The diagnostic value of ultrasound elastography in differentiating idiopathic granulomatous mastitis from breast cancer: A systematic review and a meta-analysis

Background and Aims Idiopathic granulomatous mastitis (IGM) is a rare form of chronic mastitis that often mimics breast cancer on diagnostic imaging and clinically. Mammography, conventional ultrasound (CUS), and magnetic resonance imaging have long been used to differentiate these two entities, but yield inconclusive results. Ultrasound elastography (UE) is a non-invasive technique used to evaluate tissue stiffness. However, there is insufficient information on the diagnostic utility of UE in differentiating IGM from breast cancer. This systematic review and meta-analysis was therefore conducted to ascertain the diagnostic utility of UE and how it compares to CUS. Methods This systematic review and meta-analysis was reported following the PRISMA guidelines. Four electronic databases were searched, namely EMBASE, MEDLINE, Scopus, and the Cochrane Library. Data were extracted independently by two review authors. Quantitative data were analyzed using Review Manager 5 and Metadisc 2.0. Results The meta-analysis was conducted using a random effects model and standard mean difference. Diagnostic test accuracy (DTA) analysis was also performed. The results of the meta-analysis revealed statistically significant pooled mean differences of 3.64 (95% CI: 3.25-4.02) and 2.68 (95% CI: 2.40-2.96) in strain ratio (SR) and shear wave elastography (SWE), respectively, between IGM and breast cancer patients. The results for the DTA analysis showed a high pooled sensitivity and a relatively low specificity of 90.0% and 73.0% for CUS. Shearwave elastography (SWE) yielded the best results with both the pooled sensitivity and specificity being high at 94.0% and 93.0% respectively. Conclusion Ultrasound elastography , especially SWE, enhances the ability to distinguish IGM from breast cancer. However, geographical limitations and variability in techniques highlight the need for standardization and multicenter studies to improve reliability and global applicability.