Recent advances in ovarian cancer detection are focusing on three main areas:
Liquid Biopsy: Using non-invasive blood tests to detect circulating tumor DNA (ctDNA) and other biomarkers like microRNAs.
AI and Machine Learning: Applying AI to analyze medical images (ultrasound, CT scans) and integrate various data sources to improve diagnostic accuracy and identify subtle patterns.
New Biomarkers: Developing multi-marker blood panels (e.g., combining CA-125 with HE4) and exploring novel biomarkers like autoantibodies to enhance sensitivity for early-stage detection.
These technologies aim to provide less invasive, more accurate, and earlier detection, improving patient outcomes.