Pelvic ring fractures are common in high-energy blunt trauma, especially in traffic accidents. These types of injuries have a high rate of morbidity and mortality, due to the common instability of the fractures, and the associated intrapelvic vascular and visceral complications. Computed tomography (CT) is the gold standard technique in the evaluation of pelvic trauma because it can quickly and accurately identify pelvic ring fractures, intrapelvic active bleeding, and lesions of other body systems. To properly guide the multidisciplinary management of the polytrauma patient, a classification criterion is mandatory. In this review, we decided to focus on the Young and Burgess classification, because it combines the mechanism and the stability of the fractures, helping to accurately identify injuries and related complications.

Background: Rectal cancer is a major mortality cause in the United States (US), and its treatment is based on individual risk factors for recurrence in each patient. In patients with rectal cancer, accurate assessment of response to chemoradiotherapy has increased in importance as the variety of treatment options has grown. In this scenario, a controversial non-operative approach may be considered in some patients for whom complete tumor regression is believed to have occurred. The recommended treatment for locally advanced rectal cancer (LARC, T3-4 ± N+) is total mesorectal excision (TME) after neoadjuvant chemoradiotherapy (nCRT). Magnetic resonance imaging (MRI) has become a standard technique for local staging of rectal cancer (tumor, lymph node, and circumferential resection margin [CRM] staging), in both the US and Europe, and it is getting widely used for restaging purposes. Aim: In our study, we aimed to use an MRI radiomic model to identify features linked to the different responses of chemoradiotherapy of rectal cancer before surgery, and whether these features are helpful to understand the effectiveness of the treatments. Methods: We retrospectively evaluated adult patients diagnosed with LARC who were subjected to at least 2 MRI examinations in 10–12 weeks at our hospital, before and after nCRT. The MRI acquisition protocol for the 2 exams included T2 sequence and apparent diffusion coefficient (ADC) map. The patients were divided into 2 groups according to the treatment response: complete or good responders (Group 1) and incomplete or poor responders (Group 2). MRI images were segmented, and quantitative features were extracted and compared between the two groups. Features that showed significant differences (SF) were then included in a LASSO regression method to build a radiomic-based predictive model. Results: We included 38 patients (26 males and 12 females), who are classified from T2 and T4 stages in the rectal cancer TNM. After the nCRT, the patients were divided into Group 1 (13 patients), complete or good responders, and Group 2 (25 patients), incomplete or poor responders. Analysis at baseline generated the following significant features for the Mann–Whitney test (out of a total of 107) for each sequence. Also, the analysis at the end of the follow-up yielded a high number of significant features for the Mann–Whitney test (out of a total of 107) for each image. Features selected by the LASSO regression method for each image analyzed; ROC curves relative to each model are represented. Conclusion: We developed an MRI-based radiomic model that is able to differentiate and predict between responders and non-responders who went through nCRT for rectal cancer. This approach might identify early lesions with high surgical potential from lesions potentially resolving after medical treatment.

Despite differences in pathological analysis, focal liver lesions are not always distinguishable in contrast-enhanced magnetic resonance imaging (MRI), contrast-enhanced computed tomography (CT), and positron emission tomography (PET). This issue can cause problems of differential diagnosis, treatment, and follow-up, especially in patients affected by HBV/HCV chronic liver disease or fatty liver disease. Radiomics is an innovative imaging approach that extracts and analyzes non-visible quantitative imaging features, supporting the radiologist in the most challenging differential diagnosis when the best-known methods are not conclusive. The purpose of this review is to evaluate the most significant CT and MRI texture features, which can discriminate between the main benign and malignant focal liver lesions and can be helpful to predict the response to pharmacological or surgical therapy and the patient’s prognosis.

An adrenal mass discovered incidentally during imaging for unrelated clinical reasons is termed an “adrenal incidentaloma” (AI). AIs can be categorized as primary or metastatic, functioning or non-functioning, and benign or malignant. The primary goal of radiological evaluation is to exclude malignancy by differentiating between benign and malignant lesions. Most AIs are benign, with adenomas and macronodular bilateral adrenal hyperplasia being the most common types. Less common benign lesions include myelolipomas, pheochromocytomas, cysts, and hematomas. Malignant adrenal masses account for less than 10% of cases and often include metastases from other cancers or primary adrenal diseases, such as adrenocortical carcinoma and pheochromocytoma. Computed Tomography (CT) remains the gold standard for diagnosing adrenal incidentalomas, while Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) are utilized for indeterminate cases. Additionally, innovative imaging techniques such as texture analysis are gaining importance, as they can assess quantitative parameters that are not visible to the human eye. This review aims to provide an updated overview of malignant adrenal lesions on CT and MRI, emphasizing key imaging features suspicious for malignancy to aid in distinguishing between benign and malignant lesions. Furthermore, it highlights the growing role of radiomics as a supportive tool for radiologists.