Can the ultrasound microcystic pattern accurately predict borderline ovarian tumors?

OBJECTIVE: To investigate whether the ultrasound microcystic pattern (MCP) can accurately predict borderline ovarian tumors (BOTs). METHODS: A retrospective collection of 393 patients who met the inclusion criteria was used as the study population. Indicators that could well identify BOT in different pathological types of tumors were derived by multivariate unordered logistic regression analysis. Finally, the correlation between ultrasound MCP and pathological features was analyzed. RESULTS: (1) MCP was present in 55 of 393 ovarian tumors, including 34 BOTs (34/68, 50.0%), 16 malignant tumors (16/88, 18.2%), and 5 benign tumors (5/237, 2.1%). (2) Univariate screening showed significant differences (P < 0.05) in patient age, CA-125 level, ascites, > 10 cyst locules, a solid component, blood flow, and MCP among BOTs, benign ovarian tumors, and malignant ovarian tumors. (3) Multivariate unordered logistic regression analysis showed that the blood flow, > 10 cyst locules, and MCP were significant factors in identifying BOTs (P < 0.05). (4) The pathology of ovarian tumors with MCP showed "bubble"- or "fork"- like loose tissue structures. CONCLUSION: MCP can be observed in different pathological types of ovarian tumors and can be used as a novel sonographic marker to differentiate between BOTs, benign tumors and malignant tumors. MCP may arise as a result of anechoic cystic fluid filling the loose tissue gap.