High-Resolution Scans Combined with Analysis to Help Detect Concussions
By Andrew Deutsch Posted on 14 Dec 2016 |

Image: A Magnetoencephalography (MEG) imaging is also used for patients with suspected concussion injuries of the brain (Photo courtesy of University of California, San Francisco).
Researchers in the Canada have found that there is a better chance of detecting concussion in the brain when patients undergo high-resolution Magnetoncephalography (MEG) scans, than if they undergo standard MRI or CT imaging.
The study was published in the December 2016 issue of the journal PLOS Computational Biology, and showed that MEG, which maps interactions between different brain regions, can be used to detect neural changes better than standard imaging. Mild Traumatic Brain Injuries (MTBI), a frequent injury in American football players, are also not easily detected by conventional imaging scans.
The researchers from the Simon Fraser University (SFU; Burnaby, BC, Canada) took MEG imaging scans of 41 men between 20 and 44 years old, half of who had a diagnosis of concussion in the three months prior to the scan, and found observable changes in communication between different areas of the patient’s brains. MEG functional neuroimaging is an imaging technique used for mapping brain activity that currently uses extremely sensitive magnetometers called Superconducting Quantum Interference Devices (SQUIDs).
One of the researchers, Vasily Vakorin, from the Behavioral and Cognitive Neuroscience Institute at the SFU, said, "Changes in communication between brain areas, as detected by MEG, allowed us to detect concussion from individual scans, in situations where MRI or CT failed."
Related Links:
Simon Fraser University
The study was published in the December 2016 issue of the journal PLOS Computational Biology, and showed that MEG, which maps interactions between different brain regions, can be used to detect neural changes better than standard imaging. Mild Traumatic Brain Injuries (MTBI), a frequent injury in American football players, are also not easily detected by conventional imaging scans.
The researchers from the Simon Fraser University (SFU; Burnaby, BC, Canada) took MEG imaging scans of 41 men between 20 and 44 years old, half of who had a diagnosis of concussion in the three months prior to the scan, and found observable changes in communication between different areas of the patient’s brains. MEG functional neuroimaging is an imaging technique used for mapping brain activity that currently uses extremely sensitive magnetometers called Superconducting Quantum Interference Devices (SQUIDs).
One of the researchers, Vasily Vakorin, from the Behavioral and Cognitive Neuroscience Institute at the SFU, said, "Changes in communication between brain areas, as detected by MEG, allowed us to detect concussion from individual scans, in situations where MRI or CT failed."
Related Links:
Simon Fraser University
Latest Radiography News
- AI Algorithm Uses Mammograms to Accurately Predict Cardiovascular Risk in Women
- AI Hybrid Strategy Improves Mammogram Interpretation
- AI Technology Predicts Personalized Five-Year Risk of Developing Breast Cancer
- RSNA AI Challenge Models Can Independently Interpret Mammograms
- New Technique Combines X-Ray Imaging and Radar for Safer Cancer Diagnosis
- New AI Tool Helps Doctors Read Chest X‑Rays Better
- Wearable X-Ray Imaging Detecting Fabric to Provide On-The-Go Diagnostic Scanning
- AI Helps Radiologists Spot More Lesions in Mammograms
- AI Detects Fatty Liver Disease from Chest X-Rays
- AI Detects Hidden Heart Disease in Existing CT Chest Scans
- Ultra-Lightweight AI Model Runs Without GPU to Break Barriers in Lung Cancer Diagnosis
- AI Radiology Tool Identifies Life-Threatening Conditions in Milliseconds
- Machine Learning Algorithm Identifies Cardiovascular Risk from Routine Bone Density Scans
- AI Improves Early Detection of Interval Breast Cancers
- World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
- AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Channels
Radiography
view channel
AI Algorithm Uses Mammograms to Accurately Predict Cardiovascular Risk in Women
Cardiovascular disease remains the leading cause of death in women worldwide, responsible for about nine million deaths annually. Despite this burden, symptoms and risk factors are often under-recognized... Read more
AI Hybrid Strategy Improves Mammogram Interpretation
Breast cancer screening programs rely heavily on radiologists interpreting mammograms, a process that is time-intensive and subject to errors. While artificial intelligence (AI) models have shown strong... Read moreUltrasound
view channel
Non-Invasive Ultrasound-Based Tool Accurately Detects Infant Meningitis
Meningitis, an inflammation of the membranes surrounding the brain and spinal cord, can be fatal in infants if not diagnosed and treated early. Even when treated, it may leave lasting damage, such as cognitive... Read more
Breakthrough Deep Learning Model Enhances Handheld 3D Medical Imaging
Ultrasound imaging is a vital diagnostic technique used to visualize internal organs and tissues in real time and to guide procedures such as biopsies and injections. When paired with photoacoustic imaging... Read moreNuclear Medicine
view channel
PET Tracer Enables Same-Day Imaging of Triple-Negative Breast and Urothelial Cancers
Triple-negative breast cancer (TNBC) and urothelial bladder carcinoma (UBC) are aggressive cancers often diagnosed at advanced stages, leaving limited time for effective treatment decisions.... Read more
New Camera Sees Inside Human Body for Enhanced Scanning and Diagnosis
Nuclear medicine scans like single-photon emission computed tomography (SPECT) allow doctors to observe heart function, track blood flow, and detect hidden diseases. However, current detectors are either... Read more
Novel Bacteria-Specific PET Imaging Approach Detects Hard-To-Diagnose Lung Infections
Mycobacteroides abscessus is a rapidly growing mycobacteria that primarily affects immunocompromised patients and those with underlying lung diseases, such as cystic fibrosis or chronic obstructive pulmonary... Read moreGeneral/Advanced Imaging
view channel
New Ultrasmall, Light-Sensitive Nanoparticles Could Serve as Contrast Agents
Medical imaging technologies face ongoing challenges in capturing accurate, detailed views of internal processes, especially in conditions like cancer, where tracking disease development and treatment... Read more
AI Algorithm Accurately Predicts Pancreatic Cancer Metastasis Using Routine CT Images
In pancreatic cancer, detecting whether the disease has spread to other organs is critical for determining whether surgery is appropriate. If metastasis is present, surgery is not recommended, yet current... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology
The global artificial intelligence (AI) in medical diagnostics market is expanding with early disease detection being one of its key applications and image recognition becoming a compelling consumer proposition... Read moreIndustry News
view channel
GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
GE HealthCare (Chicago, IL, USA) has entered into a collaboration with NVIDIA (Santa Clara, CA, USA), expanding the existing relationship between the two companies to focus on pioneering innovation in... Read more
Patient-Specific 3D-Printed Phantoms Transform CT Imaging
New research has highlighted how anatomically precise, patient-specific 3D-printed phantoms are proving to be scalable, cost-effective, and efficient tools in the development of new CT scan algorithms... Read more
Siemens and Sectra Collaborate on Enhancing Radiology Workflows
Siemens Healthineers (Forchheim, Germany) and Sectra (Linköping, Sweden) have entered into a collaboration aimed at enhancing radiologists' diagnostic capabilities and, in turn, improving patient care... Read more