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A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection
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A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection
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A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection
A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection
Journal Article

A Comprehensive Review of Screening Methods for Ovarian Masses: Towards Earlier Detection

2023
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Overview
Ovarian masses, ranging from benign cysts to malignant tumors, present complex diagnostic challenges in women's healthcare. Early detection of ovarian masses is paramount for improving patient outcomes, as delayed diagnoses often lead to advanced-stage disease with limited treatment options. This comprehensive review explores screening methods' current state, limitations, and emerging technologies to facilitate earlier detection. The limitations of existing screening methods, such as low sensitivity and specificity, underscore the need for improved early detection strategies. Imaging-based techniques, including transvaginal ultrasound, magnetic resonance imaging, and computed tomography, are vital in evaluating ovarian masses. However, the emergence of artificial intelligence (AI) and machine learning (ML) applications enhances the accuracy of image interpretation. Blood-based biomarkers, such as CA-125, have been the focus of research for ovarian mass detection. While CA-125 remains widely used, its limitations have prompted investigations into alternative serum biomarkers, including HE4 and miRNA, along with liquid biopsy and circulating tumor DNA. Ultrasound-based scoring systems, such as the risk of malignancy index (RMI), Ovarian-Adnexal Reporting and Data System (O-RADS), and guidelines from the International Ovarian Tumor Analysis (IOTA) group, provide structured approaches for classifying ovarian masses. These systems aid healthcare providers in clinical decision-making. Emerging technologies, such as liquid biopsy, AI, and proteomic/metabolomic approaches, offer promising avenues for enhancing early detection and risk assessment. Liquid biopsy provides noninvasive, real-time monitoring of ovarian masses, while AI and ML applications improve the accuracy of image interpretation. Proteomic and metabolomic studies reveal novel biomarkers and molecular insights. High-risk populations, often associated with genetic mutations such as BRCA1 and BRCA2, require specialized screening strategies. Current guidelines recommend screening modalities, risk-reduction strategies, and shared decision-making. Ongoing research focuses on refining risk assessment and personalized screening for high-risk individuals. This review underscores the importance of early detection in managing ovarian masses, emphasizing the need for improved screening methods, tailored approaches for high-risk populations, and ongoing research to further enhance diagnostic accuracy and patient outcomes.