Researchers have developed a new AI model, AsymMirai, to predict 5-year breast cancer risk from mammograms. The model performs almost as well as the state-of-the-art Mirai, but with an interpretable reasoning process, making it a valuable adjunct to human radiologists.
A new study published in Radiology found that coronary artery calcium scoring can identify patients with a low risk of heart attacks or strokes. Patients with a zero coronary artery calcium score showed very low risk of major adverse cardiovascular events, suggesting they may not require invasive coronary angiography.
Researchers warn that AI tools used in radiology contribute to greenhouse gas emissions through energy consumption and data storage. To minimize these impacts, experts recommend sharing resources, selecting sustainable hardware, and using data compression techniques.
A new study published in Radiology found that ultrahigh-spatial-resolution photon-counting detector CT improved the assessment of coronary artery disease, allowing for reclassification to a lower disease category in 54% of patients. This technology has the potential to improve patient management and reduce unnecessary interventions.
A new study published in Radiology found that annual breast cancer screening beginning at age 40 and continuing until 79 results in the highest mortality reduction. The study analyzed Cancer Intervention and Surveillance Modeling Network (CISNET) estimates and showed that annual screening reduces breast cancer deaths by 41.7%.
A novel imaging technique, low-dose positron emission mammography (PEM), shows promise in transforming breast cancer detection by providing high sensitivity and low false positive rates. PEM could potentially decrease healthcare costs and reduce unnecessary procedures for patients with dense breasts.
A study at the Radiological Society of North America annual meeting found that 20-40% of youth baseball players (ages 9-12) experience elbow pain. Skeletally immature children are more prone to injuries, including growth plate fractures and osteochondritis dissecans.
A study published at the Radiological Society of North America annual meeting found that attending regular mammograms can lower breast cancer mortality rates by up to 72%. Women who missed a scheduled mammogram had a significantly reduced survival rate, emphasizing the importance of adherence to screening schedules.
A deep learning AI model developed using mammographic images alone accurately predicted both ductal carcinoma in situ (DCIS) and invasive carcinoma, showing no bias across multiple races. The model outperformed traditional risk models in predicting breast cancer risk, providing a more accurate and equitable assessment.
Researchers identified a link between neck muscles and primary headaches, including tension-type headaches and migraines. Muscle T2 values were found to be significantly associated with headache frequency and neck pain.
Researchers used AI to analyze brain white matter tracts in adolescents with and without ADHD, discovering significant differences in nine brain tracts in individuals with ADHD. Early diagnosis and intervention are key to managing the condition.
A new study links soccer heading to a measurable decline in brain function and microstructure, with high levels of heading exposure associated with changes similar to mild traumatic brain injuries. The research used diffusion tensor imaging (DTI) to assess the impact of repetitive head impacts on verbal learning performance.
Research at the Radiological Society of North America annual meeting found that marijuana smokers are 12 times more likely to develop centrilobular emphysema compared to non-smokers. Combined marijuana and cigarette smoking increased the risk of breathing difficulties and other serious respiratory symptoms.
Researchers found that a higher ratio of quadriceps to hamstring muscle volume was significantly associated with lower odds of total knee replacement. Training programs that strengthen the quadriceps in relation to the hamstrings may be beneficial for preventing knee replacement surgery.
A study found that Black patients undergo medical imaging for cognitive impairment years later than white and Hispanic patients, with significantly lower rates of MRI testing. This delay can lead to earlier stages of disease diagnosis and reduced treatment options.
Researchers developed an AI tool that can identify never-smokers at high risk for lung cancer based on their chest X-ray images. The study found that 28% of non-smokers were deemed high risk by the model, and these patients had a 2.1 times greater risk of developing lung cancer compared to low-risk individuals.
A study using a novel MRI technique found that people with long COVID exhibit distinct brain changes compared to those who have fully recovered from COVID-19. The research suggests that these changes are associated with symptoms such as fatigue, cognitive impairment, and impaired sense of smell.
Researchers used fMRI to study brain activity in soccer fans, finding that brain activity changes when a fan's team succeeds or fails. The study suggests that zealousness found among some sports fans can serve as an example of intense emotional investment and impaired rationality.
A novel AI system analyzing brain MRI scans can diagnose autism in children between 24 and 48 months with a 98.5% accuracy rate. This technology enables early detection of autism, potentially leading to improved independence, IQs, and therapeutic outcomes.
A study published at the Radiological Society of North America annual meeting found that higher amounts of visceral abdominal fat in midlife are associated with increased risk of Alzheimer's disease. The research also showed that this type of fat is linked to brain inflammation, which may contribute to the development of the disease.
Researchers used a stellate ganglion block to restore the sense of smell in patients with long-COVID, showing near 100% resolution of phantosmia in some patients. The treatment was effective in improving symptoms for up to 49% of patients at three months.
A large-scale study found that low-dose CT screening increases the 20-year survival rate of lung cancer patients from 18.6% to 81%, with Stage I cancers having an even higher long-term survival rate of 95%. Early detection through annual screening can effectively cure lung cancer in the long term.
Researchers tested the feasibility of using locally run LLMs like Vicuna-13B to label key findings in chest X-ray reports while preserving patient privacy. The results showed moderate to substantial agreement with non-LLM computer programs, suggesting that these models can be a viable option for AI research.
A new AI model integrates imaging and non-imaging patient data for improved diagnostic performance on chest X-rays. The multimodal model outperformed other models for diagnosing up to 25 conditions, showing potential as an aid to clinicians in high-pressure diagnoses.
A recent study published in Radiology: Artificial Intelligence found significant racial and sex-related biases in an AI chest X-ray foundation model, affecting its performance across patient subgroups. The researchers highlighted the need for comprehensive bias analysis to ensure diversity and representativeness in dataset collection.
A study comparing radiologist and AI performance in interpreting 2,000 chest X-rays found that AI tools achieved moderate sensitivity but high false-positive rates. Radiologists outperformed AI in detecting the absence of disease, especially for complex cases.
A study published in Radiology: Cardiothoracic Imaging found that low- and middle-income countries reported persistent declines in cardiothoracic imaging procedure volumes after the COVID-19 pandemic. In contrast, high-income countries, including the US, recovered to pre-pandemic levels by 2021.
A new CT test can identify individuals with stable angina at a reduced risk of three-year adverse outcomes despite having high coronary artery calcium scores. The test uses AI algorithms and computational fluid dynamics to simulate blood flow through the coronary arteries.
Researchers found that an AI algorithm comparable to human readers demonstrated high sensitivity and specificity in detecting breast cancer. The study utilized a large dataset of mammographic exams and compared the performance of AI with human readers, finding no significant difference between the two.
A new article published in RadioGraphics warns of a potential side effect of novel Alzheimer's treatments: amyloid-related imaging abnormalities (ARIA). ARIA can cause swelling or bleeding in the brain and may be asymptomatic. Radiologists must monitor for ARIA to plan image monitoring per established guidelines.
A study published in Radiology found that combining short- and long-term breast cancer risk models using artificial intelligence can improve cancer risk assessment. The combined model showed an overall improved risk assessment for both interval and long-term cancer detection, identifying women at high risk for breast cancer.
A machine learning model found that background parenchymal enhancement (BPE) on breast MRI is an indicator of breast cancer risk in women with extremely dense breasts. Women with dense breasts are at a higher risk of developing breast cancer compared to those with fatty breasts.
A new study published in Radiology found that AI can use data from low-dose CT scans of the lungs to improve risk prediction for death from various causes. The study used data from over 20,000 individuals and found that body composition measurements derived from lung screening LDCT were strong predictors of mortality.
Researchers developed a chest imaging protocol using photon-counting CT, allowing for simultaneous evaluation of lung structure, ventilation, vasculature, and perfusion. The protocol showed advantages over standard CT, providing high image quality at lower radiation doses and better spectral resolution.
A study published in Radiology found that AI algorithms with high diagnostic accuracy improved radiologists' detection of lung cancers on chest X-rays. High-accuracy AI led to more frequent changes in reader determinations, suggesting increased human trust in AI.
A new ultra-high-resolution CT technology has been developed to detect coronary artery disease in high-risk patients, providing a potentially significant benefit for people previously ineligible for noninvasive screening. The technology delivers excellent image quality and accurate diagnosis with high sensitivity and specificity.
A study published in Radiology found that weight-loss surgery, specifically sleeve gastrectomy, has negative effects on bone health in adolescents and young adults. The procedure led to an increase in bone marrow fat and a decrease in bone density, suggesting potential long-term consequences for bone health and fracture risk.
A recent study published in Radiology found that AI algorithms performed better than the standard Breast Cancer Surveillance Consortium (BCSC) risk model for predicting five-year breast cancer risk. The AI models extracted hundreds of additional mammographic features, leading to improved predictive performance.
A new study found that photon-counting computed tomography (PCCT) provides sharper images and less image noise than dual-source CT (DSCT) in infants with suspected cardiac heart defects. The PCCT images had higher mean overall visual image quality ratings and were more than 97% diagnostic quality, compared to 77% for DSCT.
A study found that muscle fat accumulation, known as myosteatosis, is associated with a higher risk of major adverse events and death in asymptomatic adults. The presence of muscle fat was comparable to the mortality risk associated with smoking or type 2 diabetes.
Large language models like ChatGPT show incredible potential in radiology, but also struggle with reliability and accuracy. The latest model GPT-4 improves advanced reasoning capabilities and performs better on higher-order thinking questions.
Research published in Radiology suggests that exposure to recurrent brain trauma, such as explosions, may increase the risk of developing Alzheimer's disease. Amyloid-beta protein accumulation was detected in six out of nine military instructors who were exposed to subconcussive blast injuries.
A study published in Radiology found that AI can analyze breast mass images from low-cost portable ultrasound machines and accurately identify cancer. The technology showed great promise for improving breast health care in low-resource settings, reducing delays in diagnosis and potentially saving lives.
A study published in Radiology found that AI-based decision support systems can impair radiologist accuracy on mammograms, particularly for less experienced radiologists. Even highly experienced radiologists were adversely impacted by the system's judgments, highlighting the need for safeguards to mitigate automation bias.
A special report highlights radiology's role in combatting climate change, emphasizing the importance of sustainable practices in healthcare. Radiologists are well-positioned to innovate more sustainable methods of care, such as telemedicine and energy-efficient equipment purchasing.
A study published in Radiology found that digital breast tomosynthesis improved breast cancer screening performance and increased radiologists' interpretive accuracy compared to digital mammography. The results showed higher detection rates, sensitivity, and specificity for DBT, with 97.6% of assessed radiologists meeting recommended p...
A study published in Radiology found that ultrasound is an effective standalone diagnostic method for patients with focal breast complaints. The analysis showed that ultrasound alone led to accurate diagnosis in 90% of patients, with over 80% of complaints being benign findings.
A study found that high deductible health plans may lead women to skip additional testing after an abnormal mammogram finding, particularly those with lower incomes and education levels. This can result in delays in diagnosis and treatment, worsening breast cancer outcomes.
A new study published in Radiology found that a minimally invasive procedure combining pulsed radiofrequency and epidural steroid injection treatment leads to better pain reduction and disability improvement. The results showed significant benefits at four, 12, and 52 weeks compared to steroid injections alone.
A large study of over 1 million women found DBT had a higher breast cancer detection rate and lower false positive rates compared to 2D digital mammography. The results suggest that DBT may be the more effective screening method for early breast cancer detection.