MODERN DIAGNOSTICS OF CHRONIC PELVIC PAIN IN WOMEN: INTEGRATIVE APPROACHES AND EMERGING TECHNOLOGIES (Multidisciplinary Journal of Science and Technology, 2025)
Chronic pelvic pain (CPP) is a debilitating condition affecting 5.7–26.6% of women globally, significantly impairing quality of life and posing substantial diagnostic challenges due to its multifactorial etiology. Causes range from gynecological conditions (e.g., endometriosis, adenomyosis) to urological, musculoskeletal, and neurological disorders. Traditional diagnostic methods, such as patient history and physical examination, are often insufficient to pinpoint specific causes due to symptom overlap. Recent advancements in diagnostic technologies, including high-resolution imaging (ultrasound, MRI), minimally invasive laparoscopy, biomarker assays, and artificial intelligence (AI)-driven tools, have transformed the diagnostic landscape. This article provides an in-depth review of current and emerging diagnostic modalities, emphasizing integrative approaches that combine clinical assessment, advanced imaging, molecular diagnostics, and multidisciplinary collaboration. The role of novel technologies, such as machine learning algorithms for pattern recognition and biomarker panels for non-invasive diagnosis, is explored in detail. The study underscores the need for personalized, patient-centered diagnostic strategies to improve outcomes and reduce diagnostic delays in women with CPP.