Endometriosis is a benign gynecological disease, affecting women of reproductive age and characterized by the proliferation of endometrial tissue outside the uterine cavity, whose diagnosis is not easy since symptoms often appear as a severe discomfort during menstrual cycle, with consequent misunderstanding [1].
It presents as superficial peritoneal implants or as lesions located on the ovaries (endometrioma) or as deeply invasive nodules that can infiltrate different organs such as rectum, uterus and bladder, compromising their functionality [2].
Endometriosis is associated with chronic pelvic pain, dysmenorrhea, dyspareunia and infertility, unspecific symptoms present in many other pelvic diseases.
Ovarian endometrioma (OMA), superficial peritoneal endometriosis (SPE) and deep infiltrating endometriosis (DIE) are recognized as major phenotypes. DIE is the most severe clinical one in which hormonal (estrogen and progesterone receptors) and immunological factors (peritoneal macrophages, natural killer cells and lymphocytes) are critically altered [3].
A particular variant of the disease is sciatic endometriosis, due to the presence of endometrial tissue implant next to and alongside the sciatic nerve course, which causes sciatica-like pain constantly associated with menstrual cycle.
Until now few cases of neuro-endometriosis have been reported in the literature and Salazar-Grueso and Roos [4] described a mean interval of 3.7 years between the onset of symptoms and diagnosis.
Laparoscopy and surgical biopsy, followed by a histological exam, are required because they lead to direct visualization of lesions [5], but these procedures are invasive and the accuracy of the diagnosis depends on surgeon experience and ability [6]. Other diagnostic useful, but with lower specificity and sensitivity, techniques are Trans-Vaginal Ultrasound (TV-US) and Magnetic Resonance Imaging (MRI): the former is the most applied thanks to its large availability, no dangerous biological effects, repeatability and low costs, but the latter is better in terms of reproducibility and diagnostic accuracy [7].
We aim to describe all the features of MR images useful for timely disease recognition.