Magnetic resonance imaging for diagnostic workup of embolic stroke of undetermined source: A systematic review.

BACKGROUND: Embolic stroke of undetermined source (ESUS) refers to ischemic stroke where the underlying cause of thromboembolism cannot be found despite the recommended diagnostic workup. Unidentified source of emboli hinders clinical decision-making and patient management with detrimental consequences on long-term prognosis. The rapid development and versatility of magnetic resonance imaging (MRI) make it an appealing addition to the diagnostic routine of patients with ESUS for the assessment of potential vascular and cardiac embolic sources. AIMS: To review the use of MRI in the identification of cardiac and vascular embolic sources in ESUS and to assess the reclassification value of MRI examinations added to the conventional workup of ESUS. SUMMARY OF REVIEW: We reviewed the use of cardiac and vascular MRI for the identification of a variety of embolic sources associated with ESUS, including atrial cardiomyopathy, left ventricular pathologies, and supracervical atherosclerosis in carotid and intracranial arteries and in distal thoracic aorta. The additional reclassification after MRI examinations added to the workup of patients with ESUS ranged from 6.1% to 82.3% and varied depending on the combination of imaging modalities. CONCLUSION: MRI techniques allow us to identify additional cardiac and vascular embolic sources and may further decrease the prevalence of patients with the diagnosis of ESUS.

Diagnosis and Treatment of Post-Prostatectomy Lymphedema: What's New?

Lymphedema is a chronic progressive disorder that significantly compromises patients' quality of life. In Western countries, it often results from cancer treatment, as in the case of post-radical prostatectomy lymphedema, where it can affect up to 20% of patients, with a significant disease burden. Traditionally, diagnosis, assessment of severity, and management of disease have relied on clinical assessment. In this landscape, physical and conservative treatments, including bandages and lymphatic drainage have shown limited results. Recent advances in imaging technology are revolutionizing the approach to this disorder: magnetic resonance imaging has shown satisfactory results in differential diagnosis, quantitative classification of severity, and most appropriate treatment planning. Further innovations in microsurgical techniques, based on the use of indocyanine green to map lymphatic vessels during surgery, have improved the efficacy of secondary LE treatment and led to the development of new surgical approaches. Physiologic surgical interventions, including lymphovenous anastomosis (LVA) and vascularized lymph node transplant (VLNT), are going to face widespread diffusion. A combined approach to microsurgical treatment provides the best results: LVA is effective in promoting lymphatic drainage, bridging VLNT delayed lymphangiogenic and immunological effects in the lymphatic impairment site. Simultaneous VLNT and LVA are safe and effective for patients with both early and advanced stages of post-prostatectomy LE. A new perspective is now represented by the combination of microsurgical treatments with the positioning of nano fibrillar collagen scaffolds (BioBridgeTM) to favor restoring the lymphatic function, allowing for improved and sustained volume reduction. In this narrative review, we proposed an overview of new strategies for diagnosing and treating post-prostatectomy lymphedema to get the most appropriate and successful patient treatment with an overview of the main artificial intelligence applications in the prevention, diagnosis, and management of lymphedema.

Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?

Due to its widespread availability, low cost, feasibility at the patient's bedside and accessibility even in low-resource settings, chest X-ray is one of the most requested examinations in radiology departments. Whilst it provides essential information on thoracic pathology, it can be difficult to interpret and is prone to diagnostic errors, particularly in the emergency setting. The increasing availability of large chest X-ray datasets has allowed the development of reliable Artificial Intelligence (AI) tools to help radiologists in everyday clinical practice. AI integration into the diagnostic workflow would benefit patients, radiologists, and healthcare systems in terms of improved and standardized reporting accuracy, quicker diagnosis, more efficient management, and appropriateness of the therapy. This review article aims to provide an overview of the applications of AI for chest X-rays in the emergency setting, emphasizing the detection and evaluation of pneumothorax, pneumonia, heart failure, and pleural effusion.

Artificial Intellgence in the Era of Precision Oncological Imaging.

Rapid-paced development and adaptability of artificial intelligence algorithms have secured their almost ubiquitous presence in the field of oncological imaging. Artificial intelligence models have been created for a variety of tasks, including risk stratification, automated detection, and segmentation of lesions, characterization, grading and staging, prediction of prognosis, and treatment response. Soon, artificial intelligence could become an essential part of every step of oncological workup and patient management. Integration of neural networks and deep learning into radiological artificial intelligence algorithms allow for extrapolating imaging features otherwise inaccessible to human operators and pave the way to truly personalized management of oncological patients.Although a significant proportion of currently available artificial intelligence solutions belong to basic and translational cancer imaging research, their progressive transfer to clinical routine is imminent, contributing to the development of a personalized approach in oncology. We thereby review the main applications of artificial intelligence in oncological imaging, describe the example of their successful integration into research and clinical practice, and highlight the challenges and future perspectives that will shape the field of oncological radiology.

Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future.

Lung cancer is one of the malignancies with higher morbidity and mortality. Imaging plays an essential role in each phase of lung cancer management, from detection to assessment of response to treatment. The development of imaging-based artificial intelligence (AI) models has the potential to play a key role in early detection and customized treatment planning. Computer-aided detection of lung nodules in screening programs has revolutionized the early detection of the disease. Moreover, the possibility to use AI approaches to identify patients at risk of developing lung cancer during their life can help a more targeted screening program. The combination of imaging features and clinical and laboratory data through AI models is giving promising results in the prediction of patients' outcomes, response to specific therapies, and risk for toxic reaction development. In this review, we provide an overview of the main imaging AI-based tools in lung cancer imaging, including automated lesion detection, characterization, segmentation, prediction of outcome, and treatment response to provide radiologists and clinicians with the foundation for these applications in a clinical scenario.

Nontraumatic orbital emergencies: a pictorial essay - CT and MRI features for an imaging findings-based approach.

Orbital imaging plays a pivotal role in each hospital with an Ophthalmological Emergency Department. Unenhanced orbital computed tomography (CT) usually represents the first-line tool for the assessment of nontraumatic orbital emergencies, thanks to its quick execution, wide availability, high resolution, and availability of multiplanar reformats/reconstructions. Magnetic resonance imaging (MRI) is an essential tool that allows characterization and a better understanding of the anatomical involvement of different disorders due to its excellent contrast resolution and ability to study the visual pathways, even if, unfortunately, it is not always available in the emergency setting. It represents the first imaging choice in pediatric patients, due to the absence of ionizing radiation. When available, CT and MRI are often used together to diagnose, assess the extent, and provide treatment plans for various orbital nontraumatic emergencies, including infective, inflammatory, vascular, and neoplastic diseases. Familiarity with the imaging appearances of these disorders helps the radiologists to establish the correct diagnosis in the emergency setting, which contributes to timely clinical management. This pictorial essay provides a description of the clinical presentation and imaging findings of nontraumatic orbital emergencies.