Articles tagged with Medical Imaging
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.
Researchers used energy dispersive diffraction to create high-resolution 3D maps of bioapatite arrangements within shark centra, revealing key structures and their functions. The study provides insights into the structure-function relationship of the shark skeleton and could be applied to other organisms.
A new diagnostic tool combines grayscale B-mode and strain elastography ultrasound imaging to detect breast cancer with high accuracy. The model achieved a detection rate of 90% in the study, surpassing individual models trained on either B-mode or SE imaging alone.
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 new AI-based method has been developed to evaluate patients with Stargardt disease, a leading cause of childhood blindness. The study found that the severity of vision loss can be classified into different phenotypes based on genetic variants, and provided sensitive structural outcome measures for therapeutic trials.
Researchers used optical imaging to study the metabolic interactions between pancreatic cancer cells and surrounding non-cancer cells. They found that cancer cells can hijack the metabolic activity of these non-cancer cells to fuel tumor growth. This discovery could lead to new therapies targeting the tumor microenvironment.
The new BD CellView Image Technology enables high-speed sorting of individual cells based on detailed microscopic analysis, accelerating discovery research in immunology, cell biology, and genomics. This technology has the potential to unlock new cell-based therapeutic discoveries and transform various fields of biomedical research.
Researchers found that delirium and spatial neglect are associated with widespread dysfunction of brain networks, including arousal, attention, and spatial orientation. This imbalance may contribute to chronic cognitive decline after stroke.
Researchers developed a new fluorescence lifetime imaging (FLIM) technique to study DNA compaction and gene activities in live cells. The method enables fine measurements of DNA compaction, revealing differences in compaction between gene-rich and gene-poor chromatin domains.
Researchers discover that lipid droplets can be used as endogenous intracellular microlenses to enhance fluorescence imaging in living cells. This technique reduces the required excitation power by up to 73% and enables efficient detection of fluorescent signals from extracellular environments.
Researchers have developed a new laser speckle imaging technique that can monitor blood flow velocity in thick tissue without the need for surgical windows or optical clearing. This non-invasive method uses transmission detection to improve signal-to-background ratio and enables individual-vessel resolution in human subjects.
Researchers from Göttingen University and Hannover Medical School have detected changes in heart muscle tissue of people who died from Covid-19. The study used innovative X-ray imaging to visualize the affected tissue in three dimensions, revealing a network of chaotic vessel formations.
A new imaging technique can detect early signs of blood trauma in red blood cells, which could aid in the development of markers to prevent damage. The technique, developed by researchers at Shibaura Institute of Technology and Griffith University, uses high-speed cameras to visualize changes in RBC shape under stress.
A new class of faster and more powerful semiconductors is being developed by UMass Lowell scientists to enhance wireless communication and digital imaging. The $1.7M NSF project aims to improve infrared optoelectronic devices, enabling better intracellular imaging, night vision, and quantum and 5G communication.
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 developed a detachable head-mounted photoacoustic microscope for imaging brain activity in freely moving mice. The probe captures neurovascular dynamics and can be removed after imaging, enabling long-term studies that could reveal new insights into neurodegenerative diseases.
Scientists have created a new imaging method that can detect microscopic soft tissue damage in animal spines, which may lead to improved treatments for lower back pain. The technique uses fluorescent molecules to target denatured collagen and produce precise 3D maps of spinal damage.
Researchers developed photoswitchable label proteins to visualize small numbers of cells in live organisms, enabling improved understanding of diseases like the immune system or tumor development. They also created sensors for optoacoustic and super-resolution imaging to visualize small molecules or ions at nanometer resolution.
Researchers have developed microbubbles that can acoustically detect blood oxygen levels, showing a strong correlation between oxygen concentration and acoustic bubble response. This innovation has the potential to benefit medicine and imaging by evaluating oxygen-deprived regions of tumors and in the brain.
Researchers from Doshisha University developed a new imaging technique to measure oxygen concentration in osteoclasts, revealing key molecular mechanisms involved in bone resorption. The study found that hypoxia interferes with TET enzyme activity, limiting osteoclastogenesis.
Researchers developed an AI method to correct speed of sound aberrations in photoacoustic images, resulting in improved image quality and resolution. The technique reduced streak artifacts by up to 5% and increased signal-to-noise ratio by about 25 decibels.
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 new imaging technique called single-shot photoluminescence lifetime imaging thermometry (SPLIT) measures temperature in 2D, without contact, and in real-time. This technology could improve photothermal therapy and help detect skin cancers.
Researchers have developed the world's thinnest X-ray detector, made from tin mono-sulfide nanosheets, which could enable real-time imaging of cellular processes. The detectors possess high photon absorption coefficients and rapid response times, making them suitable for studying soft X-rays.
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 from Tokyo Medical and Dental University have developed a non-invasive imaging technique using blue light to identify areas affected by diabetic retinopathy. The study found that blue images obtained through multicolor widefield scanning laser ophthalmoscopy (SLO) can reveal hyporeflective areas indicative of damage associa...
Researchers developed a molecular agent that can target lung and other cancer cells for imaging and treatment, distinguishing between healthy and cancerous cells. The new approach uses a unique chemistry method to tune the reactivity of the molecule, avoiding off-target effects.
Researchers have trained a neural network to detect anomalies in medical images, adapting it to the nature of medical imaging and achieving better results. The new method uses weakly supervised training and can spot small-scale anomalies, accelerating the work of histopathologists and radiologists.
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.
A recent study from Penn State and Lawrence Livermore National Laboratory has discovered a natural protein called lanmodulin that can recover and purify radioactive metals like actinium. The protein-based approach simplifies the purification process, reduces costs, and enables the production of higher-purity actinium.
Scientists developed a fluorescent spray that specifically targets and illuminates cancerous tissue, enabling precise tumor detection and removal during surgery. The innovative approach offers a solution to the challenge of distinguishing between healthy tissue and cancerous cells.
The USC Stevens INI is partnering with Vanderbilt University Medical Center and the University of Miami to merge Alzheimer's disease data from over 30 datasets, producing a large-scale, standardized set of clearly defined data. This harmonization will enable large-scale machine learning analysis to better characterize the genetic basis...
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.
Researchers developed a non-toxic, small-molecule probe that provides real-time visualization of disease progression, overcoming limitations of MRI and PET imaging. The probe binds copper ions and detects dysregulated levels, accurately identifying Wilson's disease and other maladies.
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.
Scientists have developed a technique to enhance digital sensor capabilities beyond current limits, enabling applications in consumer photography, medical imaging, and space exploration. The new approach uses 'modulo' sampling to process a wider range of information, unlocking high dynamic range for sensors.
A Dartmouth research team has been selected to present their abstract on a new advancement in Cherenkov imaging at the ASTRO Annual Meeting. The work, which involves designing a color-sensitive camera to image Cherenkov emission from patients, allows for more accurate quantification of radiation delivery and safe treatment.
A team of neuroscientists at the Beckman Institute developed safety standards for multiband EEG-fMRI imaging, reducing heating risks and maintaining data quality. By establishing protocols to mitigate artifacts, they enabled the use of accelerated fMRI sequences with EEG recordings.
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...
Researchers at UCLA have developed a computational technique powered by artificial intelligence that transforms images of tissue previously stained with H&E into new ones with added special stains. The process takes less than one minute per tissue sample, significantly improving diagnoses in medical conditions such as organ transpl...
A team of researchers is developing a smartphone-based device that can predict the size of aortic aneurysms and detect fluid overload in postpartum women. The device uses arterial waveforms, which can be easily recorded with a smartphone camera or smart scale, to provide a non-imaging solution for AA screening.
Researchers developed a new phosphorescent material inspired by wood's natural ability to faintly glow, using lignin trapped within a 3D polymer network. The material glows visibly for around one second and has potential applications in medical imaging, optical sensing, and textile industry.
A new study from University of California - San Diego suggests that protein deposits in the retina and brain may be a sign of Alzheimer's disease risk. Retinal imaging may potentially serve as an early biomarker for detecting AD risk, offering a non-invasive alternative to traditional brain scans.
Scientists from Osaka University create optical imaging system that can capture over a million cells in a single image, enabling simultaneous observation of centimeter-scale dynamics with micrometer resolution. This technology, termed 'trans-scale scope,' may accelerate research in fields such as neuroscience, oncology, and immunology.
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.
The researcher is investigating the inflammatory responses produced by exposure to chemical agents, comparing different chemical exposures at both whole-body and tissue levels. The study aims to develop a common treatment for chemical exposures and diagnose the responsible chemicals.
A team of Beckman researchers developed software to boost infrared imaging-based cancer diagnosis, enhancing image resolution and accelerating recording speeds. The software integrates data analysis and reduces limitations associated with IR imaging, making it faster and more accurate.
Researchers at University of Bonn found that fixing objects slightly away from the center of cone density improves overall vision. The observed image shift is due to the varying resolution across the human retina, with sharper areas in the fovea and less sharp areas in the periphery.
A retrospective study of over 3,900 patients found that warming iohexol 350 contrast media did not significantly reduce adverse reactions or extravasations. The results suggest that maintaining the agent at room temperature is non-inferior to warming it to body temperature before injection.
Researchers developed nanoscale sensors that can convert brain electrical activity into optical signals detectable outside the body. These sensors, called NeuroSWARM3, offer a non-invasive way to track brain activity and could one day enable people with physical disabilities to interact with the world and control wearable technology.
Researchers developed novel imaging approach to visualize eggs and embryos in live animals, revealing complex dynamics of egg and embryo transport. The findings have important implications for studies of fertilization, embryogenesis, and in vitro fertilization.
Scientists from the University of Tsukuba used radio-frequency imaging to detect nitrogen-vacancy defects in diamond with improved resolution. The technique, called spin-locking, enhances accuracy and sensitivity by shielding electron spin from random noise.
A team of researchers has developed a new imaging technique to visualize the chemical interactions between small animals and their microbes. This allows for a better understanding of how these interactions form and persist in animal tissues. The method, called chemo-histo-tomography, combines chemical imaging with micro-computed X-ray ...
Researchers have developed a new method to control scrambled light in optical fibres, allowing for high-resolution imaging of individual cells. This technology has the potential to guide biopsy needles and identify diseased cells within the body.
The Chan Zuckerberg Initiative (CZI) has awarded nearly $28 million in grants to support the development of next-generation electron microscopy techniques for visualizing proteins in cells. The awards will enable researchers to obtain unprecedented views of protein structure, quantity, distribution, and interactions at near-atomic reso...
Researchers developed AstroPath, a platform combining astronomy and pathology to analyze tumor microenvironments. It predicts response to anti-PD-1 therapy in melanoma patients, providing new insights into cancer treatment options.
Researchers have developed a new fluorescence microscopy technique that allows for high-resolution images of microcirculation in the brain without invasive surgical methods. This breakthrough has the potential to reveal new insights into neurological disorders and facilitate early detection and treatment.
An international team used Raman microspectroscopy and imaging to identify signatures in the elastic and collagen fibers of the aorta that indicate the presence of an aneurysm. The study found biomarkers for thoracic aortic aneurysms, which could enable early detection and potentially save lives.