Lin Zhong1, Cong Wang2. 1. The First Affiliated Hospital of Dalian Medical University, Dalian City, Liaoning Province, China. 2. Ultrasound department of the First Affiliated Hospital of Dalian Medical University,Xigang District, Dalian City, Liaoning Province,China.. wc027214@163.com.
Abstract
AIM: This meta-analysis aimed to identify the accuracy of ultrasound superb microvascular imaging (SMI) for the diagnosis of a breast tumor. MATERIAL AND METHOD: We searched PubMed, Web of Science, Google Scholar, Cochrane Library, EBSCO, and CBM databases from January 1st, 2013 until February 1st, 2020 without language restrictions. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 software. We calculated the summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR+/LR-), diagnostic odds ratio (DOR) and receiver operating characteristic (SROC) curve. RESULTS: Fifteen studies that met all inclusion criteria were included in this meta-analysis. A total of 955 breast neoplasm patients and 1116 patients with benign breast tumors were assessed. All breast lesions were histologically confirmed after SMI. The pooled Sen was 0.81 (95%CI=0.78-0.83); the pooled Spe was 0.71 (95%CI=0.68-0.73) The pooled LR+ was 3.24 (95%CI=2.27-4.64); the pooled negative LR-was 0.25 (95%CI=0.18-0.34) The pooled DOR of SMI in the diagnosis of breast tumor was 46.97 (95 % CI=16.72∼131.97). The area under the SROC curve was 0.87 (95%CI=0.84- 0.90). We found no evidence for publication bias (t=-0.84, p=0.42). CONCLUSION: Our meta-analysis indicates that SMI may have a high diagnostic accuracy in differential diagnosis between benign and malignant breast tumors. Thus, SMI may be a good tool for the diagnosis of breast tumors.
AIM: This meta-analysis aimed to identify the accuracy of ultrasound superb microvascular imaging (SMI) for the diagnosis of a breast tumor. MATERIAL AND METHOD: We searched PubMed, Web of Science, Google Scholar, Cochrane Library, EBSCO, and CBM databases from January 1st, 2013 until February 1st, 2020 without language restrictions. Meta-analysis was conducted using STATA version 14.0 and Meta-Disc version 1.4 software. We calculated the summary statistics for sensitivity (Sen), specificity (Spe), positive and negative likelihood ratio (LR+/LR-), diagnostic odds ratio (DOR) and receiver operating characteristic (SROC) curve. RESULTS: Fifteen studies that met all inclusion criteria were included in this meta-analysis. A total of 955 breast neoplasmpatients and 1116 patients with benign breast tumors were assessed. All breast lesions were histologically confirmed after SMI. The pooled Sen was 0.81 (95%CI=0.78-0.83); the pooled Spe was 0.71 (95%CI=0.68-0.73) The pooled LR+ was 3.24 (95%CI=2.27-4.64); the pooled negative LR-was 0.25 (95%CI=0.18-0.34) The pooled DOR of SMI in the diagnosis of breast tumor was 46.97 (95 % CI=16.72∼131.97). The area under the SROC curve was 0.87 (95%CI=0.84- 0.90). We found no evidence for publication bias (t=-0.84, p=0.42). CONCLUSION: Our meta-analysis indicates that SMI may have a high diagnostic accuracy in differential diagnosis between benign and malignant breast tumors. Thus, SMI may be a good tool for the diagnosis of breast tumors.