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Is endometriosis a progressive disease?

Sun-Wei Guo1, Michel Canis2, Paolo P Vercellini3

  • 1Research Institute, Shanghai OB/GYN Hospital, Fudan University, Shanghai 200433, China; Shanghai Key Laboratory of Reproduction and Development, Fudan University, Shanghai 200433, China; Shanghai Key Laboratory of Female Reproductive Endocrine-Related Diseases, Fudan University, Shanghai 200433, China.

Trends in Molecular Medicine
|March 21, 2026
PubMed
Summary
This summary is machine-generated.

Endometriosis progression is debated, but lesional stiffness, measured by elastography, shows promise as a marker. This stiffness correlates with disease characteristics and could improve diagnosis and treatment for endometriosis.

Keywords:
endometriosisnatural historyprogressionrepeated tissue injury and repairwound healing

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Area of Science:

  • Gynecology
  • Pathology
  • Biomedical Engineering

Background:

  • The progressive nature of endometriosis, a chronic inflammatory condition, remains a subject of debate.
  • Understanding the natural history of endometriotic lesions, characterized by repeated injury and repair cycles, is crucial.

Purpose of the Study:

  • To reassess the literature on endometriosis progression, considering aggravating and mitigating factors.
  • To propose lesional stiffness, measured by elastography, as a potential marker for disease progression.

Main Methods:

  • Literature review on endometriosis natural history and progression factors.
  • Correlation analysis of lesional stiffness with histological, molecular, symptomatic, and mechanobiological aspects of endometriosis.

Main Results:

  • Lesional fibrosis, indicated by stiffness, is proposed as a key factor in endometriosis progression.
  • Lesional stiffness correlates with aberrant histology, molecular changes, symptom severity, and clinical prognosis.

Conclusions:

  • Lesional stiffness measured via elastography is a promising biomarker for endometriosis progression.
  • This marker could aid in endometriosis diagnosis, treatment selection, and outcome prediction.