This article analyzes the diagnostic significance of transvaginal ultrasound examination (TVUS) in the early detection of ovarian cancer, as well as the advantages, limitations, and potential for combining this method with modern diagnostic approaches. Ovarian cancer is one of the most dangerous pathologies in gynecological oncology. Due to its prolonged asymptomatic course and detection at late stages, mortality rates remain high. According to WHO data, over 300,000 new cases are registered worldwide annually. In Uzbekistan, 70–80% of cases are diagnosed at stages III–IV due to insufficient screening programs. TVUS is considered a first-line screening method due to its non-invasiveness, cost-effectiveness, and real-time results. Using the IOTA Simple Rules and the IOTA ADNEX model, the accuracy of distinguishing benign from malignant tumors reaches 94–96%. Color Doppler imaging additionally allows assessment of blood flow parameters (resistance index <0.4, pulsatility index <1.0). Combining TVUS with the CA-125 tumor marker and the ROMA index increases diagnostic accuracy to 96–97%. The integration of artificial intelligence technologies (AI transformer models) enables ovarian cancer diagnosis with 92–98% accuracy and reduces diagnostic errors by up to 30%. Meanwhile, limitations of the method include dependence on operator experience (error rate 20–30%), reduced sensitivity (70–75%) in stage I, and false-positive results (up to 30%). In conclusion, TVUS is a primary diagnostic tool in ovarian cancer screening; combining it with biomarkers and artificial intelligence can significantly improve early diagnosis and survival rates. In Uzbekistan, expanding screening coverage in rural areas and improving specialist training remain urgent priorities.

Ovarian cancer, Transvaginal ultrasound (TVUS), Screening programs, Cancer prevention, Artificial intelligence (AI) integration, Biomarkers, CA-125

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