Articles tagged with Radiology
Researchers at Karolinska Institutet have found that one AI algorithm is as accurate as the average radiologist in identifying breast cancer from mammograms. The study compared three AI algorithms and showed significant differences between them, with one outperforming others and rivaling human detection accuracy.
A study found that electronic consultations between primary providers and radiologists improved patient care by reducing unnecessary imaging tests. The platform provided a secure method for PCPs to ask specialist questions, promoting collaboration and improving outcomes.
A study found that 11.4% of second-opinion radiology reports were ignored by clinicians, with sonography and pediatrics having the highest rates. The cost of these ignored reports could be substantial, estimated at €53,700 or approximately $63,427.
A new study found a significant increase in domestic violence injuries during the COVID-19 pandemic, with more severe injuries reported despite fewer patients seeking help. The study suggests that fear of contracting infection and limited access to ambulatory sites may be preventing victims from reporting abuse.
A new study published in Radiology found an alarming rise in intimate partner violence (IPV) during the COVID-19 pandemic, with a significant increase in physical injuries and severe signs of abuse. The study suggests that victims may have delayed seeking care due to fear of COVID-19.
A pilot study found that Snapchat improves diagnostic performance among radiology residents, who performed better on the platform than with traditional classroom screens. The results suggest a promising novel training method to enhance recognition of life-threatening imaging diagnoses.
The COVID-19 pandemic has had a substantial impact on private radiology practices, with examination volumes decreasing by 40%-90%. To mitigate losses, practices are adjusting service availability, staffing, compensation, and seeking additional revenues.
The study found that focusing on subjects less likely to remain in the program, such as smokers and those with negative low-dose CT exams, improves cost-effectiveness and maximizes societal benefits. Adherence increased progressively with higher Lung-RADS categories, and having smoked previously was a significant predictor of adherence.
A study found that non-white patients with COVID-19 have more severe disease on chest X-rays, increasing the likelihood of adverse outcomes. Limited English proficiency and socioeconomic factors contribute to these disparities.
A study found that cardiac CT exams can effectively screen for osteoporosis by measuring thoracic spine bone mineral density, which is strongly associated with fracture risk. This non-invasive method can guide preventive measures and treatment decisions without adding time or radiation to the exam.
The study highlights social media's benefits in Radiology, including educational content dissemination, professional networking, and collaboration. However, it also warns of challenges, such as maintaining patient privacy and avoiding e-professionalism.
The American Journal of Roentgenology is implementing an author-centered peer-review system to streamline the submission process and provide rapid initial decisions. The journal is also rapidly publishing accepted manuscripts as Online First, expediting timely research for radiologists and allied scientists.
A recent study published in Radiology found that prostate MRI quality is highly variable across institutions, with a significant impact on cancer detection and treatment outcomes. The study's findings suggest that improved standardization and training are needed to ensure consistent imaging results and better patient care.
A new case series published in Radiology examines the spectrum of imaging findings in children with Multisystem Inflammatory Syndrome in Children (MIS-C) associated with prior exposure or infection to SARS-CoV-2. The study identified a pattern of imaging findings including airway inflammation and pulmonary edema.
A new multi-institutional study found patterns of abnormal brain MRI findings in patients with severe COVID-19, including signal abnormalities in the medial temporal lobe and non-confluent multifocal white matter hyperintense lesions. The study suggests that imaging and neurological follow-up are crucial to evaluate prognosis.
A house call model using interventional radiology treatments in patients' homes improved access to care, reducing emergency department use by 77% and hospital readmissions by 50%. The model provides specialized care to elderly homebound patients with chronic illnesses, preventing complications and delaying urgent visits.
A new nonsurgical treatment decreases errant blood flow in the shoulder to quickly reduce pain and improve function in patients with adhesive capsulitis, also known as 'frozen shoulder'. The treatment was successfully completed in 16 patients whose symptoms had not responded to conservative treatment over 30 days.
A novel treatment for advanced mesothelioma has been shown to be safe and effective, with a 70.3% disease control rate and median overall survival rate of 8.5 months. The transarterial chemoperfusion treatment may improve the quality of life for patients who have few treatment options.
Researchers successfully tested a holographic guidance system in a clinical trial, demonstrating its feasibility and potential benefits for liver tumor ablation. The technology improved visualization of the tumor and surrounding structures, allowing for faster localization and increased treating-physician confidence.
Diagnostic ultrasound services have implemented several updates to prevent COVID-19 transmission to frontline providers. Segregated workflows and protocols ensure patient screening, staff isolation, and proper equipment handling to minimize the risk of nosocomial transmission.
A minimally invasive procedure destroying cancer cells by freezing them is as effective as surgery for treating early-stage kidney cancer. Cryoablation offers similar 10-year survival rates with a lower rate of complications compared to traditional surgical options.
The American Roentgen Ray Society reaffirms its mission to improve health through a community of allies dedicated to knowledge and quality care for all. Recent events highlighting racial injustice in the US healthcare system have prompted ARRS to reiterate its commitment to addressing these inequities.
To minimize risks, interventional radiologists propose a tiered approach for delaying cross-sectional procedures during the pandemic. Procedures should be categorized into urgent, within 2 weeks, or delayed for 2-6 months based on clinical circumstances.
Remote reading of imaging studies on home PACS workstations helps protect vulnerable radiologists and patients from COVID-19, while ensuring seamless interpretation capabilities in emergency scenarios. The study highlights the challenges and solutions in implementing teleradiology, including workstation assignments and workflow redesign.
Radiologists at Shanghai Jiao Tong University Medical School implemented strict disinfection measures, including air disinfector use and ultraviolet light, in CT examination rooms to reduce COVID-19 transmission risk. Radiographers followed personal protective equipment protocols, with separate zones for clean and contaminated areas.
Researchers used chest X-rays to identify patients at higher risk of severe illness from COVID-19. A unique scoring system evaluated lung patterns, predicting outcomes and guiding treatment for high-risk patients.
A retrospective study found bowel abnormalities in 31% of COVID-19 patients, with thickening and ischemic findings more common in ICU patients. The study suggests that SARS-CoV-2 may play a role in causing bowel or vascular injury, and further research is needed to clarify the cause of these findings.
The RSNA COVID-19 Task Force has published documents on COVID-19 surge preparedness and post-COVID-19 preparedness for radiology departments. These resources provide tools and information to help radiologists manage the COVID-19 outbreak, including guidance on departmental policies, surge and post-COVID preparedness insights.
A recent study found that artificial intelligence can provide results comparable to lung function tests in diagnosing emphysema and classifying its severity. The AI system can automatically analyze chest scans and create a 3D model of the patient's lungs, helping doctors better communicate with patients and track treatment progress.
Recent reports show a strong association between elevated D-dimer levels and poor prognosis in patients with COVID-19. Microvascular thrombotic processes may play a role in respiratory failure, suggesting a new severe infectious lung disease with no proven therapies.
A new deep learning model accurately localises the exact location of mandibular canals in lower jaws, making dental implant operations faster and more efficient. The model surpasses existing methods, such as statistical shape models, and performs equally fast and accurately every time.
A new approach to combine CT and MRI data in one 3D image helps solve uncertain findings in coronary artery disease diagnosis. The technique correlates specific stenoses with possible cardiac scar tissue and ischemia, guiding revascularization procedures.
The Fleischner Society statement provides guidance on the use of chest imaging in COVID-19 management, recommending its use in patients with worsening respiratory status or moderate to severe features. The panel also found that CT is appropriate in patients with functional impairment and/or hypoxemia after recovery from COVID-19.
A clinical research study at UC San Diego Health is using artificial intelligence to analyze lung imaging data for COVID-19 patients. The AI algorithm has provided unique insights into over 2,000 images, helping physicians identify early signs of pneumonia and potentially saving lives.
A new AI technique detects acute ischemic stroke lesions on MRIs with high accuracy, outperforming expert drawn gold standard. The fully automated approach reduces workflow time and operator bias in lesion segmentation.
A new study found that artificial intelligence (AI) can accurately identify patients at risk of osteoporosis and fractures by analyzing electronic radiology reports, outperforming traditional manual methods. The AI tool, XRAIT, detected a significant number of major fractures, improving patient outcomes and reducing the burden of illness.
A new online platform, CovED, aims to improve COVID-19 diagnosis by providing healthcare workers with rapid training and image-based diagnostic tools. Developed by DetectED-X, the platform can be accessed for free and is supported by leading corporations and healthcare experts.
A study found that per capita radiation exposure in the US decreased by 20% between 2006 and 2016, mainly due to a decline in nuclear medicine procedures. Meanwhile, CT scans increased but saw a small drop in effective dose thanks to advancements in dose modulation technology.
A panel of experts outlines priorities for handling COVID-19 cases, including early detection, limiting virus exposure, safety precautions, and training. Radiology departments must continue to plan and prepare for future outbreaks and pandemics.
The article highlights key areas of review for diagnostic radiologists, vascular and interventional radiologists, nuclear medicine and molecular imaging specialists, as well as radiographers and nursing units. It emphasizes the need for rapid sharing of accurate information, infection prevention, and control knowledge, and emotional ma...
A recent study published in the American Journal of Roentgenology found that chest CT scans have a low misdiagnosis rate for COVID-19 and can standardize imaging features. However, CT remains limited for distinguishing between specific viruses.
A combination of AI algorithms and radiologist interpretations improved mammogram accuracy, avoiding unnecessary tests for 10% false positives. This approach has the potential to increase detection value and make healthcare more sustainable.
A study published in Radiology analyzed chest CT images and X-rays of 14 teenagers with EVALI, revealing characteristic ground-glass opacity and subpleural sparing. The findings suggest that CT imaging is crucial for early diagnosis and timely management of the condition in pediatric patients
A recent study found that chest CT imaging has a sensitivity of 98% for detecting COVID-19, compared to RT-PCR's 71%, making it a reliable and practical method for early diagnosis. This is particularly important given the highly contagious nature of the virus.
Mount Sinai physicians analyzed chest CT scans of Chinese COVID-19 patients, identifying specific patterns in lung disease as it develops over a week and a half. The study could lead to quicker diagnosis and prompt isolation in early stages.
A meta-analysis of severe frostbite injuries found promising results using intraarterial and intravenous tissue plasminogen activator to reduce amputation rates. The study included 209 patients treated with thrombolytic therapy, resulting in a salvage rate of 76%.
Researchers describe key chest CT imaging findings in Wuhan coronavirus patients, highlighting bilateral ground-glass and consolidative pulmonary opacities. The study's findings suggest that lung cavitation, discrete nodules, and lymphadenopathy are characteristically absent in cases of 2019-nCoV.
A study published in Radiology found that patients with abdominal aortic aneurysms and blood clots on the aorta wall experience faster growth and increased rupture risk. The researchers suggest adjusting imaging follow-up schedules for these patients to reduce the risk of rupture.
Abnormal chest CT findings in patients with EVALI typically show diffuse lung injury with sparing of the periphery. Prompt medical treatment can decrease severity, but the exact cause of EVALI remains unclear. Long-term vaping risks pose concerns for nicotine and THC addiction, cardiovascular disease, and chronic pulmonary injury.
A team of researchers from Stanford University has developed a quantitative framework to sonographically differentiate between benign and malignant thyroid nodules. The framework achieved AUC values comparable to those of expert radiologists, suggesting its potential for establishing a fully automated system of thyroid nodule triage.
New statements from ACR and NKF clarify risk of contrast-induced acute kidney injury and provide recommendations for use of intravenous contrast media in patients with varying degrees of impaired kidney function. The authors emphasize the need for prospective controlled data to further understand the risk.
A deep learning method using a convolutional neural network (CNN) accurately differentiates between malignant and benign solid masses in small renal masses on contrast-enhanced CT scans. The corticomedullary phase showed the highest AUC value, indicating its effectiveness in malignancy prediction.
The Journal Healthcare Transformation: Artificial Intelligence, Automation, and Robotics explores the challenges and opportunities for integrating technology into consumer healthcare. A recent article found that five telemedicine companies provided nearly half of telemental health visits, highlighting the need for coordinated care.
A new AI model developed by researchers can predict which women are at future risk of breast cancer with higher accuracy than existing models. The deep neural network-based approach has a lower false negative rate, indicating that it can identify women who would benefit from additional screening with MRI.
Researchers developed AI models for chest X-ray interpretation that can detect fractures, nodules, opacity and pneumothorax as effectively as experienced radiologists. The models were trained on large datasets and evaluated using a panel of radiologists to increase expert consensus and accuracy.
A new study analyzed X-ray and CT scans of people injured in e-scooter accidents, finding that the majority had injuries to their upper extremities, particularly wrists. The study emphasizes the importance of helmet use and speed limits to prevent such injuries.
A panel of medical professionals will discuss the public health impact of e-cigarette use, with a focus on radiologic findings associated with vaping-related lung injury. The session aims to educate radiologists about this critical public health issue and provide guidance on identifying cases.
A new study presents a minimally invasive procedure using focused ultrasound to reduce tremors and improve quality of life in patients with Parkinson's disease. The treatment, known as MRgFUS thalamotomy, shows substantial improvement in 95% of patients, with significant reductions in tremor severity and quality of life.
An interdisciplinary team developed a simple method to identify the most accurate experts in groups by analyzing decision similarity. The research tested it successfully in various fields, including radiology and geopolitics, and found that the method accurately predicted accuracy.
A deep convolutional neural network-based software improved radiologist detection of malignant lung nodules by 70.3%, reducing false positives to 0.18 per X-ray. The study suggests machine learning methods can help overcome challenges in detecting lung lesions on chest X-rays.