Prevalence and distribution of adnexal findings suggesting endometriosis in patients with MR diagnosis of adenomyosis

T Thomas Zacharia, M. J. O'Neill

Research output: Contribution to journalReview articlepeer-review

24 Scopus citations


The purpose of this investigation was to establish the prevalence and distribution of MR findings associated with pelvic endometriosis in patients with a MRI diagnosis of adenomyosis. Retrospective review of the pelvic MRI in 59 patients (age 32-54 years, mean 42 years) who met strict MRI criteria for adenomyosis was performed. T1 weighted fat saturated and T2 weighted images in these patients were reviewed for the presence or absence of T1 bright signal suggesting endometriosis in any of nine locations (uterine serosa, right and left ovary, right and left fallopian tube, right and left broad ligament, and right and left pelvic side wall). 20 (20/59) patients (34%), showed characteristic MRI features associated with endometriosis. A total of 54 sites of involvement were identified (uterine serosa n=17, ovaries n=14, broad ligaments n=10, fallopian tubes n=8, pelvic side walls n=5) in 20 patients with an average of 2.7 sites per patient. Implants (n=43) were more common than endometriomas (n = 11). Endometriomas occurred most often in the ovaries (ovaries n=9, broad ligament n=2) whereas implants were seen on all locations (uterine serosa n=17, ovaries n=5, broad ligaments n=8, fallopian tubes n=8, pelvic side walls n=5). One third of patients with adenomyosis diagnosed by MRI also had MRI findings of endometriosis, with serosal implants being the most common finding. Imaging protocols should routinely include T1 weighted fat saturated imaging sequences in order to detect coexistent endometriosis in patents undergoing pelvic MRI for the diagnosis of adenomyosis.

Original languageEnglish (US)
Pages (from-to)303-307
Number of pages5
JournalBritish Journal of Radiology
Issue number940
StatePublished - Apr 1 2006

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging


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