We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

MedImaging

Download Mobile App
Recent News Radiography MRI Ultrasound Nuclear Medicine General/Advanced Imaging Imaging IT Industry News

MRI Innovation That Makes Cancerous Tissue Glow Could Be a Game-Changer for Cancer Imaging

By MedImaging International staff writers
Posted on 22 Mar 2022
Print article
Image: MRI innovation makes cancerous tissue light up and easier to see (Photo courtesy of Pexels)
Image: MRI innovation makes cancerous tissue light up and easier to see (Photo courtesy of Pexels)

A new form of magnetic resonance imaging (MRI) that makes cancerous tissue glow in medical images could help doctors more accurately detect and track the progression of cancer over time.

The innovation, developed by researchers at the University of Waterloo (Ontario, Canada), creates images in which cancerous tissue appears to light up compared to healthy tissue, making it easier to see. Irregular packing of cells leads to differences in the way water molecules move in cancerous tissue compared to healthy tissue. The new technology, called synthetic correlated diffusion imaging, highlights these differences by capturing, synthesizing and mixing MRI signals at different gradient pulse strengths and timings.

In the largest study of its kind, the researchers applied the technology to a cohort of 200 patients with prostate cancer. Compared to standard MRI techniques, synthetic correlated diffusion imaging was better at delineating significant cancerous tissue, making it a potentially powerful tool for doctors and radiologists.

"Our studies show this new technology has promising potential to improve cancer screening, prognosis and treatment planning," said Alexander Wong, Canada Research Chair in Artificial Intelligence and Medical Imaging and a professor of systems design engineering at Waterloo. "Prostate cancer is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. That's why we targeted it first in our research. We also have very promising results for breast cancer screening, detection, and treatment planning. This could be a game-changer for many kinds of cancer imaging and clinical decision support."

Related Links:
University of Waterloo 

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
New
Pre-Op Planning Solution
Sectra 3D Trauma
New
Ultrasound Table
Ergonomic Advantage (EA) Line
Brachytherapy Planning System
Oncentra Brachy

Print article

Channels

Ultrasound

view channel
Image: The powerful machine learning algorithm can “interpret” echocardiogram images and assess key findings (Photo courtesy of 123RF)

Largest Model Trained On Echocardiography Images Assesses Heart Structure and Function

Foundation models represent an exciting frontier in generative artificial intelligence (AI), yet many lack the specialized medical data needed to make them applicable in healthcare settings.... Read more

Nuclear Medicine

view channel
Image: The multi-spectral optoacoustic tomography (MSOT) machine generates images of biological tissues (Photo courtesy of University of Missouri)

New Imaging Technique Monitors Inflammation Disorders without Radiation Exposure

Imaging inflammation using traditional radiological techniques presents significant challenges, including radiation exposure, poor image quality, high costs, and invasive procedures. Now, new contrast... 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