Cheng Qingqing, Huang Jiaxi, Liang Jianye, Ma Mengjie, Ye Kunlin, Shi Changzheng, Luo Liangping
Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Engineering Research Center of Medical Imaging Artificial Intelligence for Precision Diagnosis and Treatment, Guangzhou, China.
Front Oncol. 2020 Feb 12;10:93. doi: 10.3389/fonc.2020.00093. eCollection 2020.
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. 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). 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) ( = 14) as a responder showed a tendency for higher sensitivity compared with those that set pCR and near pCR together ( = 5) as a responder (0.83 vs. 0.72), and studies ( = 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 ( = 5) that assessed the response after NAC completion. 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.
新辅助化疗(NAC)常用于局部乳腺癌的术前治疗,其临床缓解率较高,6% - 25%的患者可实现病理完全缓解(pCR)。近年来,动态对比增强磁共振成像(DCE - MRI)越来越多地用于评估乳腺癌对NAC的病理反应。在本分析中,我们评估DCE - MRI在评估乳腺癌对NAC病理反应方面的诊断性能。我们在PubMed、Cochrane图书馆和Web of Science中对原始研究进行了系统检索。使用诊断准确性研究质量评估 - 2工具评估纳入研究的方法学质量。提取患者、研究和影像特征,并获得足够的数据以重建2×2列联表。使用Stata 12.0版本(StataCorp LP,美国德克萨斯州大学城)进行数据合并、异质性检验、森林图构建、Meta回归分析和敏感性分析。本Meta分析纳入了18项研究(969例乳腺癌患者)。DCE - MRI的合并敏感性和特异性分别为0.80(95%置信区间[CI]:0.70,0.88)和0.84(95%[CI]:0.79,0.88)。Meta回归分析未发现影响异质性的显著因素。敏感性分析表明,将病理完全缓解(pCR)(n = 14)设定为缓解者的研究,与将pCR和接近pCR一起(n = 5)设定为缓解者的研究相比,敏感性有更高的趋势(0.83对0.72),并且与在NAC完成后评估反应的研究(n = 5)相比,使用DCE - MRI早期预测乳腺癌病理反应的研究(n = 14)具有更高的敏感性(0.83对0.71)和相当的特异性(0.80对0.86)。我们的结果表明,DCE - MRI可被视为评估乳腺癌对NAC病理反应的重要辅助方法,并用作在NAC期间动态监测疗效的有效方法。DCE - MRI在预测乳腺癌对NAC的pCR方面也表现良好。然而,由于纳入研究的异质性,在应用我们的结果时应谨慎。