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lüll Deep retroperitoneal pelvic endometriosis: MR imaging appearance with laparoscopic correlation Del Frate C; Girometti R; Pittino M; Del Frate G; Bazzocchi M; Zuiani CRadiographics 2006[Nov]; 26 (6): 1705-18Deep pelvic endometriosis is defined as subperitoneal infiltration of endometrial implants in the uterosacral ligaments, rectum, rectovaginal septum, vagina, or bladder. It is responsible for severe pelvic pain. Accurate preoperative assessment of disease extension is required for planning complete surgical excision, but such assessment is difficult with physical examination. Various sonographic approaches (transvaginal, transrectal, endoscopic transrectal) have been used for this purpose but do not allow panoramic evaluation. Furthermore, exploratory laparoscopy has limitations in demonstrating deep endometriotic lesions hidden by adhesions or located in the subperitoneal space. Despite some limitations, magnetic resonance (MR) imaging is able to directly demonstrate deep pelvic endometriosis. The MR imaging features depend on the type of lesions: infiltrating small implants, solid deep lesions mainly located in the posterior cul-de-sac and involving the uterosacral ligaments and torus uterinus, or visceral endometriosis involving the bladder and rectal wall. Solid deep lesions have low to intermediate signal intensity with punctate regions of high signal intensity on T1-weighted images, show uniform low signal intensity on T2-weighted images, and can demonstrate enhancement on contrast-enhanced images. MR imaging is a useful adjunct to physical examination and transvaginal or transrectal sonography in evaluation of patients with deep infiltrating endometriosis.|Endometriosis/*pathology[MESH]|Female[MESH]|Humans[MESH]|Image Enhancement/*methods[MESH]|Laparoscopy/*methods[MESH]|Magnetic Resonance Imaging/*methods[MESH]|Pelvic Inflammatory Disease/*diagnosis[MESH]|Peritoneal Diseases/*diagnosis[MESH]|Practice Guidelines as Topic[MESH]|Practice Patterns, Physicians'[MESH]|Retroperitoneal Space/*pathology[MESH]|Statistics as Topic[MESH] |