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 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
- Higher Chest X-Ray Usage Catches Lung Cancer Earlier and Improves Survival
- AI-Powered Mammograms Predict Cardiovascular Risk
- Generative AI Model Significantly Reduces Chest X-Ray Reading Time
- AI-Powered Mammography Screening Boosts Cancer Detection in Single-Reader Settings
- Photon Counting Detectors Promise Fast Color X-Ray Images
- AI Can Flag Mammograms for Supplemental MRI
- 3D CT Imaging from Single X-Ray Projection Reduces Radiation Exposure
Channels
Radiography
view channel
AI Helps Radiologists Spot More Lesions in Mammograms
Breast cancer is a critical health issue, and accurate detection through mammography is essential for effective treatment. However, interpreting mammograms can be challenging for radiologists, particularly... Read more
AI Detects Fatty Liver Disease from Chest X-Rays
Fatty liver disease, which results from excess fat accumulation in the liver, is believed to impact approximately one in four individuals globally. If not addressed in time, it can progress to severe conditions... Read moreUltrasound
view channel
Pain-Free Breast Imaging System Performs One Minute Cancer Scan
Breast cancer is one of the leading causes of death for women worldwide, and early detection is key to improving outcomes. Traditional methods like mammograms and ultrasound have their limitations, particularly... Read more
Wireless Chronic Pain Management Device to Reduce Need for Painkillers and Surgery
Chronic pain affects millions of people globally, often leading to long-term disability and dependence on opioid medications, which carry significant risks of side effects and addiction.... Read moreNuclear Medicine
view channel
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 more
New Imaging Approach Could Reduce Need for Biopsies to Monitor Prostate Cancer
Prostate cancer is the second leading cause of cancer-related death among men in the United States. However, the majority of older men diagnosed with prostate cancer have slow-growing, low-risk forms of... Read moreGeneral/Advanced Imaging
view channel
CT Colonography Beats Stool DNA Testing for Colon Cancer Screening
As colorectal cancer remains the second leading cause of cancer-related deaths worldwide, early detection through screening is vital to reduce advanced-stage treatments and associated costs.... Read more
First-Of-Its-Kind Wearable Device Offers Revolutionary Alternative to CT Scans
Currently, patients with conditions such as heart failure, pneumonia, or respiratory distress often require multiple imaging procedures that are intermittent, disruptive, and involve high levels of radiation.... Read more
AI-Based CT Scan Analysis Predicts Early-Stage Kidney Damage Due to Cancer Treatments
Radioligand therapy, a form of targeted nuclear medicine, has recently gained attention for its potential in treating specific types of tumors. However, one of the potential side effects of this therapy... 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