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Abdominal Imaging

, Volume 28, Issue 5, pp 733–742 | Cite as

Staging of pelvic endometriosis based on MRI findings versus laparoscopic classification according to the American Fertility Society

  • R. Zanardi
  • C. Del Frate
  • C. Zuiani
  • M. Bazzocchi
Article

Abstract

Background: Preoperative staging of pelvic endometriosis helps the gynecologist plan therapy and offers a prognosis to patients. We compared a staging system of pelvic endometriosis based on magnetic resonance imaging (MRI) findings with the American Fertility Society (AFS) laparoscopic classification.

Methods: Forty-four consecutive females with clinically suspected endometriosis underwent MRI examination to demonstrate the presence of endometriomas and pelvic implants. Laparoscopy was performed within 2 weeks. An MRI score was developed to classify endometriosis into four classes comparable to those of AFS laparoscopic staging. Concordance between MRI and laparoscopic classification was evaluated with κ statistics.

Results: Laparoscopy confirmed 60 of 61 endometriomas detected by MRI. Implants were discovered in 20 of 44 patients with MRI and in 23 of 44 with laparoscopy. MRI detected 50 endometrial implants of 65 detected by laparoscopy (76.9%). With regard to endometriosis staging, we obtained a concordance between MRI and AFS classification in 42 of 44 patients (κ = 0.913).

Conclusion: Although MRI has limitations such as suboptimal depiction of small implants and adhesions, this technique is very useful to guide laparoscopy. Moreover, the optimal concordance (95%) between our proposed MRI staging and the AFS laparoscopic classification demonstrated a new advantage of MRI in preoperative staging of endometriosis.

Endometriosis American Fertility Society classification Staging of endometriosis Pelvic magnetic resonance imaging. 

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Copyright information

© Springer-Verlag New York Inc. 2003

Authors and Affiliations

  • R. Zanardi
    • 1
  • C. Del Frate
    • 1
  • C. Zuiani
    • 1
  • M. Bazzocchi
    • 1
  1. 1.Institute of Radiology, University of Udine, via Colugna 50, 33100 UdineItaly

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