Human Reproduction, Vol. 16, No. 11, 2427-2433,
November 2001
© 2001 European Society of Human Reproduction and Embryology
Ultrasonography compared with magnetic resonance imaging for the diagnosis of adenomyosis: correlation with histopathology
1 Departments of Radiology, 2 Pathology and 3 Obstetrics and Gynecology, Hôpital Tenon, 4 rue de la Chine, 75020, France,
BACKGROUND: The objective of this study was to compare the accuracy of transabdominal (TAUS) and transvaginal sonography (TVUS) and magnetic resonance imaging (MRI) for the diagnosis of adenomyosis, and to correlate imaging with histological findings. METHODS: In a prospective study, 120 consecutive patients referred for hysterectomy underwent TAUS, TVUS and MRI. Results of these examinations were interpreted blindly to histopathological findings. RESULTS: Histological prevalence of adenomyosis and leiomyomas was 33.0 and 47.5% respectively. Adenomyotic uteri were accompanied by additional pelvic disorders in 82.5% of cases. Sensitivity, specificity, and positive and negative predictive values of TAUS and TVUS were 32.5 and 65.0%, 95.0 and 97.5%, 76.4 and 92.8%, and 73.8 and 88.8% respectively. Myometrial cyst was the most sensitive and specific TVUS criterion. In MRI, the presence of a high-signal-intensity myometrial spot was as specific but less sensitive than a maximal junctional zone thickness (JZmax) >12 mm and a JZmax to myometrial thickness ratio >40%. Sensitivity, specificity, and positive and negative predictive values of MRI were 77.5, 92.5, 83.8 and 89.2% respectively. No difference in accuracy was found between TVUS and MRI, but sensitivity was lower with sonography in women with associated myomas. CONCLUSIONS: TVUS is as efficient as MRI for the diagnosis of adenomyosis in women without myoma, while MRI could be recommended for women with associated leiomyoma.
Key words: adenomyosis/leiomyoma/MRI/ultrasound/uterus
4 To whom correspondence is addressed at: Service de Radiologie, Hôpital Tenon, 4 rue de la Chine, 75020,Paris, France. E-mail: marc.bazot{at}tnn.ap-hop-paris.fr
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