Search Tag: AI in radiology
2025 10 Nov
Referring physicians who rely on radiology services are central to how artificial intelligence is adopted in clinical pathways. A survey of licensed doctors in Germany explored how these clinicians view AI in radiological diagnosis, what they trust and which applications they value most. The sample included internists, surgeons and general pr1Read more
2025 16 Oct
Accurate preoperative classification of bone tumours as benign or malignant supports timely treatment selection and better outcomes, yet interpretation of radiographs can be challenging, particularly for less experienced clinicians. A machine learning approach integrating radiomics features from knee X-ray images with routine clinical data wa1Read more
2025 02 Sep
Artificial intelligence has become an integral part of radiology, particularly in high-demand settings such as emergency and teleradiology services. Non-contrast head CT scans are central to evaluating acute emergencies including intracranial haemorrhage, a condition with a 44% mortality rate within 30 days and a recovery rate of only 20% at 1Read more
2025 16 Aug
Artificial intelligence is increasingly shaping radiology, supporting detection, diagnosis and workflow efficiency. Its safe use, however, depends on robust evaluation of performance. Metrics must reflect clinical objectives, patient safety and real-world settings rather than theoretical accuracy alone. The European Society of Medical Imaging1Read more
2025 22 Jul
Large language models (LLMs) such as ChatGPT and Google Gemini are increasingly used to improve patient communication by simplifying complex medical content. In breast imaging, radiology reports are often filled with specialised terminology that can confuse patients, particularly when accessed online before physician consultation. Clearer lan1Read more
2025 20 Jul
The integration of artificial intelligence into breast cancer screening holds promise for addressing workforce shortages and enhancing diagnostic accuracy. While previous studies have demonstrated that AI decision support can improve sensitivity without compromising specificity or reading time, its influence on radiologists’ visual search str1Read more
2025 20 Jun
Radiology departments face increasing pressure to deliver timely and accurate reports. Compounding this challenge is a global shortage of radiologists, creating a pressing need for solutions that enhance productivity without compromising quality. Generative artificial intelligence has been recognised as a promising tool in this context, offer1Read more
2025 15 Jun
Cancer-associated cachexia (CAC) is a complex syndrome marked by irreversible muscle loss, with or without fat depletion, that cannot be remedied by nutrition alone. Affecting up to 70% of patients with cancer, CAC significantly worsens outcomes by accelerating disease progression, reducing tolerance to treatment and increasing mortality. Des1Read more
2025 13 May
The accurate and timely communication of critical findings from radiology reports is vital to effective patient care. Traditionally, this task has relied on human effort, with radiologists manually identifying and reporting urgent observations. However, radiology reports are often unstructured, inconsistent and lengthy, posing significant cha1Read more
2025 12 May
Incidental detection of pancreatic cystic lesions (PCLs) is increasingly common during abdominal imaging. While many of these lesions are benign, some carry the potential for malignancy, necessitating routine surveillance. The American College of Radiology (ACR) Incidental Findings Committee (IFC) provides a detailed algorithm to guide follow1Read more
2025 24 Apr
Artificial intelligence (AI) is revolutionising radiology, offering improved diagnostic precision and operational efficiency. Deep learning models, particularly within medical imaging, are at the forefront of this transformation. However, the increasing adoption of AI in radiology has introduced a complex sustainability paradox. While AI hold1Read more
2025 30 Mar
The integration of artificial intelligence in radiology has rapidly advanced, offering significant potential for predictive diagnostics and personalised care. However, the clinical reliability of these models hinges on their transparency and reproducibility, particularly through independent external validation. Despite growing emphasis on open s1Read more
2025 25 Mar
Image caption: Anonymised head and neck MRI scan for detailed medical imaging and diagnosis. Head and neck squamous cell carcinoma (HNSCC) is a common cancer that contributes to about 4.6% of global cancer deaths, with around 890,000 new cases each year. It primarily affects adults over 50, with a male-to-female incidence ratio of 2:1. Progno1Read more
2025 18 Mar
The European Society of Radiology (ESR) has provided key recommendations for implementing the European Union’s Artificial Intelligence Act in medical imaging. As AI transforms radiology, it's crucial to comply with this regulatory framework to ensure patient safety, enhance clinical effectiveness and uphold ethical standards. While AI innovat1Read more
2025 10 Mar
The implementation of low-dose computed tomography (LDCT) screening has significantly improved early lung cancer detection, leading to reduced mortality in high-risk populations. Early detection allows for timely treatment interventions. Many countries are moving toward national screening programmes, necessitating a structured and standardised app1Read more
2025 01 Mar
The session AI Integration in a Nutshell at the European Congress of Radiology explored key challenges and opportunities in AI adoption for medical imaging. Three experts—Willem Grootjans, Sergey Morozov and Kicky Gerhilde Van Leeuwen—shared insights on user expectations, workflow integration and AI marketplaces, highlighting the critical role o1Read more
2025 01 Mar
The session on nuclear medicine at the European Congress of Radiology showcased cutting-edge advancements in AI, radiomics, emerging imaging technologies and radioprotection. Experts highlighted how these innovations are transforming diagnostics, treatment precision and safety in nuclear medicine. AI and Radiomics: Transforming Nuclea1Read more
2025 28 Feb
The European Congress of Radiology session on interventional radiology brought together leading experts to explore key developments in the field. The discussions spanned emerging techniques in oncology, the evolving responsibilities of radiographers and the critical importance of safety and radioprotection during interventional procedures. At1Read more
2025 28 Feb
AI-Powered Ultrasound: Transforming Imaging with Practical Innovation Ultrasound technology is advancing rapidly, and the latest systems are integrating practical AI to enhance efficiency, accuracy, and usability. With workforce shortages and growing patient demand, these innovations are reshaping medical imaging for professionals worldwide1Read more
2025 28 Feb
AI-driven image reconstruction in radiology holds great promise for enhancing image quality and improving diagnostic capabilities. However, concerns persist regarding the reliability of AI models, the lack of clinical validation and the risk of unintentional distortions in medical imaging. At the European Congress of Radiology, experts examined ke1Read more
2025 28 Feb
At ECR 2025 , the session "Sustainability and Equity in Radiology AI: Ensuring a Fair Future" brought together leading experts to discuss the environmental and ethical challenges of artificial intelligence in radiology. As AI becomes increasingly integrated into clinical practice, its impact extends beyond efficiency and accuracy to broade1Read more
2025 27 Feb
Recent advancements in lung cancer imaging and treatment are transforming patient care, shifting towards precision medicine, multidisciplinary collaboration and cutting-edge technologies. Experts at the European Congress of Radiology highlighted key developments from the perspectives of oncologists, thoracic surgeons and radiologists, undersc1Read more
2025 25 Feb
Emergency radiology is integral to trauma care, providing rapid imaging assessments that guide critical treatment decisions. The increasing volume of imaging studies, coupled with the complexity of radiologic classification systems, presents challenges for radiologists who must navigate multiple frameworks to ensure accurate diagnoses. As the1Read more
2025 04 Feb
Colorectal cancer is a major cause of cancer-related mortality, but early detection and removal of adenomatous polyps can prevent its progression. Optical colonoscopy is the primary screening method, though CT colonography offers a non-invasive alternative with high sensitivity. However, CT colonography cannot reliably differentiate between a1Read more
2025 02 Feb
Artificial intelligence is revolutionising radiology, enhancing diagnostic accuracy, optimising workflow efficiency and improving patient care. However, integrating AI-generated insights into radiology reports presents challenges, particularly in ensuring consistency and interoperability across diverse healthcare systems. Traditional reportin1Read more
2024 30 Nov
Lung cancer remains the leading cause of cancer-related deaths globally, claiming millions of lives annually. One of the key contributors to this high mortality rate is the late-stage diagnosis of the disease, which drastically limits treatment options and reduces survival rates. Early detection, particularly in localised stages, significantl1Read more
2024 26 Nov
The convergence of artificial intelligence (AI) and cloud technology is transforming radiology, addressing the long-standing challenges of cost management, efficiency and diagnostic accuracy. With healthcare demands escalating and patient expectations changing, traditional imaging systems face increasing pressure to deliver improved outcomes with 1Read more
2024 26 Nov
Pneumothorax (PTX) detection is a critical aspect of diagnostic radiology, particularly in emergency and trauma care, where timely and accurate diagnoses are vital. Increasing imaging demands, coupled with a global shortage of radiologists, have created significant challenges for healthcare systems. Delays in diagnosis can lead to worsened ou1Read more
2024 16 Nov
Radiology is at the forefront of a digital revolution, with artificial intelligence (AI) transforming traditional diagnostic workflows. Among the most significant advancements is the application of large language models (LLMs) like OpenAI’s GPT-4. Equipped with its Advanced Data Analysis (ADA) capabilities, GPT-4 has the potential to aid radi1Read more
2024 03 Nov
Advances in medical imaging technology have revolutionised cardiovascular diagnostics, yet non-invasive techniques for assessing myocardial oxygenation remain a challenge. Traditional methods like positron emission tomography (PET) are effective but have limitations such as radiation exposure, cost and accessibility. Recently, an innovative a1Read more