Uterine adenomyosis is a common benign condition defined by the presence of heterotopic endometrial glands and stroma within the myometrium. Adenomyosis is often related to infertility and other adverse pregnancy outcomes. Modern imaging techniques allow the non-invasive diagnosis of adenomyosis and, in this framework, Magnetic Resonance Imaging (MRI) has assumed a central role due to its high diagnostic accuracy in the detection of adenomyosis. Currently, there is still a lack of international consensus on adenomyosis diagnostic criteria and classification, despite the fact that an agreed reporting system would promote treatment outcomes and research. This review aims to emphasize the important contribution of MRI to the diagnosis of adenomyosis and to highlight how, thanks to the great tissue differentiation provided by MRI, it is possible to identify the main direct (cystic component) and indirect (junctional zone features) signs of adenomyosis and to distinguish its various subtypes according to different MRI-based classifications. We also explored the main MRI criteria to identify the most common pitfalls and differential diagnoses of adenomyosis, whose features should be considered to avoid misdiagnosis.

PC represents the most striking picture of the loco-regional spread of ovarian cancer, configuring stage III. In the last few years, many papers have evaluated the role of imaging and therapeutic management in patients with ovarian cancer and PC. This paper summed up the literature on traditional approaches to the imaging of peritoneal carcinomatosis in advanced ovarian cancer, presenting classification systems, most frequent patterns, routes of spread and sites that are difficult to identify. The role of imaging in diagnosis was investigated, with particular attention to the reported sensitivity and specificity data—computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography-CT (PET-CT)—and to the peritoneal cancer index (PCI). In addition, we explored the therapeutic possibilities and radiomics applications that can impact management of patients with ovarian cancer. Careful staging is mandatory, and patient selection is one of the most important factors influencing complete cytoreduction (CCR) outcome: an accurate pre-operative imaging may allow selection of patients that may benefit most from primary cytoreductive surgery.

Purpose: To evaluate the diagnostic accuracy of the Node-RADS score and the utility of apparent diffusion coefficient (ADC) values in predicting metastatic lymph nodes (LNs) involvement in cervical cancer (CC) patients using magnetic resonance imaging (MRI). The applicability of the Node RADS score across three readers with different years of experience in pelvic imaging was also assessed. Material and methods: Among 140 patients, 68 underwent staging MRI, neoadjuvant chemotherapy and radical surgery, forming the study cohort. Node-RADS scores of the main pelvic stations were retrospectively determined to assess LN metastatic likelihood and compared with the histological findings. Mean ADC, relative ADC (rADC), and correct ADC (cADC) values of LNs classified as Node-RADS ≥ 3 were measured and compared with histological reports, considered as gold standard. Results: Sensitivity, specificity, positive and negative predictive values (PPVs and NPVs), and accuracy were calculated for different Node-RADS thresholds. Node RADS ≥ 3 showed a sensitivity of 92.8% and specificity of 72.5%. Node RADS ≥ 4 yielded a sensitivity of 71.4% and specificity of 100%, while Node RADS 5 yielded 42.9% and 100%, respectively. The diagnostic performance of mean ADC, cADC and rADC values from 78 LNs with Node-RADS score ≥ 3 was assessed, with ADC demonstrating the highest area under the curve (AUC 0.820), compared to cADC and rADC values. Conclusion: The Node-RADS score provides a standardized LNs assessment, enhancing diagnostic accuracy in CC patients. Its ease of use and high inter-observer concordance support its clinical utility. ADC measurement of LNs shows promise as an additional tool for optimizing patient diagnostic evaluation.

To evaluate the diagnostic performance of Node-RADS score using magnetic resonance imaging (MRI) in predicting lymph node involvement (LNI) in patients with endometrial cancer (EC). Additionally, the applicability of the Node-RADS score was evaluated by three readers with different levels of experience in pelvic imaging. Finally, this study investigated the correlation between the Node-RADS score and the extent of myometrial invasion, histological type, lympho vascular invasion (LVI) and molecular subtype. Out of 108 cases, 82 patients with histologically confirmed locally advanced EC met the inclusion criteria for retrospective analysis. LNI risk was assessed for each pelvic lymph node station using a Node-RADS score (1-5). Diagnostic accuracy was determined by comparing scores to histologic findings, considered as the gold standard. Three independent readers with different experience levels assigned scores. The Node-RADS score strongly correlated with histologically confirmed LNI (AUC: 0.832). A cutoff of Node-RADS ≥ 3 optimally detected metastatic lymph nodes, with 85.71 % sensitivity and 76.47 % specificity. Interobserver agreement was high, with κ values of 0.86 (senior vs. junior reader 1) and 0.70 (senior vs. junior reader 2). A significant positive correlation was found between Node-RADS score and myometrial invasion as well as LVI. Node-RADS score is a reliable, standardized tool for assessing LN stations and enhancing diagnostic accuracy in locoregional staging of EC.

Pelvic inflammatory disease (PID) encompasses a broad range of infection-induced inflammatory disorders of the female upper genital tract, commonly caused by ascending sexually transmitted infections. Diagnosis is often challenging because of nonspecific or absent symptoms and the overlap with other pelvic pathologies. While clinical and laboratory assessments are essential, cross-sectional imaging plays a pivotal role, especially in complicated, atypical, or equivocal cases. This review focuses on the typical and atypical imaging features of PID and highlights the crucial roles of computed tomography (CT) and magnetic resonance imaging (MRI) in its diagnostic evaluation. CT is frequently employed in emergency settings because of its widespread availability and ability to detect acute complications such as tubo-ovarian abscesses (TOA), peritonitis, or Fitz-Hugh–Curtis syndrome. However, it is limited by ionizing radiation and suboptimal soft-tissue contrast. MRI provides superior tissue characterization and multiplanar imaging without radiation exposure. When combined with diffusion-weighted imaging (DWI), MRI achieves high diagnostic accuracy, particularly in differentiating PID from other entities such as endometriosis, adnexal tumors, and gastrointestinal or urinary tract diseases. This review also addresses PID in specific clinical contexts, including post-partum infection, post-assisted reproductive technologies (ART), intrauterine device (IUD) use, and chronic or recurrent forms. A comprehensive, multimodal imaging approach integrated with clinical findings is essential for timely diagnosis, effective treatment, and prevention of severe reproductive sequelae.

To evaluate the feasibility, interobserver reproducibility, reporting efficiency, and perceived clinical impact of the Deep Pelvic Endometriosis Index (dPEI) when implemented as part of structured MRI reporting in routine clinical practice. This retrospective single-center study included 100 consecutive women with surgically confirmed deep pelvic endometriosis who underwent preoperative 3-Tesla pelvic MRI. Three radiologists with different levels of experience (2, 4, and 20 years) independently reviewed all examinations using a structured MRI report based on the dPEI. Interobserver agreement for the global score was assessed using the intraclass correlation coefficient (ICC), while compartment-specific agreement was evaluated using Cohen's and Fleiss' κ statistics. Reporting time was recorded for each reader. Perceived clinical utility and practical limitations were assessed through a structured questionnaire administered to 10 clinicians and 10 surgeons involved in multidisciplinary endometriosis care. The dPEI was applicable across all cases and readers. Interobserver agreement for the global score was low-to-moderate (ICC = 0.44) and was influenced by reader experience, with higher concordance between senior and intermediate radiologists than between pairs including the junior reader. Agreement was higher in central compartments and lower in lateral and extrapelvic compartments. Reporting time decreased with increasing reader experience and demonstrated a clear learning effect, remaining below 30 min for all readers. Clinicians rated the dPEI as useful for disease stratification and multidisciplinary communication, whereas surgeons reported limited usefulness for advanced surgical planning, mainly due to the lack of quantitative descriptors. The dPEI is a feasible and intuitive MRI-based staging system whose performance is influenced by reader experience, while remaining easy to apply and associated with a rapid learning curve. These characteristics support its use as a complementary structured reporting tool in routine clinical practice and suggest a potential role as an educational and training instrument in deep pelvic endometriosis imaging.