NON-INVASIVE BIOMARKERS AND ADVANCED IMAGING FOR EARLY DETECTION OF ENDOMETRIOSIS: DIAGNOSTIC PERFORMANCE, REAL-WORLD EVIDENCE, ARTIFICIAL INTELLIGENCE, AND IMPLEMENTATION PRIORITIES

Xolboyeva Mashhura
In: ACUMEN: INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH · 2026 · vol. 3(10) , pp. 222–250 · doi:10.66301/tprcz211 · W7222874074
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This paper critically appraises the diagnostic performance of non-invasive modalities for endometriosis, including expert transvaginal ultrasonography, MRI, circulating biomarkers, and saliva-based microRNA signatures.

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This paper critically appraises the diagnostic role of non-invasive modalities, including expert transvaginal ultrasonography, magnetic resonance imaging, circulating biomarkers, and saliva-based microRNA signatures, for endometriosis. It addresses the clinical challenges of delayed recognition and unequal access to specialist imaging by proposing an integrated strategy that moves away from surgically centered diagnosis. The authors describe how real-world data, causal inference, and artificial intelligence can support the safe implementation of these advanced detection methods. This paper is centrally about endometriosis — specifically focusing on non-invasive biomarkers and advanced imaging for early detection.

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Abstract

Endometriosis is a chronic, heterogeneous inflammatory disease for which delayed recognition and unequal access to specialist imaging remain important clinical problems. The transition from surgically centered diagnosis to an integrated, non-invasive strategy has increased interest in expert transvaginal ultrasonography, magnetic resonance imaging, circulating biomarkers, and saliva-based microRNA signatures. Objective: To critically appraise the diagnostic role of these modalities and describe how real-world data, causal inference and artificial intelligence can support safe implementation. Methods:
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Abstract

Endometriosis is a chronic, heterogeneous inflammatory disease for which delayed recognition and unequal access to specialist imaging remain important clinical problems. The transition from surgically centered diagnosis to an integrated, non-invasive strategy has increased interest in expert transvaginal ultrasonography, magnetic resonance imaging, circulating biomarkers, and saliva-based microRNA signatures. Objective: To critically appraise the diagnostic role of these modalities and describe how real-world data, causal inference and artificial intelligence can support safe implementation. Methods:

References

1. World Health Organization. Endometriosis. Fact sheet. 2025. Available from: https://www.who.int/news-room/fact-sheets/detail/endometriosis 2. Becker CM, et al. ESHRE guideline: endometriosis. Hum Reprod Open. 2022;2022(2):hoac009. Available from: https://academic.oup.com/hropen/article/2022/2/hoac009/6537540 3. European Society of Human Reproduction and Embryology. Endometriosis guideline. 2022. Available from: https://www.eshre.eu/Guidelines-andLegal/Guidelines/Endometriosis-guideline 4. Validation of a Saliva Micro-RNA Signature for Endometriosis. NEJM Evid. 2025. doi:10.1056/EVIDoa2400195. Available from: https://pubmed.ncbi.nlm.nih.gov/41147827/ 5. Transvaginal ultrasound and magnetic resonance imaging in detecting rectosigmoid deep infiltrating endometriosis: a comparative meta-analysis. 2025. Available from: This work is licensed under a Creative Commons Attribution 4.0 International License.

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