Does pelvic magnetic resonance imaging differentiate among the histologic subtypes of uterine leiomyomata?
OBJECTIVE
To evaluate if pelvic magnetic resonance imaging (MRI) is reliable for differentiating leiomyoma subtypes.


METHODS
Prospective study.


METHODS
Academic center.


METHODS
Forty-five patients underwent MRI before surgery for leiomyomata.


METHODS
One radiologist blinded to patient history and histologic diagnosis recorded the MRI characteristics and classification of the largest leiomyoma.


METHODS
Comparison of MRI and histologic diagnoses.


RESULTS
Leiomyoma subtypes were diagnosed accurately by MRI in 69% of cases. Magnetic resonance imaging had a 95% sensitivity and 72% specificity for diagnosing an uncomplicated leiomyoma and a 10% sensitivity and 100% specificity for a cellular leiomyoma. For cystic leiomyomata, the sensitivity was 80% and specificity was 98%, and for hemorrhagic leiomyomata, 100% and 86%, respectively. Magnetic resonance imaging correctly diagnosed all malignant tumors and did not incorrectly diagnose a leiomyoma as a leiomyosarcoma in any case. Ill-defined MRI margins were significantly more likely to be leiomyosarcoma, whereas well-defined margins were characteristic of benign lesions. Hemorrhagic leiomyomata were significantly more likely to be hyperintense on T1-weighted images than other subtypes.


CONCLUSIONS
Although MRI is only fairly accurate in differentiating the subtypes of benign uterine smooth muscle tumors, signal intensities and margin characteristics are useful to distinguish accurately benign from malignant tumors.
Department of Obstetrics and Gynecology, New York University Medical Center, New York 10016, USA.
L B
LB
Schwartz
M
M
Zawin
M L
ML
Carcangiu
R
R
Lange
S
S
McCarthy
D000328:Adult; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007889:Leiomyoma / Q000175:diagnosis*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D010388:Pelvis; D011446:Prospective Studies; D015203:Reproducibility of Results; D016037:Single-Blind Method; D014594:Uterine Neoplasms / Q000175:diagnosis*