==== Front Thorac CancerThorac Cancer10.1111/(ISSN)1759-7714TCAThoracic Cancer1759-77061759-7714John Wiley & Sons Australia, Ltd Melbourne 10.1111/1759-7714.12774TCA12774Original ArticleOriginal ArticlesAxillary lymph node metastasis detection by magnetic resonance imaging in patients with breast cancer: A meta‐analysis MRI to detect axillary LN metastasisP. Zhou et al.Zhou Peng 1 Wei Yongqing 2 Chen Guoyue 1 Guo Lei 1 Yan Deyue 1 Wang Ying 18953116569@163.com 1 1 Department of Radiology Jinan Central Hospital Affiliated to Shan Dong University Jinan China 2 Department of Obstetrics Jinan Central Hospital Affiliated to Shan Dong University Jinan China * Correspondence Ying Wang, Department of Radiology, Jinan Central Hospital Affiliated to Shan Dong University, 105 Jie Fang Road, Jinan City, Shandong, Province 250000, China. Tel: +86 133 7058 2590 Email: 18953116569@163.com 06 6 2018 8 2018 9 8 10.1111/tca.2018.9.issue-8989 996 01 4 2018 02 5 2018 02 5 2018 © 2018 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, LtdThis is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.Background The study was conducted to evaluate the diagnostic performance of magnetic resonance imaging (MRI) for the detection of axillary lymph node metastasis in patients with breast cancer. Methods PubMed, Medline, Web of Science, Cochrane Embase, Chinese Biomedical Literature, and China National Knowledge Infrastructure databases were searched for open published studies relevant to the use of MRI for the detection of axillary lymph node metastasis in breast cancer patients. The pooled diagnostic sensitivity, specificity, and the symmetric receiver operating characteristic (SROC) curve was calculated by combining the individual data extracted from 26 included studies. Results The pooled diagnostic sensitivity and specificity of MRI to detect axillary lymph node metastasis in patients with breast cancer were 0.77 (95% confidence interval [CI] 0.75–0.80) and 0.90 (95% CI 0.89–0.91), respectively. The pooled positive and negative likelihood ratios were 7.67 (95% CI 5.09–11.53) and 0.23 (95% CI 0.17–0.32), respectively, by random effect method. The area under the SROC curve was 0.93 for MRI to detect axillary lymph node metastasis in breast cancer patients. Conclusion With high sensitivity, specificity, and area under the curve, MRI is an effective method to differentiate metastatic axillary lymph node in breast cancer patients, which can provide useful information for surgical procedure selection. Axillary lymph node metastasisbreast cancerdiagnosismeta‐analysis source-schema-version-number2.0component-idtca12774cover-dateAugust 2018details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_NLMPMC version:version=5.4.4 mode:remove_FC converted:01.08.2018 ==== Body Introduction Statistical studies of cancer have revealed that breast cancer is one of the most common malignant carcinomas diagnosed and the seconding leading cause of cancer related‐death in women.1, 2, 3 Axillary lymph node metastasis is common in breast cancer patients, which also affects the treatment modality and surgical procedure.4 Axillary lymph node status of patients with breast cancer is usually assessed by sentinel lymph node biopsy (SLNB), core needle biopsy (CNB), or fine needle aspiration cytology (FNAC). However, these procedures are mini‐invasive and potentially lead to implantation metastasis. Magnetic resonance imaging (MRI), with high resolution of different tissues, is widely used to diagnose many types of cancers and also affects treatment modality. Previously studies have evaluated its performance for evaluating the axillary lymph node status of patients with breast cancer. However, because of the small sample sizes of previous studies, statistical research is limited. In our present study, we searched open published studies relevant to MRI for the detection of axillary lymph node metastasis in patients with breast cancer and conducted a meta‐analysis to further evaluate diagnostic performance. Methods Publication searching PubMed, Medline, Web of Science, Cochrane Embase, Chinese Biomedical Literature, and China National Knowledge Infrastructure databases were searched for open published studies relevant to the use of MRI to detect axillary lymph node metastasis in patients with breast cancer. The search procedure is demonstrated in Figure 1. The terms “breast cancer” OR “breast carcinoma” OR “breast neoplasm” And “axillary lymph node” And “MRI” OR “magnetic resonance imaging” OR “MR” were used. Figure 1 Search procedure. Study inclusion and exclusion Two reviewers drew up the inclusion and exclusion criteria and crosschecked the data. The inclusion criteria were: (i) prospective or retrospective diagnostic studies; (ii) studies relevant to the evaluation of MRI to detect axillary lymph node metastasis in patients with breast cancer; (iii) the axillary lymph node metastasis was confirmed by pathological examination; and (iv) the number of true positive (TP), false positive (FP), false negative (FN), and true negative (TN) results could be extracted from each individual study. The exclusion criteria were: (i) duplicate publications or data; (ii) literature review of case reports; (iii) malignant carcinoma other than breast cancer; and (iv) diagnostic data could not be extracted from individual studies. Initially, 268 relevant studies were identified. Nineteen duplicated publications or data were excluded. After reading the title and abstract, 204 studies were excluded. After review of the full text, a further 19 studies were excluded. Twenty‐six open published studies were finally included in the meta‐analysis (Fig 1). The main features of the included 26 studies are listed in Table 1. Table 1 General characteristics of the included publications First author Year Country Study type Reference standard Lymph node Age (year) TP FP FN TN Chen5 2014 China NR ALND/CNB 154 21–82 70 8 17 59 Meng6 2013 China NR SLNB 35 35–61 10 0 1 24 Wang7 2013 China Retrospective ALND/SLNB 136 21–77 55 11 8 62 Xie8 2014 China Retrospective ALND/SLNB 193 21–73 60 9 20 104 Xu9 2004 China NR ALND 17 34–70 9 2 2 4 Yin10 2013 China NR ALND 268 NR 63 52 15 148 Du11 2017 China NR ALND 229 NR 91 17 11 110 Harada12 2007 Japan Prospective ALND 506 36–77 42 73 23 368 Kimura13 2009 Japan Prospective ALND 10 35–79 2 0 0 8 Kvistad14 2000 Norway NR ALND 65 38–78 6 1 18 40 Memarsadeghi15 2006 Australia Prospective ALND 22 40–79 6 23 5 99 Michel16 2002 Switzerland Prospective ALND 18 22–76 25 9 5 243 Mumtaz17 1997 UK NR ALND 75 29–80 21 5 5 64 García Fernández18 2011 Spain Prospective ALND 105 52.5 14 3 25 63 Hwang19 2013 Korea Prospective ALND/SLNB 349 25–79 44 29 48 228 Javid20 2010 USA Prospective ALND 47 NR 24 2 4 17 Chung21 2013 USA Prospective ALND 110 NR 68 7 0 35 Fornasa22 2012 Italy Prospective ALND 43 NR 18 2 1 22 Rautiainen23 2015 Finland Prospective ALND 32 28–82 22 0 3 7 He24 2012 China Retrospective ALND 1242 NR 108 26 34 1074 Kamitani25 2013 Japan Retrospective ALND 110 25–81 24 47 2 37 Kim26 2014 Korea NR ALND 253 28–82 69 26 22 136 Li27 2014 China Prospective SLNB 121 30–58 53 1 3 64 Luo28 2013 China NR ALND 78 30–63 38 4 7 30 Motomura29 2011 Japan Prospective SLNB 102 57 21 7 4 70 Nakai30 2011 Japan Prospective ALND 216 36–77 30 4 6 176 ALND, axillary lymph node dissection; FN, false negative; FP, false positive; NR, not reported; SLNB, sentinel lymph node biopsy; TN, true negative; TP, true positive. Data extraction Two reviewers independently reviewed the data of each included study. General information, such as sample size, year of publication, diagnostic gold standard, and patient age, were extracted. The number of TP, FP, FN, and TN results were carefully extracted from each study and crosschecked. Statistical methods All analysis was performed using MetaDiSc 1.4 software (http://www.hrc.es/investigacion/metadisc_en.htm). Statistical heterogeneity across the 26 included studies was assessed by I2 test. The data was pooled by fixed or random effect method according to the heterogeneity. Publication bias was assessed by line regression test. Diagnostic sensitivity and specificity was calculated using the formula: sensitivity = TP/(TP + FN) and specificity = TN/(TN + FP). P < 0.05 was considered statistically significant. Results Sensitivity and specificity analysis The diagnostic sensitivity and specificity of MRI to detect axillary lymph node metastasis in patients with breast cancer were pooled by random effect method because of significant statistical heterogeneity (I2 = 86.6% for sensitivity; I2 = 92.5% for specificity). The pooled sensitivity and specificity were 0.77 (95% confidence interval [CI] 0.75–0.80) (Fig 2) and 0.90 (95% CI 0.89–0.91) (Fig 3), respectively. Figure 2 Forest plot of pooled diagnostic sensitivity. CI, confidence interval. Figure 3 Forest plot of pooled diagnostic specificity. CI, confidence interval. Positive and negative likelihood ratios The pooled positive and negative likelihood ratios were 7.67 (95% CI 5.09–11.53) (Fig 4) and 0.23 (95% CI 0.17–0.32), respectively, by random effect method (Fig 5). Figure 4 Forest plot of pooled positive likelihood ratio (LR). CI, confidence interval. Figure 5 Forest plot of pooled negative likelihood ratio (LR). CI, confidence interval. Diagnostic odds ratio Because of significant heterogeneity across the included 26 studies (I2 = 80.9%; P < 0.05), the diagnostic odds ratio (DOR) was pooled by random effect method. The pooled DOR was 36.69, with a 95% confidence interval of 22.09–60.92 (Fig 6). Figure 6 Forest plot of diagnostic odds ratio (OR). CI, confidence interval. Symmetric receiver operating characteristic curve The symmetric receiver operating characteristic (SROC) curve was calculated by sensitivity against 1‐specificity using MetaDiSc 1.4 software. The area under the SROC curve (AUC) was 0.93 for MRI for the detection of axillary lymph node metastasis in breast cancer patients (Fig 7). Figure 7 Pooled symmetric receiver operating characteristic (SROC) curves. AUC, area under the curve; SE, standard error. Evaluation of publication bias The studies were evaluated by line regression test and no significant publication bias was observed (t = 0.33; P > 0.05) (Fig 8). Figure 8 Egger's line regression test to evaluate publication bias. Discussion Recent studies have shown that breast cancer has become one of the leading causes of cancer‐related death worldwide. It is estimated that 266 120 new breast cancer patients will be diagnosed in the United States in 2018.31 Breast cancer is the most commonly diagnosed malignant carcinoma in women. Fortunately, the long‐term (five‐year) survival rate of breast cancer in women is approximately 90%. As described in previous studies, axillary lymph node involvement is one the key factors relevant to prognosis in breast cancer patients. A clear understanding of the status of axillary lymph nodes in breast cancer patients is important not only for prognosis but also to select treatment modality or surgical method. Axillary lymph node dissection (ALND) is the reference standard for evaluating lymph node involvement. However, approximately 40–70% of breast cancer patients have histopathologically negative axillary lymph nodes32 indicating that 40–70% of breast cancer patients undergo unnecessary invasive examinations. Determining axillary lymph node involvement before treatment or dissection is important to reduce such examinations. The diagnostic performance of MRI to detect axillary lymph node metastasis in patients with breast cancer has been widely discussed. However, the exact diagnostic performance of MRI for discriminating axillary lymph node involvement is not fully understood because of the inconsistent results reported by previous studies.25, 26, 28 These inconsistencies may be the result of: (i) small sample sizes with limited statistical power; (ii) patient inclusion criteria; (iii) MRI examination technology; (iv) types of MRI instruments used; and (v) different reference standards for axillary lymph node involvement. In our present study, we included 26 studies that evaluated the diagnostic performance of MRI to determine axillary lymph node involvement in breast cancer and pooled the diagnostic sensitivity (0.77, 95% CI 0.75–0.80), specificity (0.90, 95% CI 0.89–0.91), and SROC (0.92) to further assess its value in clinical application. However, there are some limitations to our meta‐analysis. Firstly, we only searched for studies published in English or Chinese, which may have led to publication selection bias. Secondly, significant statistical heterogeneity existed in the sensitivity, specificity, positive and negative likelihood ratios, and ROC effect sizes. Thirdly, not all of the included studies were prospective, reducing the reliability of our results. 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