女性盆底功能障碍性疾病筛查的研究进展

doi:10.12280/gjszjk.20250632

摘要/Abstract

摘要：

女性盆底功能障碍性疾病（pelvic floor dysfunction，PFD）患病率为17.8%~74.07%，严重影响女性的生活质量和心理健康。目前PFD常用筛查手段中，盆腔器官脱垂定量（pelvic organ prolapse quantification，POP-Q）分度法、标准化问卷调查、二维超声及静态MRI仅能评估静态解剖结构，主观性强且缺乏动态功能评估。新兴筛查技术虽各有优势，但也有局限性，如高密度肌电图空间分辨率高、可精准定位肌肉损伤，但设备成本高；三维/四维超声与动态MRI可实现动态功能评估，但成本高、基层普及困难；生物标志物检测（如8-羟基脱氧鸟苷等）可提供分子层面诊断依据，但仍需大量临床样本验证；人工智能预测模型效能良好，尚缺乏多中心标准化验证。PFD筛查正经历从单一技术评估到多模态整合的转变，通过建立多模态整合策略，实施分级筛查路径，制定个体化筛查方案，有望实现PFD的早期发现、精准诊断和早期干预，最终改善患者的生活质量和预后。

关键词: 生物标记, 人工智能, 症状评估, 诊断筛查项目, 盆底功能障碍性疾病

Abstract:

The prevalence of female pelvic floor dysfunction (PFD) ranges from 17.8% to 74.07%, which severely compromises the life quality and mental health of women. The screening modalities commonly used for PFD, such as pelvic organ prolapse quantification (POP-Q) staging system, standardized questionnaires, two-dimensional ultrasound and static MRI, are only capable of evaluating the static anatomical structure, yet they are highly subjective and lack the dynamic and functional assessment. Although emerging screening techniques exhibit respective advantages, they also present inherent limitations. High-density electromyography features high spatial resolution and enables precise localization of muscle injury, but entails high equipment costs. Three-dimensional/four-dimensional ultrasound and dynamic MRI allow a dynamic and functional evaluation, yet they are constrained by high costs and limited accessibility in primary care settings. Biomarker detection (e.g., 8-hydroxy-2'-deoxyguanosine, etc.) can provide molecular-level diagnostic evidence, but it still requires further validation with large clinical samples. Artificial intelligence prediction models demonstrate promising predictive performance, but lack the standardized multicenter validation. PFD screening is undergoing a transition from single-technique evaluation to multimodal integration. The establishment of a multimodal integration strategy, implementation of a hierarchical screening pathway, and formulation of individualized screening protocols are expected to achieve early detection, precise diagnosis, early intervention of PFD, and ultimately improve the life quality and prognosis of PFD patients.

Key words: Biomarkers, Artificial intelligence, Symptom assessment, Diagnostic screening programs, Pelvic floor dysfunction

梁丽春, 莫智媛, 钟庆梅, 黄静, 唐桂艳. 女性盆底功能障碍性疾病筛查的研究进展[J]. 国际生殖健康/计划生育杂志, 2026, 45(3): 259-264.

LIANG Li-chun, MO Zhi-yuan, ZHONG Qing-mei, HUANG Jing, TANG Gui-yan. Research Progress on Screening for Female Pelvic Floor Dysfunction[J]. Journal of International Reproductive Health/Family Planning, 2026, 45(3): 259-264.

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