The integration of artificial intelligence (AI) into clinical practice, particularly within radiology, nuclear medicine and radiation oncology, is transforming diagnostic and therapeutic processes. AI‐driven tools, especially in deep learning and machine learning, have shown remarkable potential in enhancing image recognition, analysis and decision‐making. This technological advancement allows for the automation of routine tasks, improved diagnostic accuracy, and the reduction of human error, leading to more efficient workflows. Moreover, the successful implementation of AI in healthcare requires comprehensive education and training for young clinicians, with a pressing need to incorporate AI into residency programmes, ensuring that future specialists are equipped with traditional skills and a deep understanding of AI technologies and their clinical applications. This includes knowledge of software, data analysis, imaging informatics and ethical considerations surrounding AI use in medicine. By fostering interdisciplinary integration and emphasising AI education, healthcare professionals can fully harness AI's potential to improve patient outcomes and advance the field of medical imaging and therapy. This review aims to evaluate how AI influences radiology, nuclear medicine and radiation oncology, while highlighting the necessity for specialised AI training in medical education to ensure its successful clinical integration.

Acute pulmonary embolism (APE) represents a significant cause of morbidity and mortality worldwide, requiring rapid and precise diagnosis and effective therapy strategies. Computed Tomography Pulmonary Angiography (CTPA) is currently the gold standard technique for diagnosing PE; however, it presents some disadvantages, including limited sensitivity in detecting sub-segmental emboli and contrast-related risks. Recent advancements in imaging technologies, including Dual-Energy Computed Tomography (DECT) and Photon Counting (PC), offer improved sensitivity and specificity for APE and perfusion abnormalities detection. Digital Dynamic Radiography (DDR) perfusion imaging represents a novel imaging that allows pulmonary perfusion assessment without contrast medium administration, able to detect anomalies at the patient’s bedside, representing a promising advancement, particularly for critically ill or contrast-allergic patients. In parallel, interventional radiology has become integral to APE management, particularly for high-risk and intermediate–high-risk patients, with evolving intravascular treatment techniques such as catheter-directed thrombolysis, mechanical thrombectomy, and thrombus aspiration. This narrative review provides an overview of the latest developments in APE diagnostic imaging and interventional radiology, contextualizing them within current guideline recommendations for endovascular treatment.

Background: Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Percutaneous thermal ablation is an effective treatment, but standard ultrasound (US) guidance is limited in cases of inconspicuous nodules. Ultrasound fusion imaging (USFI), which overlays cross-sectional imaging onto real-time US is an emerging technique that improves tumor visibility and technical feasibility. This study reports real-life outcomes of USFI-guided microwave ablation (MWA) for HCC in two Italian centers. Materials and Methods: In this multicentric retrospective study, 56 patients with 73 poorly or non-visible HCC nodules underwent USFI-guided percutaneous MWA with no visibility or poor visibility on B-mode US. Technical success, complications, and local tumor control were evaluated, with follow-up imaging at 1 month and every 3 months thereafter. Results: Complete response (CR) at 1 month was observed in 78.1% of nodules, with residual disease (RD) more common in poorly visible nodules than non-visible nodules (18.1% vs. 4.2%, p = 0.019). During a median 13-month follow-up, local tumor progression (LTP) occurred in 9.6% of patients. No significant association was found with difficult tumor location. Conclusions: USFI-guided MWA is a safe and effective option for treating HCC nodules not adequately visualized with conventional US, expanding eligibility to complex cases.

Background: Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide. Percutaneous thermal ablation is an effective treatment, but standard ultrasound (US) guidance is limited in cases of inconspicuous nodules. Ultrasound fusion imaging (USFI), which overlays cross-sectional imaging onto real-time U is an emerging tech-nique which improves tumor visibility and technical feasibility. This study reports re-al-life outcomes of USFI-guided microwave ablation (MWA) for HCC in two Italian centres. Materials and Methods: In this multicentric retrospective study, 56 patients with 73 poorly or non-visible HCC nodules underwent USFI-guided percutaneous MWA with no visibility or poor visi-bility on B-mode US. Technical success, complications, and local tumor control were evaluated, with follow-up imaging at 1 month and every 3 months thereafter. Results: Complete response (CR) at 1 month was observed in 78.1% of nodules, with residual disease (RD) more common in poorly visible nodules than non-visible nodules (18.1% vs. 4.2%, p=0.019). During a median 13-month follow-up, local tumor progression (LTP) occurred in 9.6% of patients. No significant association was found with difficult tumor location. Conclusion: USFI-guided MWA is a safe and effective option for treating HCC nodules not ade-quately visualized with conventional US, expanding eligibility to complex cases.