TY - JOUR T1 - The accurate diagnosis of grand microvascular imaging in differentiating benign and malignant thyroid nodules: A meta-analysis TT - JF - Int-J-Radiat-Res JO - Int-J-Radiat-Res VL - 20 IS - 2 UR - http://ijrr.com/article-1-4247-en.html Y1 - 2022 SP - 263 EP - 267 KW - thyroid nodule KW - superb microvascular imaging KW - meta-analysis. N2 - Background: Meta-analysis experiments can be used to judge the hypothesis of SMI benign and malignant thyroid nodules. Material and Methods: We explored Cochrane Library, PubMed, Google Scholar, CBM and Web of Science, databases according to the required content, and used a number of analysis equipment to analyze, and through the conclusions drawn to determine the sensitivity (Sen) and specificity (Spe), the probability ratio of pragmatic and dismissive (LR + / LR-), diagnostic factor (DOR) and receiver performance typical curve (SROC) are calculated for summary statistics. Results: The meta-analysis included nine studies that met the participation criteria. An aggregation of 636 malignant thyroid legumes and 732 benign thyroid nodules were evaluated. The comprehensive Sen was 0.79 (95% confidence interval (CI) = 0.76-0.82), and the comprehensive Spe was 0.89 (95% CI = 0.85-0.92). The comprehensive LR + was 7.04 (95% CI = 5.26-9.43), and the comprehensive negative LR- was 0.23 (95% CI = 0.20-0.27). The comprehensive DOR of thyroid nodules diagnosed by SMI was 30.33 (95% confidence interval = 20.73–44.38). The range beneath the SROC curve was 0.82 (95% confidence interval = 0.79 to 0.86). We established no proof of reporting bias (t = 0.91, P = 0.39). Conclusion: In a related meta-analysis, the study found that SMI has a very high prognosis accuracy in distinguishing malignant and benign thyroid nodules. M3 10.52547/ijrr.20.2.2 ER -