Objective: To report an overview and update on Artificial Intelligence (AI) and COVID-19 using chest Computed Tomography (CT) scan and chest X-ray images (CXR). Machine Learning and Deep Learning Approaches for Diagnosis and Treatment were identified. Methods: Several electronic datasets were analyzed. The search covered the years from January 2019 to June 2021. The inclusion criteria were studied evaluating the use of AI methods in COVID-19 disease reporting performance results in terms of accuracy or precision or area under Receiver Operating Characteristic (ROC) curve (AUC). Results: Twenty-two studies met the inclusion criteria: 13 papers were based on AI in CXR and 10 based on AI in CT. The summarized mean value of the accuracy and precision of CXR in COVID-19 disease were 93.7% ± 10.0% of standard deviation (range 68.4–99.9%) and 95.7% ± 7.1% of standard deviation (range 83.0–100.0%), respectively. The summarized mean value of the accuracy and specificity of CT in COVID-19 disease were 89.1% ± 7.3% of standard deviation (range 78.0–99.9%) and 94.5 ± 6.4% of standard deviation (range 86.0–100.0%), respectively. No statistically significant difference in summarized accuracy mean value between CXR and CT was observed using the Chi square test (p value > 0.05). Conclusions: Summarized accuracy of the selected papers is high but there was an important variability; however, less in CT studies compared to CXR studies. Nonetheless, AI approaches could be used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, COVID-19 diagnosis, and disease management.

In the last decades, nanotechnology has been used in a wide range of biomedical applications, both diagnostic and therapeutic. In this scenario, imaging techniques represent a fundamental tool to obtain information about the properties of nanoconstructs and their interactions with the biological environment in preclinical and clinical settings. This paper reviews the state of the art of the application of magnetic resonance imaging in the field of nanomedicine, as well as the use of nanoparticles as diagnostic and therapeutic tools, especially in cancer, including the characteristics that hinder the use of nanoparticles in clinical practice.

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and nodal staging of RC by using morphological criteria. The actual dimensional and morphological criteria for nodal assessment present several limitations in terms of sensitivity and specificity. For these reasons, several different techniques, such as Diffusion Weighted Imaging (DWI), Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Dynamic Contrast Enhancement (DCE) in MRI have been introduced but still not fully validated. Positron Emission Tomography (PET)/CT plays a pivotal role in the assessment of LNs; more recently PET/MRI has been introduced. The advantages and limitations of these imaging modalities will be provided in this narrative review. The second part of the review includes experimental techniques, such as iron-oxide particles (SPIO), and dual-energy CT (DECT). Radiomics analysis is an active field of research, and the evidence about LNs in RC will be discussed. The review also discusses the different recommendations between the European and North American guidelines for the evaluation of LNs in RC, from anatomical considerations to structured reporting.

Extended reality (XR) technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), hold transformative potential for radiology. This review examines the current applications, benefits, limitations, and future prospects of XR in radiology, with a focus on education, diagnostics, interventional procedures, and patient interaction. A comprehensive literature search of PubMed, Scopus, and Web of Science databases identified relevant publications from 1992 to 2024. Key studies were selected for detailed discussion. XR technologies enhance radiology education by offering immersive learning experiences that improve the proficiency and confidence of professionals. In diagnostics, XR improves the accuracy and efficiency of ultrasound and CT imaging and aids in precise patient positioning. For interventional radiology, XR provides valuable tools for training and real-time procedural planning, leading to better patient outcomes. Additionally, XR improves patient–doctor interactions, reducing anxiety and enhancing the consent process. Despite challenges such as high costs, technical limitations, and the need for extensive clinical validation, the potential benefits of XR underscore its value as a significant tool in radiology. Addressing these challenges will be essential for the widespread adoption and integration of XR in radiology, ensuring its potential benefits are fully realized. This review highlights the transformative impact of XR technologies on radiology, emphasizing the need for further research and development to harness their full capabilities and improve patient care.

Tumour ablation is a strategy of treatment of hepatic tumours in patients with small hepatocellular carcinoma (HCC) (<3 cm) or in patients unfit for surgical resection. Moreover, tumor ablation can be used as an adjuvant therapy or may be used in association with resection in case of patients with poor functional liver disease. These types of treatment usually could be performed percutaneously under image guidance. The most clinically verified and used ablation modalities are Radiofrequency Ablation (RFA) and microwave ablation (MWA). However, despite both of them are considered minimally invasive techniques, they could be related to post-procedural complications. The International Working Group on Image-Guided Tumor and the Society of Interventional Radiology (SIR) identified major and minor post-ablative complications. Major complications, as vascular complications, occur in 2.2% to 3.1% of cases and include all the high risk pathological conditions which could increase the level of care or result in hospital admission or substantially prolonged hospital stay (SIR classifications C–E). Minor complications, as biliary complications, occur in 5% to 8.9% and include self-limiting conditions that are considered to be of low risk for the patient’s outcome. The purpose of this review is to summarise the main pathological ultrasound (US) and Computed Tomography (CT) findings, that may arise after ablative treatment. To simplify the analysis, the pathological pictures are divided according to the site of damage into vascular, biliary and extrahepatic complications.

Inflammatory bowel disease (IBD) is the term used to identify a form of chronic inflammation of the gastrointestinal tract that primarily contemplates two major entities: ulcerative colitis (UC) and Crohn’s disease (CD). The classic signs are abdominal pain and diarrhoea that correlate with the localization of gastro-enteric disease, although in this pathology extraintestinal symptoms may coexist. The diagnosis of CD relies on a synergistic combination of clinical, laboratory (stool and biochemical), cross-sectional imaging evaluation, as well as endoscopic and histologic assessments. The purpose of this paper is to prove the role of imaging in the diagnosis and follow-up of patients with CD with particular focus on recent innovations of magnetic resonance enterography (MRE) as a pivotal diagnostic tool, analysing the MRE study protocol and imaging features during the various phases of disease activity and its complications.