Articles tagged with Clinical Imaging
The SCAI/SCCT expert opinion document presents a comprehensive framework for using CCTA to guide PCI. It outlines current evidence and future opportunities, providing practical guidance on image acquisition, interpretation, and procedural strategy. The document aims to bridge the gap between imaging and intervention, emphasizing educat...
A new review advocates for building confidence in AI applications by implementing robust data governance frameworks, enhancing transparency, and involving stakeholders. The authors emphasize the importance of addressing ethical implications and ensuring equitable access to AI-driven innovations in clinical oncology.
Researchers at TUM developed an AI-powered algorithm to predict kidney damage in prostate cancer patients undergoing lutetium-177 PSMA therapy. Early detection could enable personalized treatment adjustments to prevent organ damage.
NGR Oncology has created a new Sarcoma Subcommittee to improve outcomes for adults with cancer, focusing on building a robust program, collaborating with the Children's Oncology Group, and promoting sarcoma research. The subcommittee is led by Chair Dian Wang, MD, PhD, and Vice-Chairs William Tseng, MD, and Brian A Van Tine, MD, PhD.
A new case report presents a highly unusual combination of two benign ovarian tumors: serous cystadenofibroma and collision lesions. Accurate preoperative diagnosis is critical for effective treatment planning, and this case emphasizes the need for personalized evaluation of each ovarian mass.
Three UVA Engineering faculty members, Scott T. Acton, Gustavo Kunde Rohde and Shannon Barker, have been named to the 2025 class of the American Institute for Medical and Biological Engineering (AIMBE) College of Fellows. They are recognized for their contributions to biomedical engineering research, innovation, teaching and leadership.
The PREMSTEM Conference will present cutting-edge research on neonatal brain repair, focusing on human mesenchymal stem cells as a potential therapy for preterm birth-related brain injury. Associate Professor Atul Malhotra's keynote address will highlight successes and lessons learned from his ongoing stem cell-based therapy trials.
A new radiology screening tool can help detect intimate partner violence (IPV) in patients, enabling healthcare providers to identify victims earlier. The study found that imaging studies and injury patterns differ between women who have reported IPV and those who have not.
Quantitative parameters from DCE-MRI show high diagnostic efficacy for malignant SSPNs. DCE-MRI provides a non-invasive, radiation-free method for differential diagnosis.
A new algorithm proposes measuring quadriceps muscle mass for more accurate sarcopenia diagnosis, potentially leading to earlier detection and better treatment options. Ultrasound imaging is recommended as a cost-effective and practical solution for diagnosing sarcopenia in clinical settings.
Researchers develop transcranial ultrasound stimulation (TUS) as a non-invasive therapy for brain-related issues, with potential for personalized treatments. A 'search and rescue tool' for the brain, TUS enables precise targeting of specific areas before treatment.
Researchers have introduced DSFN to improve the speed and accuracy of diagnoses of retinal disorders. This AI-powered medical imaging technique combines retina images with vascular distribution information to accurately locate the fovea in complex clinical scenarios, enabling doctors to detect early signs of ocular diseases.
Generative AI is revolutionizing oncological imaging by expanding datasets and improving image quality. This technology enables predictive oncology and personalized cancer screening, offering new hope in the fight against cancer.
Researchers at CNIC discover clonal hematopoiesis as a new cause of atherosclerosis, while identifying the ancient medication colchicine as a potential treatment. Clonal hematopoiesis is linked to an increased risk of cardiovascular disease, with no influence on the progression of mutated blood cells.
Researchers explore emerging role of Graph Filtration Learning (GFL) in revolutionizing HCC imaging analysis. GFL captures complex topological features inaccessible to traditional pixel-based methods.
A multi-university research team led by University of Virginia engineering professor Gustavo K. Rohde has developed a system that can accurately spot genetic markers of autism in brain images. The system uses generative computer modeling technique called transport-based morphometry, which reveals brain structure patterns that predict v...
Women with regular annual mammograms had higher overall survival and lower late-stage cancer rates than those screened less frequently. The study's findings contradict current guidelines, suggesting a significant benefit to annual screening for women over 40.
Researchers at WVU created a motion-compatible brain scanner that allows patients to move around during imaging. The Ambulatory Motion-enabling PET (AMPET) scanner can help study human behaviors, balance, and emotions, and may be used to monitor brain activity for PTSD treatment and mindfulness meditation.
Researchers discuss primary hepatic angiosarcoma, a rare mesenchymal liver tumor, and its poor prognosis compared to hepatocellular carcinoma. Diagnosing PHA is critical due to its similar clinical presentation to HCC.
A study by Nanyang Technological University found that eight in 10 gastroenterologists in the Asia-Pacific region accept and trust AI-powered tools for diagnosing colorectal polyps. The study also highlights the need for more research into what influences doctors' acceptance of AI in their medical practice.
Researchers developed metamaterials-enhanced MRI technology using coaxial cables to boost signal-to-noise ratio. The innovative coils address patient discomfort and cost by providing adaptable, form-fitting designs for various anatomical sites.
A new AI model has been shown to significantly improve the accuracy of diagnosing prostate cancer by 45 times compared to doctors' measurements alone. The system assists in mapping out the boundaries of cancerous tissue, reducing the risk of underestimation and enabling more precise treatment planning and effective surgical procedures.
The Multifunctional Ablative Gastrointestinal Imaging Capsule (MAGIC) combines OCT technology with an endoscope camera and ablation laser for superior esophageal imaging. It provides unmatched accuracy in detecting early lesions, enabling potential ablative treatment of esophageal abnormalities.
A new approach to heart bypass surgery has been successfully tested, using non-invasive cardiac-CT scan images and AI-powered blood flow analysis. The trial showed a 99.1% feasibility rate, indicating that the procedure is safe and effective without invasive diagnostic catheterisation.
A combined PET-MRI scan improved treatment outcomes for 57 out of 205 patients with early-stage breast cancer. The scan helped doctors spot signs of tumour spread, enabling alternative treatments such as chemotherapy or different surgical approaches.
Researchers found no significant differences in participants with AHIs and controls, except for increased self-reported fatigue, post-traumatic stress, and depression. Forty-one percent of AHI group members met criteria for functional neurological disorders or had significant somatic symptoms.
A novel transparent ultrasonic transducer (TUT) developed by POSTECH researchers offers exceptional optical transparency and maintains acoustic performance, surpassing conventional limitations. This breakthrough enables high-depth-to-resolution ratios for ultrasound imaging, with applications in various medical devices and fields.
Researchers developed a compact, cost-effective PA sensing instrument for biomedical tissue diagnosis, showcasing its potential to streamline sampling processes and improve diagnostic accuracy for breast disease. The instrument successfully differentiated various tissue types based on quantitative spectral parameters.
Researchers at the University of Oklahoma Health Sciences have developed a new imaging technique that can detect pancreatic cancer cells approximately 10 times more magnificently than current options. The approach combines contrast agent recognition with Multispectral Optoacoustic Tomography, enabling real-time detection and surgery pl...
Researchers at University of Tsukuba discovered a correlation between hypoxia levels and clinical symptoms in UC patients. Lower oxygen saturation in the rectal mucosa was associated with greater severity of colitis, making this method a potential tool for objective measurement of disease activity.
Researchers developed a method to measure microvascular changes in the skin using AI and optoacoustic imaging technology, enabling non-invasive assessment of diabetes severity. The study identified 32 significant changes in blood vessels, which can be used to monitor disease progression.
Researchers developed an AI-based method to estimate BMD from plain X-ray images using a hierarchical learning framework. The approach showed high performance and reliability in estimating BMD, with correlation coefficients of 0.88 and 0.92 compared to DXA and QCT.
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.
Researchers aim to create machine learning tools that can analyze and quantify shape information from images, enabling more accurate diagnoses and improving patient care. A new family of deep neural networks, called DSNNs, will be developed to tackle AI's blind spot in image analysis.
A study of 29 clinical trials found that MRg-A-SBRT significantly reduces urinary and bowel side effects in prostate cancer patients, with a 44% reduction in urinary and 60% reduction in bowel side effects. This technique uses imaging technology to accurately aim radiation beams at the prostate while avoiding nearby tissue.
Researchers developed a novel endoscopic imaging system with a bioinspired sensor that can detect multiple fluorescent probes, enabling more accurate fluorescence-guided cancer surgery. The system showed improved spatial resolution and sensitivity in detecting tumors, paving the way for the adoption of multi-tracer FGS.
Researchers at the Beckman Institute for Advanced Science and Technology have developed a new framework for super-resolution ultrasound using deep learning, reducing processing speeds from minutes to seconds. The new technology enables real-time blood flow visualization, overcoming challenges faced by conventional methods.
A 13-year study led by UTEP professor Arshad M. Khan mapped specific cell populations in the brain responsive to rapid changes in blood sugar. The discovery could lead to more targeted therapies for individuals with Type I and Type II diabetes.
Dr. Erik K. Paulson, MD, chair of Duke University's radiology department, has been elected as the 123rd President of ARRS for a one-year term starting April 2023. He succeeds Gary J. Whitman, who served from 2022 to 2023.
Researchers developed innovative contrast-enhancing agents to tackle limitations of photoacoustic imaging, including low SNR, image contrast, and targeted delivery. The study suggests promising strategies such as photoswitching agents, near-infrared-II agents, and micromotor agents.
A trial using PSMA-PET/CT scans has shown that clinicians changed their treatment plans for patients with clinically significant prostate cancer in 19% of cases, helping to detect more cancers. The technique was found to be beneficial in high-risk patients but also led to false positives requiring further investigations.
Using a dual-source CT scanner eliminates the need for beta-blockers and decreases nondiagnostic examinations, resulting in shorter CT completion times. The study found no difference in ED length of stay but demonstrated significant benefits in reducing nondiagnostic examinations.
A new study reveals that phase-contrast X-ray imaging can visualize smallest airways and their obstructions, potentially detecting early-stage lung disease. This technique could provide better resolution and contrast than conventional radiography, enabling subtle pathological changes to be seen.
The University of Oklahoma engineer is developing a novel endoscopic optical imaging technique to provide real-time visualizations for needle-based medical interventions. This technology aims to improve the precision of needle placement, reducing complications and improving treatment efficacy.
The international group of clinicians established guidelines on measuring plasma EBV DNA in managing nasopharyngeal carcinoma (NPC) during the COVID-19 pandemic. Plasma EBV DNA can be used in most clinical circumstances with imaging scans, but cannot replace essential procedures like nasoendoscopy and tumour biopsy.
A cohort study of over 600 persons with non-MRI-conditional implantable cardioverter defibrillators found that these devices continue to appropriately treat detected tachyarrhythmias after MRI scans. The findings suggest that patients with non-MRI-conditional ICDs can safely undergo MRI exams without compromising device function.
Researchers created monthly infant brain atlases to track normative trends in brain development. The atlases reveal changes in brain structure, cortical geometry, and tissue contrast, shedding light on conditions like ADHD and dyslexia. The study aims to facilitate discovery of new insights into child cognition and social behavior.
Researchers developed a multimodal imaging-based tool, the active biopsy guidance system (ABGS), to improve oral cancer diagnosis. The ABGS provides clinically actionable direct visible guidance for biopsies, enhancing precision and potentially saving lives.
Researchers analyzed MRI images of Olympic athletes' injuries during the 2020 Tokyo Games and found that those with tendon tears were more likely to drop out. The study aims to improve injury management and prevention by understanding different types of muscle injuries and their outcomes.
A new biopsy procedure is developed with a multispectral confocal endomicroscope to aid in lung tissue imaging. The system allows for simultaneous imaging of multiple fluorescent dyes, enabling unique identification and spectral unmixing.
Researchers developed an innovative deep learning-based approach to classify epileptic seizures in near real-time, overcoming clinical limitations. The system uses action recognition with intelligent 3D cropping to distinguish between frontal and temporal lobes seizures or non-epileptic events.
The American Roentgen Ray Society has awarded the 2023 ARRS Gold Medal to Dr. Bernard F. King, Jr., MD, FACR, FSAR, in recognition of his distinguished service to radiology. Dr. King has made significant contributions to the field, including the development of contrast media recognition and treatment protocols.
Researchers have developed a new X-ray technology that visualizes lung tissue microstructure, providing additional information for accurate diagnosis. Dark-field X-ray images can differentiate between diseased and healthy lung tissue, potentially replacing computed tomography (CT) for repeated examinations.
For adrenal lesions evaluated by single-phase dual-energy CT, fat fraction had significantly higher sensitivity than virtual noncontrast attenuation at both clinically optimal threshold and traditional ≤10 HU threshold. Fat fraction-derived metrics can help definitively diagnose incidental adrenal lesions as adenomas.
The American Roentgen Ray Society (ARRS) named Dr. Sarah Kamel of Thomas Jefferson University Hospital and Dr. Ankur Goyal of the All India Institute of Medical Sciences as Melvin Figley and Lee Rogers Fellows in Radiology Journalism, respectively. They will receive expert instruction in scientific writing and communication through the...
A study published in American Journal of Roentgenology found that a PACS tool improved completion rates of clinically necessary follow-up imaging. The tool identified socioeconomically disadvantaged patients at increased risk of failure, and referrer agreements played a crucial role in improving recommendations.
The Beckman Institute has established a new national collaborative Biomedical Technology Research Resource to develop label-free optical imaging technologies. The center aims to create optical and computational imaging technologies that can serve as a resource for clinicians and researchers.
A new project will develop a technique to quantify uncertainty in AI-based tools used for image analysis and create a questionnaire to assess patients' risk tolerance when using these tools. The goal is to ensure that AI-assisted clinical decisions are informed by the inherent uncertainty of imaging technologies.
Researchers propose an optical imaging system for real-time hypoxia imaging in cancer treatment. The technique utilizes protoporphyrin IX to enhance contrast between tumors and healthy tissues, allowing for more effective surgical removal.
Interdisciplinary researchers at the Beckman Institute have received a four-year, $2M award from the National Institutes of Health to develop a device that can instantly enable real-time 3D ultrasound imaging. The device, named FASTER, is designed to improve high-quality medical imaging accessibility in diverse communities.