Articles tagged with Radiology
A recent study published in Neuro-Oncology found that genomic profiling led to more aggressive patient management resulting in improved clinical outcomes compared to traditional biologically matched historical cohorts.
Researchers found that video radiology reports improved patients' understanding of their results by using lay language and annotated images. The reports were also well-received by patients, with an average rating of 4.7 out of 5.
A retrospective study found that higher coronary artery calcium score, higher pulmonary artery-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse overall survival. The PA-to-aorta ratio was the most important predictor of overall survival.
A new approach called REFERS enables automatic acquisition of supervision signals from hundreds of thousands of radiology reports, achieving high accuracy in predictions. The innovative method reduces human cost by 90% and surpasses conventional medical image diagnosis employing AI algorithms.
Researchers found a steady decline in annual mammography use by breast cancer survivors between 2009 and 2016, with the largest decrease seen among younger patients. The study highlights the importance of reinforcing the significance of annual mammograms for breast cancer survivors.
A multicenter study found that only 42% of patients with a visualization score C on surveillance exams maintain the same score on follow-up exams. The study suggests that alternative surveillance strategies may be necessary for patients at risk for HCC, particularly those with severe steatosis and advanced cirrhosis.
A prospective study found that the 3-T Dixon gradient-recalled echo (GRE) sequence performed better than the current standard of 1.5-T SSFP for unenhanced coronary MRA, particularly in distal and branch segments. The technique demonstrated higher image quality, visible segments, sensitivity, and specificity for significant stenoses.
A study published in JAMA Network Open found that half of all women will experience at least one false positive mammogram over a decade of annual breast cancer screening with 3D mammography. The risk of false positives is lower for women screened every other year, and non-dense breasts also show a lower false positive risk.
A retrospective case-control study found no significant difference in traumatic intracranial hemorrhage frequency between adult patients on antithrombotic therapy and those not on the therapy. However, hematoma expansion occurred more frequently in patients on antithrombotic therapy.
A retrospective study found that positive oral CT contrast material improves detection of malignant deposits, particularly with adequate bowel filling. The NPV for detection was 65.8% for positive oral contrast material with adequate bowel filling.
A multicenter study found relatively high interobserver agreement for chronic pancreatitis findings in children using both CT and MRI. However, subjective findings like atrophy showed moderate agreement, emphasizing the need for standardized criteria.
A multicenter study validates the accuracy and reliability of NS-RADS for classifying and grading peripheral neuropathies, with high interrater agreement across different reader experience levels. The study shows promising results for routine practice, suggesting NS-RADS as a standardized guideline for reporting peripheral neuropathies.
Researchers developed a new imaging approach called VascuViz to visualize blood vessels at different spatial scales. The method enables detailed mathematical models and complementary images to clarify the role of blood flow in health and disease, advancing our understanding of tissues throughout the body.
A retrospective study found that online patient experience ratings improved radiologists' performance, with scores increasing over time. The results showed that radiologists' performance was comparable to that of non-radiologist physicians, suggesting the value of implementing patient experience surveys in radiology.
Researchers developed a novel method of measuring aortic growth, called vascular deformation mapping, which outperforms standard manual rating methods. The technique uses high-resolution CT imaging to calculate three-dimensional changes in the aortic wall, achieving an accuracy of less than 1 millimeter.
A study published in American Journal of Roentgenology found that digital breast tomosynthesis (DBT) spot compression views increased both intrareader and interreader agreement, as well as diagnostic accuracy, for equivocal findings. This improvement was primarily due to increased specificity.
The American Roentgen Ray Society recognizes Drs. Nguyen, Beheshtian, Harfouch, and Hashiba for their outstanding research and education contributions to the field of radiology. The awards honor the candidates' scientific merit and potential impact on imaging and allied sciences research.
A new machine learning process has been developed to identify and classify hip fractures from X-rays, achieving 92% accuracy and confidence. This approach aims to improve patient outcomes, reduce care costs, and alleviate the bottleneck of unreported radiographs in the UK.
The American Roentgen Ray Society has awarded two 2022 ARRS Scholarships to Sean Woolen and Bradley Allen, providing a total of $180,000 in funding for their radiological research projects. The scholarships aim to advance emerging scholars and prepare them for leadership positions.
Researchers at TUM integrated dark-field X-ray imaging into a clinical CT scanner, providing additional information on fine tissue structures. The new prototype can capture both conventional and dark-field X-ray images in a single scan, potentially improving lung disease diagnosis and kidney stone differentiation.
A study of 74 healthy individuals found correlations between spleen volume and gender, age, and certain blood parameters such as HGB, HCT, RBC, ALT, but not others like LYM%, PLT. Spleen volume was estimated using the Cavalieri principle and stereological method.
A retrospective study found that the upgrade rate of architectural distortion on digital breast tomosynthesis (DBT) to malignancy was 10.2% for radial scars without atypia and 28.2% for those with atypia. Imaging surveillance is considered an alternative to surgery for these cases.
Dr. Edward Y. Lee, MD, MPH, receives the highest distinction from North America's first radiological society for his contributions to pediatric thoracic imaging and education. The ARRS Gold Medal honors his tireless efforts to advance radiology globally.
Samuel Galgano and Pankaj Gupta have been named the 2022 Melvin M. Figley Fellow in Radiology Journalism and the 2022 Lee F. Rogers International Fellow in Radiology Journalism, respectively. They will attend the 2022 ARRS Annual Meeting and participate in the Editor’s Forum.
A retrospective study found that dual-energy CT examinations performed in 2019 had a significantly lower frequency of equivocal interpretations compared to those in 2013. Joint aspirations were also less likely to be performed after negative DECT interpretations in 2019.
A prospective observational study found that preoperative shear wave elastography (SWE) can predict successful rotator cuff repair. SWE-derived elasticity was higher in patients with insufficient repair, and the elasticity ratio independently predicted insufficient repair.
Researchers at Duke University developed an artificial intelligence platform that analyzes potentially cancerous lesions in mammography scans. The algorithm is interpretable, showing physicians how it came to its conclusions, making it more trustworthy and useful for training students and aiding physicians in sparsely populated regions.
A retrospective study found that whole-spine MRI commonly demonstrates isolated thoracolumbar injuries in children with suspected abusive head trauma. The study included 256 children who underwent whole-spine MRI as part of their evaluation, revealing that 23% of examinations showed injuries localized to the thoracolumbar spine.
A new study reveals that radiologist fatigue impacts performance differently depending on experience level. Less-experienced radiologists are more likely to recommend additional imaging for women undergoing breast cancer screening when interpreting digital breast tomosynthesis (DBT) images later in the day.
Dr. Mark S. Parker, MD, FACR, has been recognized as the 2022 ARRS Distinguished Educator for his outstanding contributions to radiological education. He will be formally recognized at the ARRS Annual Meeting in New Orleans, LA on May 1, 2022.
Automated brain volumetry in memory-impaired patients shows significant differences and systematic biases between conventional and ultrafast 3D T1-weighted MRI sequences. Most regions demonstrated substantial agreement but also significantly different mean values and consistent biases.
Researchers from Egypt used 3D CT scanning to 'digitally unwrap' the mummy of Pharaoh Amenhotep I, dispelling a theory that 21st dynasty restorers reused old royal burial equipment. The study revealed that the priests lovingly repaired injuries inflicted by tomb robbers and preserved the pharaoh's jewelry and amulets.
A new study found that AI can help physicians interpret x-rays after an injury and suspected fracture. AI-assisted diagnosis reduced missed fractures by 29% and increased sensitivity by 16%, improving efficiency and accuracy.
Researchers have published an extensive 7T fMRI dataset to study how humans perceive and interpret naturalistic photographs. The Natural Scenes Dataset provides a massive scale of brain data for training complex deep-learning models that predict brain activity.
A prospective study found that ultrasound alone adequately completed the diagnostic evaluation of 71.2% of noncalcified lesions, diagnosed 92.1% of cancers, and yielded a sensitivity of 94.9%. Radiologists should consider performing ultrasound first for digital breast tomosynthesis-recalled noncalcified masses.
Researchers at KAUST have developed a nanocomposite that absorbs X-rays with near-perfect efficiency and re-emits the energy as light. This innovation improves high-resolution medical imaging and security screening, with detection limits up to 142 times lower than traditional methods.
Researchers simulated an attack that falsified mammogram images, fooling both AI breast cancer diagnosis models and human radiologist experts. The study highlights the need to develop ways to make AI models more robust to adversarial attacks, which could lead to incorrect cancer diagnoses.
A prospective study found that MRI outperformed conventional tests and FDG PET/CT for various staging endpoints in SCLC. Whole-body MRI and FDG PET/MRI were more accurate than FDG PET/CT for assessing local invasion extent.
A recent review reveals alarming increase in physician burnout among diagnostic radiologists, with causes including lack of control, social isolation and technological demands. Possible solutions include heightened engagement, dedicated reading room assistants and mindfulness techniques.
A study found that racial disparities in mammography screening worsened after COVID-19 closures, with non-white patients facing reduced access to facilities. Early interventions aimed at expanding access to these facilities helped to recover late recovery volumes for patients of races other than white.
Convolutional neural networks trained to identify abnormalities on upper extremity radiographs are susceptible to a ubiquitous confounding image feature: radiograph labels. Covering these labels increases accuracy, while using them alone leads to decreased performance.
A retrospective study found that Lung-RADS performed well in assessing lung cancer risk on follow-up CT scans, with a weighted cancer risk of 5% for new nodules. Strict application of Lung-RADS criteria downgraded some malignant nodules, highlighting the need for category 4X for suspicious features.
A study of 5.9 million radiological examinations found no significant difference in major and minor discrepancy rates for acute community setting exams between concordant and discordant with radiologists' fellowship training. However, advanced examination discrepancies were higher when concordant with radiologists' fellowship training.
Researchers have demonstrated a new technique for cross-sectional medical images without the need for tomography, enabling faster and more accurate imaging. The breakthrough is made possible by ultrafast photon detectors that can precisely determine the arrival times of photons, allowing for reconstruction-free positron emission imaging.
A recent study published in the American Journal of Roentgenology found a link between COVID-19 mRNA vaccination and myocarditis in adolescent males. Cardiac MRI was used to assess suspected myocarditis post-vaccination, with late gadolinium enhancement persisting in two patients undergoing repeat MRI.
A deep learning algorithm from VUNO improved radiologists' sensitivity for detecting reticular opacity on chest radiographs in patients with mild to severe interstitial lung disease. The algorithm accuracy reached 98.5% and improved interobserver agreement, suggesting its potential for screening suspected ILD patients.
Researchers at UC San Diego will document brain development from birth through early childhood, focusing on environmental factors and mental disorders. The HBCD study aims to optimize brain imaging technologies and predict future behavioral problems.
Left atrium emptying fraction derived from cardiac CTA improves predictive performance of established clinical risk scores. A reduced LAEF independently predicts all-cause mortality within 24 months post-procedure.
A retrospective cohort study of 27 patients with sarcoma lung metastases found high primary technical success rates for percutaneous image-guided microwave and cryoablation. The treatment modality and tumor location did not affect local progression, and smaller tumors showed lower cumulative incidence of local progression.
A prospective study found that liver stiffness measurements obtained by shear-wave elastography decreased significantly after image-guided intervention for chronic Budd-Chiari syndrome in children. Disease recurrence was typically associated with an increase in liver stiffness measurements compared to prior assessments.
A new AI system developed by NYU and NYU Abu Dhabi researchers achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. The system helps decrease false-positive findings and requested biopsies while maintaining sensitivity.
A recent study published in AJR found that gallbladder polyps can fluctuate significantly in size and number over time. The authors suggest revising guidelines to reflect this variability, with no cases of gallbladder carcinoma identified in patients who underwent cholecystectomy.
A multidisciplinary organization has reached consensus on guidelines for performing, interpreting, and reporting MR defecography. The consensus templates aim to standardize care for patients with evacuation disorders of the pelvic floor.
A new paradigm in breast cancer screening has been established with immediate-read screenings during the pandemic. This approach reduces racial and ethnic disparities in same-day diagnostic imaging, while speeding up diagnoses.
The new QIBA profile provides a framework for evaluating the reliability of cartilage compositional imaging measurements, including T1rho and T2 mapping. It establishes minimum detectable changes in these values, enabling early detection of cartilage abnormalities and potentially preventing osteoarthritis.
A new study uses deep learning to predict breast cancer risk from mammograms, outperforming clinical risk factors in distinguishing between women who will develop cancer and those who won't. The findings have significant implications for breast cancer management, suggesting a potential role for AI as a second reader for radiologists.
A single-center retrospective study found that preoperative thoracic CT findings can complement preoperative clinical risk factors to improve risk assessment for the need of postoperative mechanical ventilation. Bronchial wall thickening, pericardial effusion, and anteroposterior chest diameter were identified as independent predictors...
A new 3D spiral gradient recalled echo (GRE) sequence has been developed to overcome conventional challenges in head and neck MRI. This sequence achieves improved image quality and contrast-to-noise ratio compared to traditional Cartesian sequences, while reducing scan time by up to 44.6%.
A deep learning tool for sarcopenia assessment on CT scans shows similar utility in predicting hip fractures and death at both L1 and L3 vertebral levels. Muscle attenuation measurements performed better than muscle area assessments, likely due to the inclusion of intramuscular fat.
A single-center retrospective study found that AI-CAD reduced recall rates and improved accuracy compared to digital mammography (DM) and DBT. The study showed lower recall rates and higher accuracy for DM with AI-CAD, indicating a practical addition to lowering false-positive findings.