Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




New MRI Techniques Help Predict Neuro Outcomes

By MedImaging International staff writers
Posted on 23 Oct 2017
Image: The images show an fMRI scan of a healthy control subject on the left; a scan of a patient after a cardiac arrest with a good functional outcome in the middle; and a cardiac arrest patient with a poor functional outcome on the right (Photo courtesy of RSNA).
Image: The images show an fMRI scan of a healthy control subject on the left; a scan of a patient after a cardiac arrest with a good functional outcome in the middle; and a cardiac arrest patient with a poor functional outcome on the right (Photo courtesy of RSNA).
Researchers are using advanced Magnetic Resonance Imaging (MRI) techniques to help predict the neurological outcomes of patients that survive a cardiac arrest.

The researchers used MRI-Diffusion Tensor Imaging (DTI) and resting-state functional MRI (fMRI) to show the large-scale functional integration, or connectome, of the brain.

The study included 46 patients who had suffered a cardiac arrest, and were in a coma, and was published online in the October 2017 issue of the journal Radiology by researchers from Johns Hopkins University School of Medicine (Baltimore, MD).

The researchers assessed the functional connectivity of the brain of the patients and found that brain connectivity measurements could predict the long-term recovery potential of patients with brain damage related to a cardiac arrest they had experienced. The researchers concluded that by carrying out MRI-based measurements of the functional connections in the brain they could better predict long-term recovery for those patients who suffered from a neurological disability following a cardiac arrest. The results also showed that connectivity measures could provide early markers of long-term recovery potential in such patients.

Lead author of the study, Robert D. Stevens, MD, said, “This is game-changing information about what happens in the brains of people who suffer cardiac arrest. We realize that network architectures can be selectively disrupted in this setting. Anti-correlation was preserved in patients who recovered and abolished in those who did not. Relative preservation of this anti-correlation was the most robust signal of a favorable outcome. Connectome studies have the potential to change not only outcome prediction, but to guide treatment as well."

Related Links:
Johns Hopkins University School of Medicine

X-Ray Illuminator
X-Ray Viewbox Illuminators
New
Mobile X-Ray System
K4W
Digital Intelligent Ferromagnetic Detector
Digital Ferromagnetic Detector
New
Digital Color Doppler Ultrasound System
MS22Plus

Channels

Nuclear Medicine

view channel
Image: Perovskite crystal boules are grown in carefully controlled conditions from the melt (Photo courtesy of Mercouri Kanatzidis/Northwestern University)

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

General/Advanced Imaging

view channel
Image: The Angio-CT solution integrates the latest advances in interventional imaging (Photo courtesy of Canon Medical)

Cutting-Edge Angio-CT Solution Offers New Therapeutic Possibilities

Maintaining accuracy and safety in interventional radiology is a constant challenge, especially as complex procedures require both high precision and efficiency. Traditional setups often involve multiple... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

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
Copyright © 2000-2025 Globetech Media. All rights reserved.