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The annual meeting of the Radiological Society of North America was held virtually this year from Nov. 29 to Dec. 5 and attracted participants from around the world, including radiologists, radiation oncologists, physicists in medicine, radiologic technologists, and other health care professionals. The conference featured scientific papers in a number of subspecialties covering the newest trends in radiological research as well as education and informatics exhibits.
In one study, Miriam A. Bredella, M.D., of Harvard Medical School in Boston, and colleagues found that adolescents with severe obesity who undergo weight loss surgery show a reduction in bone mineral density and an increase in marrow adipose tissue in the lumbar spine.
The authors recruited 52 adolescents with severe obesity, including 26 adolescents who were scheduled to undergo weight loss surgery and 26 adolescents who were followed without surgery. The authors performed quantitative computed tomography (CT) to assess volumetric bone mineral density and proton magnetic resonance spectroscopy to measure fat within bones of the lumbar spine at baseline and 12 months. The investigators found that weight loss surgery in adolescents decreased bone strength.
"The key conclusion was that weight loss surgery in adolescents is bad for bones," Bredella said. "If adolescents are scheduled to undergo weight loss surgery, it is important to pay extra attention to bone health -- for example, by a healthy diet with enough calcium and vitamin D and possible supplements and weight bearing exercise."
In another study, Aaron Afran, a third-year medical school student at the Boston University School of Medicine, and colleagues found that observed relationships between social determinants of health (SDH) such as food and housing insecurity and longer lapses between diagnostic breast imaging/biopsy appointments are supportive of the idea that SDH may influence medical care and ultimately outcomes.
The authors evaluated electronic medical record data, including responses to a novel SDH screening tool called THRIVE in use at the Boston University School of Medicine, as well as clinical data from a breast imaging clinic. A multivariate analysis was conducted to assess the duration of lapse (time between imaging appointments) as it relates to their explanatory SDH variables and controlled for demographic data. The researchers found that food and housing insecurity were both associated with a longer lapse between diagnostic breast imaging and biopsy. Meanwhile, paradoxically, inadequate access to transportation was associated with a shorter lapse between diagnostic breast imaging and biopsy.
"At this time, it remains unclear how this might influence clinical practice," Afran said. "However, our findings are certainly supportive of the hypothesis that addressing social determinants of health such as food and housing insecurity might positively benefit patients, particularly as it relates to keeping their medical appointments and improving clinical outcomes."
Maximillian Diaz, a biomedical engineering Ph.D. student at the University of Florida in Gainesville, and colleagues found that they were able to diagnose Parkinson disease using a basic photograph of the eye and machine learning.
The authors built two datasets of fundus eye images, a generalized dataset of images from the U.K. Biobank and a clinical practice dataset of images collected at the University of Florida Center for Movement Disorders. The authors then used a convolution neural network (a type of deep learning) to select the blood vessels in each image to be used as inputs into a support vector machine classifier to perform the diagnosis. The researchers found that a machine learning classifier assessing the blood vessels in the eye can diagnose Parkinson disease. The machine learning classifier performed successfully on both a large, generalized database and data collected in a clinical setting. The machine learning network appears to focus on smaller blood vessels, which is in line with previous studies in the literature.
"By using an everyday smartphone camera to obtain the required image, it is easier to not only get this in more clinical settings, but also to underdeveloped regions that may not have the resources required for equipment typically used to diagnose brain diseases," Diaz said. "We are hoping that further research can be done to better understand the progression of Parkinson disease and lead to solutions that can prevent the disease progression or hopefully reverse the neurological damage."
Abhilash Kizhakke Puliyakote, Ph.D., of the University of California San Diego School of Medicine, and colleagues found that exposure to environmental pollutants from biomass fuels can lead to considerable lung damage.
The authors recruited women near Thanjavur, India, who cooked primarily with wood fuels or liquified petroleum gas. The women were assessed for lung function using spirometry and imaged on a GE 128-slice CT scanner at total lung capacity (TLC; full inspiration) and residual volume (RV; full expiration). Using advanced quantitative image analysis software tools to register TLC and RV images, the researchers computed metrics of regional lung function. CT images revealed evidence of lung inflammation and associated air trapping whereby inhaled gas is unable to escape upon exhalation, thus limiting gas exchange (oxygen in and carbon dioxide out).
"Detecting early-stage alterations in lung function are critical in halting and reversing the course of chronic lung diseases that may arise from prolonged exposures. Our results indicate that in the presence of diffuse inflammation, changes in lung function may go undiagnosed by traditional lung function tests and CT imaging metrics derived from static snapshots of the lung," Puliyakote said. "Use of advanced quantitative CT imaging and image analysis provides a new window into regional lung function, thus providing an important tool for better understanding the correlations of exposure and lung pathophysiology, which will hopefully lead to improved control of environmental exposures and to better understand who is at risk and how to intervene to limit the long-term lung damage."
RSNA: Ulnar Fractures May Indicate Intimate Partner Violence
MONDAY, Dec. 7, 2020 (HealthDay News) -- Up to one-third of women with isolated ulnar fractures may have confirmed or suspected intimate partner violence, according to a study presented at the annual meeting of the Radiological Society of North America, held virtually from Nov. 29 to Dec. 5.
RSNA: Deep Learning Model Can Predict Breast Cancer Risk
THURSDAY, Dec. 3, 2020 (HealthDay News) -- A deep learning model using screening mammography imaging biomarkers can improve accuracy for predicting future breast cancer risk, according to a study presented at the annual meeting of the Radiological Society of North America, held virtually from Nov. 29 to Dec. 5.
RSNA: Sleeve Gastrectomy in Teens May Harm Bone Health
WEDNESDAY, Dec. 2, 2020 (HealthDay News) -- Adolescents with obesity undergoing sleeve gastrectomy have a decrease in lumbar volumetric bone mineral density, which is associated with increased lumbar marrow adipose tissue, according to a study presented at the annual meeting of the Radiological Society of North America, held virtually from Nov. 29 to Dec. 5.
RSNA: Anxiety May Hasten Progression to Alzheimer Disease
WEDNESDAY, Nov. 25, 2020 (HealthDay News) -- Apolipoprotein E4 genotype, anxiety, and lower hippocampal and entorhinal cortex volumes are associated with an elevated progression rate from mild cognitive impairment to Alzheimer disease, according to a study scheduled for presentation at the annual meeting of the Radiological Society of North America, held virtually from Nov. 29 to Dec. 5.
RSNA: Neurologic Complications of COVID-19 Examined
TUESDAY, Nov. 24, 2020 (HealthDay News) -- More than one-fifth of patients with COVID-19 presenting with neurologic findings who underwent neuroimaging had critical findings, according to a study scheduled for presentation at the annual meeting of the Radiological Society of North America, held virtually from Nov. 29 to Dec. 5.
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Updated on May 25, 2022
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