-MRI could be considered an important auxiliary method for evaluating the pathological response of breast cancer to NAC and used as an effective method for dynamically monitoring the efficacy during NAC. DCE-MRI also performed well in predicting the pCR of breast cancer to NAC. However, due to the heterogeneity of the included studies, caution should be exercised in applying our results.

Keywords: breast cancer; dynamic contrast-enhanced magnetic resonance imaging; meta-analysis; neoadjuvant chemotherapy; pathological response.

Figure 1

Flow diagram of study selection for meta-analysis.

Figure 2

Grouped bar charts showing risk of bias (Left) and concerns for applicability (Right) for each included study using QUADAS-2.

Figure 3

Hierarchical summary receiver operating characteristic (SROC) curve of the diagnostic performance of DCE-MRI for evaluation of the pathological response of breast cancer to neoadjuvant chemotherapy. Each solid circle represents one included study. Values in bracketsare 95% CIs. AUC, area under the curve.

Figure 4

Hierarchical summary receiver operating characteristic (SROC) curve of the diagnostic performance of DCE-MRI for prediction of the pathological complete response (pCR) of breast cancer to neoadjuvant chemotherapy. Each solid circle represents one included study. Values in bracketsare 95% CIs. AUC, area under the curve.

Figure 5

Forest plots of the sensitivity and specificity of DCE-MRI for evaluation of the pathological response of breast cancer to neoadjuvant chemotherapy. I² > 50% indicated substantial heterogeneity in the diagnostic parameters across studies.

Figure 6

Forest plots of the sensitivity and specificity of DCE-MRI for prediction of the pathological complete response (pCR) of breast cancer to neoadjuvant chemotherapy. I² > 50% indicated substantial heterogeneity in the diagnostic parameters across studies.

Figure 7

Deeks funnel plot shows the likelihood of publication bias is low with a P value of 0.85. ESS, effective sample size.

Figure 8

Fagan plot of the DCE-MRI test for evaluation of the pathological response of breast cancer to neoadjuvant chemotherapy.