# Magnetic Resonance Roadmap in Detecting and Staging Endometiosis: Usual and Unusual Localizations
## 2 Indications for MRI
### Technical Requirements and Protocols of Acquisition  
A 1.5 Tesla (T) or more MRI system is strongly recommended. Only a few centers have published some interesting analyses using a 3.0 T, but there is still a lack of information on the comparison of the images obtained by the two systems and, therefore, there is no recommendation for using a specific device or another [23]. Pelvic phased array coils give a higher signal-to-noise ratio (SNR) than a body coil; some centers use endocavitary coil in addition to the pelvic array, although this is not convenient in terms of costs and acceptability [24]. The MRI protocol consists of a T2-weighted imaging (T2 WI) sequence without fat suppression [7], which is considered the best for detecting pelvic endometriosis implants. At least two orthogonal planes must be performed (sagittal and axial). An axial T2 WI acquisition from the renal hila to the pubic bone, allowing the visualization of kidneys and the right iliac fossa, should be recommended. In addition, a thin oblique section 2D T2 WI sequence may be used to detect urerosacral and parametrial implants [25]. Three-dimensional T2 WI sequences are reported as a potential option in some studies. In fact, some authors describe a new technique called \"CUBE\", a coronal single-slab 3D fast spin echo T2 WI MRI able to reduce time acquisition with superior image quality and better 3D reconstruction (multi-planar reconstruction). These improvements are similar to 2D fast spin echo T2 WI MRI in the evaluation of DIE locations [24]. T1 WI MRI sequences with or without fat suppression are recommended for the study of adnexal endometriosis and for active foci of DIE [26; 27]. There is no recommendation regarding diffusion-weighted imaging (DWI) sequences, but some authors suggest that it can be performed to differentiate endometriosis from hemorrhagic cysts, with lower apparent diffusion coefficient (ADC) values in the endometriosis [23]. There is no consensus on the use of intravenous contrast agent in the evaluation of DIE, but it is recommended as an \"option\" in the evaluation of adnexal endometriosis; it can be useful for recognizing abdominal wall endometriosis, or in the differentiation of an endometriosis from a luteal ovarian cyst or tubo-ovarian abscess due to an intense wall enhancement [28; 29]. Some authors show that it can be useful to recognize mural nodules, which are probably malignant in ovarian lesions [30]. Finally, in patients with the simultaneous presence of endometriosis and pelvic inflammatory disease, a strong wall enhancement within an adnexal mass is useful to distinguish the two pathologies. Recently, few studies reported the utility of using T2-star-weighted imaging (T2*WI) to better characterize endometrioma: this sequence is highly sensitive for hemosiderin as it can detect the hemosiderin deposits in endometrioma caused by ectopic endometrium's cyclic hemorrhage, appearing hypointense. This hypointensity can be classified into four types of patterns: eggshell, nodular, multinodular, and planar all along the cyst walls. Consequently, hypointensity in T2*WI can be useful in distinguishing endometrioma from mucinous cystadenomas [31]. With regard to artificial intelligence (AI), several studies have recently demonstrated the role of AI in increasing diagnostic and research efficacy and outcome prediction in endometriosis; a recent literature review analyzed the most recent published studies on endometriosis and AI, identifying six major categories to build diagnostic and predictive AI models (biomarkers, such as plasma biomarkers of menstrual cycle, miRNA, components of endometrial fluid, clinical symptoms, genetic variables and metabolite spectra, and MRI), showing a good diagnostic and predictive capacity in assessing endometriosis [32]. Another recent review compared two algorithms of AI medical image segmentation and the nursing care given to patients in pre- and post-surgical assistance.