Non-alcoholic fatty liver disease (NAFLD) is considered a predominant chronic liver disease worldwide and a component of metabolic syndrome. Due to its relationship with multiple organs, it is extremely complex to precisely define its pathogenesis as well as to set appropriate therapeutic and preventive strategies. Endocrine disruptors (EDCs) in general, and bisphenol A (BPA) in particular, are a heterogeneous group of substances, largely distributed in daily use items, able to interfere with the normal signaling of several hormones that seem to be related to type 2 diabetes mellitus (T2DM), obesity, and other metabolic disorders. It is reasonable to hypothesize a BPA involvement in the pathogenesis and evolution of NAFLD. However, its mechanisms of action as well as its burden in the vicious circle that connects obesity, T2DM, metabolic syndrome, and NAFLD still remain to be completely defined. In this review we analyzed the scientific evidence on this promising research area, in order to provide an overview of the harmful effects linked to the exposure to EDCs as well as to frame the role that BPA would have in all phases of NAFLD evolution.

Dermatologic ultrasonography applications are rapidly growing in all skin fields. Thanks to very high spatial resolution, high-frequency and ultra-high-frequency ultrasound can evaluate smaller structures, allowing us to improve diagnosis accuracy and disease activity. Moreover, they can guide treatment, such as drug injection, and assess therapy efficacy and complications. In this narrative review, we evaluated high-frequency ultrasound and ultra-high-frequency ultrasound in infections, inflammatory dermatoses, metabolic and genetic disorders, specific cutaneous structure skin disorders, vascular and external-agent-associated disorders, neoplastic diseases, and aesthetics.

Background: Primary cutaneous lymphoma (PCL) is a rare form of extranodal non-Hodgkin’s lymphoma characterized by malignant lymphocytes confined to the skin. Accurate diagnosis and staging are crucial for optimal management, yet radiological literature on imaging PCL remains limited. This study aims to delineate the imaging characteristics of PCLs using high and ultra-high frequency ultrasound (UHFUS) and proposes a classification system based on ultrasound findings. Methods: A cohort of 88 individuals with suspected PCL underwent high-resolution ultrasound (HRUS) and color Doppler examination of lesions. Lesions were categorized based on sonographic appearance, and subsequent histopathological assessment confirmed the diagnosis. Results: Ultrasound imaging revealed distinct patterns for primary cutaneous T-cell lymphomas (PCTCL) and primary cutaneous B-cell lymphomas (PCBCL), with characteristic features such as hypoechoic nodules, pseudonodular lesions, and dermal infiltration. Histopathological analysis confirmed the ultrasound findings, supporting the proposed classification system. Conclusions: Ultrasonography, particularly UHFUS, offers valuable insights into the imaging characteristics of primary cutaneous lymphomas, aiding the accurate diagnosis and assessment of treatment response. The proposed classification system based on ultrasound findings enhances the diagnostic approach to PCLs, and paves the way for improved patient care and management strategies.

Puropose: Preoperative T-staging in rectal cancer is essential for treatment planning, yet conventional MRI shows limited accuracy (~ 60–78). Our study investigates whether radiomic analysis of high-resolution T2-weighted MRI can non-invasively improve staging accuracy through a retrospective evaluation in a real-world surgical cohort. Methods: This single-center retrospective study included 200 patients (January 2024–April 2025) with pathologically confirmed rectal cancer, all undergoing preoperative high-resolution T2-weighted MRI within one week prior to curative surgery and no neoadjuvant therapy. Manual segmentation was performed using ITK‑SNAP, followed by extraction of 107 radiomic features via PyRadiomics. Feature selection employed mRMR and LASSO logistic regression, culminating in a Rad-score predictive model. Statistical performance was evaluated using ROC curves (AUC), accuracy, sensitivity, specificity, and Delong’s test. Results: Among 200 patients, 95 were pathologically staged as T2 and 105 as T3–T4 (55 T3, 50 T4). After preprocessing, 26 radiomic features were retained; key features including ngtdm_contrast and ngtdm_coarseness showed AUC values > 0.70. The LASSO-based model achieved an AUC of 0.82 (95% CI: 0.75–0.89), with overall accuracy of 81%, sensitivity of 78%, and specificity of 84%. Conclusion: Radiomic analysis of standard preoperative T2-weighted MRI provides a reliable, non-invasive method to predict rectal cancer T-stage. This approach has the potential to enhance staging accuracy and inform personalized surgical planning. Prospective multicenter validation is required for broader clinical implementation.

Background: Radiomics, an evolving paradigm in medical imaging, involves the quantitative analysis of tumor features and demonstrates promise in predicting treatment responses and outcomes. This study aims to investigate the predictive capacity of radiomics for genetic alterations in non-small cell lung cancer (NSCLC). Methods: This exploratory, observational study integrated radiomic perspectives using computed tomography (CT) and genomic perspectives through next-generation sequencing (NGS) applied to liquid biopsies. Associations between radiomic features and genetic mutations were established using the Area Under the Receiver Operating Characteristic curve (AUC-ROC). Machine learning techniques, including Support Vector Machine (SVM) classification, aim to predict genetic mutations based on radiomic features. The prognostic impact of selected gene variants was assessed using Kaplan–Meier curves and Log-rank tests. Results: Sixty-six patients underwent screening, with fifty-seven being comprehensively characterized radiomically and genomically. Predominantly males (68.4%), adenocarcinoma was the prevalent histological type (73.7%). Disease staging is distributed across I/II (38.6%), III (31.6%), and IV (29.8%). Significant correlations were identified with mutations of ROS1 p.Thr145Pro (shape_Sphericity), ROS1 p.Arg167Gln (glszm_ZoneEntropy, firstorder_TotalEnergy), ROS1 p.Asp2213Asn (glszm_GrayLevelVariance, firstorder_RootMeanSquared), and ALK p.Asp1529Glu (glcm_Imc1). Patients with the ROS1 p.Thr145Pro variant demonstrated markedly shorter median survival compared to the wild-type group (9.7 months vs. not reached, p = 0.0143; HR: 5.35; 95% CI: 1.39–20.48). Conclusions: The exploration of the intersection between radiomics and cancer genetics in NSCLC is not only feasible but also holds the potential to improve genetic predictions and enhance prognostic accuracy.

Metastasis to bone is a common occurrence among epithelial tumors, with a high incidence rate in the Western world. As a result, bone lesions are a significant burden on the healthcare system, with a high morbidity index. These injuries are often symptomatic and can lead to functional limitations, which in turn cause reduced mobility in patients. Additionally, they can lead to secondary complications such as pathological fractures, spinal cord compression, hypercalcemia, or bone marrow suppression. The treatment of bone metastases requires collaboration between multiple healthcare professionals, including oncologists, orthopedists, neurosurgeons, physiatrists, and radiotherapists. The primary objective of this study is to evaluate the correlation between two methods used to assess local control. Specifically, the study aims to determine if a reduction in the volume of bone lesions corresponds to better symptomatic control in the clinical management of patients, and vice versa. To achieve this objective, the study evaluates morphological criteria by comparing pre- and post-radiotherapy treatment imaging using MRI and RECIST 1.1 criteria. MRI without contrast is the preferred diagnostic imaging method, due to its excellent tolerance by patients, the absence of exposure to ionizing radiation, and the avoidance of paramagnetic contrast media side effects. This imaging modality allows for accurate assessment of bone lesions. One of the secondary objectives of this study is to identify potentially useful parameters that can distinguish patients into two classes: “good” and “poor” responders to treatment, as reported by previous studies in the literature. These parameters can be evaluated from the imaging examinations by analyzing morphological changes and radiomic features on different sequences, such as T1, STIR (short tau inversion recovery), and DWI-MRI (diffusion-weighted).