Explore these preview press releases to learn about highlights of some of the innovative medical imaging research and new technologies that will be presented at RSNA 2023. Press releases are distributed to the media throughout the week to increase public awareness of radiology and its role in personal health care.
Hidden Belly Fat in Midlife Linked to Alzheimer’s Disease
Higher amounts of visceral abdominal fat in midlife are linked to the development of Alzheimer’s disease, according to a new study from Mallinckrodt Institute of Radiology at Washington University School of Medicine in St. Louis. Researchers analyzed data from 54 cognitively healthy participants, ranging in age from 40 to 60 years old, with an average BMI of 32. Using MRI and PET, the researchers found that a higher visceral to subcutaneous fat ratio was associated with higher amyloid PET tracer uptake in the precuneus cortex, the region known to be affected early by amyloid pathology in Alzheimer’s disease, and that higher visceral fat measurements were related to an increased burden of inflammation in the brain.
Access the presentation, “Visceral Abdominal Adipose Tissue and Insulin Resistance Respectively Influence Alzheimer’s Disease Amyloid Pathology and Neurodegeneration in Midlife,” (M2-SPNR-13) on demand at Meeting.RSNA.org.
New Treatment Restores Sense of Smell in Patients with Long COVID
Using an image-guided, minimally invasive procedure, researchers may be able to restore the sense of smell in patients who have suffered with long-COVID, according to a new study from Jefferson Health in Philadelphia. For the study, 54 patients were referred from an ear, nose and throat specialist after at least six months of post-COVID parosmia that was resistant to pharmaceutical and topical therapies. CT guidance was used to position a spinal needle at the base of the neck for injection into the stellate ganglion. At follow-up one week later, 59% of patients reported improvement in symptoms.
Access the presentation, “Stellate Ganglion Block with CT Guidance for Post-COVID Parosmia," (T5A-SPHN-6) on demand at Meeting.RSNA.org.
MRI Reveals Brain Activity Behind Fanaticism
Soccer fans exhibit different patterns of brain activation while watching a match that may trigger positive and negative emotions and behaviors, according to research from Universidad San Sebastián, Santiago, Chile. Researchers used fMRI to measure brain activity in 43 fans of rival soccer teams during match play. When their team wins, the reward system in the fan’s brain is activated, but when they lose, the mentalization network may be activated, or the mechanism that regulates cognitive control may be inhibited. The findings lend themselves to extreme fanaticism in other areas like politics and may shed light on social dynamics in all walks of life.
Access the presentation, “Brain Mechanisms Underlying Emotional Response in Social Pain. Football as a Proxy to Study Fanatism: An fMRI Study," (M5A-SPNR-6) on demand at Meeting.RSNA.org.
Novel MRI Reveals Brain Changes in Long-COVID Patients
COVID-19 infection is associated with long-lasting microstructural brain changes, and patients with long COVID had different patterns of brain changes than people who had recovered from the infection without any long-term symptoms, according to a new study from University Hospital Freiburg in Germany. Researchers used diffusion microstructure imaging to examine 89 patients with long COVID, 38 patients who had fully recovered from COVID-19, and 46 healthy controls. The results showed a specific pattern of microstructural changes in various brain regions, which differed between those who had long COVID and those who did not.
Access the presentation, “Cerebral Microstructural Alterations in Post-Covid-Condition are Related to Cognitive Impairment, Olfactory Dysfunction and Fatigue," (S4-SSNR01-4) on demand at Meeting.RSNA.org.
AI Identifies Non-smokers at High Risk for Lung Cancer
Using a routine chest X-ray image, an AI tool can identify non-smokers who are at high risk for lung cancer, according to a study from the Cardiovascular Imaging Research Center at Massachusetts General Hospital in Boston. The “CXR-Lung-Risk” model was developed using 147,497 chest X-rays of 40,643 asymptomatic smokers and never-smokers, based on a single chest X-ray image as input. Of 17,407 patients included in the study, 28% were deemed high risk by the deep learning model, and 2.9% of these patients later had a diagnosis of lung cancer. The high-risk group well exceeded the 1.3% six-year risk threshold where lung cancer screening CT is recommended by National Comprehensive Cancer Network guidelines.
Access the presentation, “Lung Cancer Risk Using Never Smokers’ Chest X-Rays: Validation of a Deep Learning-based Model," (M5A-SPCH-6) on demand at Meeting.RSNA.org.
Visit RSNA.org/Press23 for additional press releases from RSNA 2023.
