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.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
Radcal IBA  Group

Download Mobile App




Accelerated MRI Sequence Helps Radiologists Assess Heart Disease without Breath-Holding

By MedImaging International staff writers
Posted on 14 Feb 2024
Image: MRI examinations require patients to repeatedly perform breath holds to avoid respiratory artifacts (Photo courtesy of 123RF)
Image: MRI examinations require patients to repeatedly perform breath holds to avoid respiratory artifacts (Photo courtesy of 123RF)

Cardiac magnetic resonance imaging (MRI) is essential for evaluating and diagnosing heart damage resulting from poor blood flow. Traditional cardiac MRI examinations are time-consuming and typically require patients to perform multiple breath holds to prevent respiratory artifacts. This can be challenging, especially for patients with ischemic heart disease, and may lead to compromised image quality and potential measurement inaccuracies. Now, an accelerated MRI sequence can help radiologists assess ischemic heart disease without requiring patients to hold their breath.

Scientists at Amiens University Hospital (Amiens, France) conducted a prospective study involving patients undergoing cardiac MRI for ischemic heart disease assessment between March and June 2023. The study included an innovative, free-breathing, short-axis imaging sequence that utilized deep learning for image reconstruction. Two radiologists evaluated the image quality of both the traditional and the new MRI methods. The study involved a total of 26 patients.

The results showed that the acquisition time was shorter with the deep learning-based method compared to the standard sequence. Furthermore, this accelerated approach demonstrated no significant difference in assessing the left ventricular ejection fraction, an important measure of heart function. The radiologists observed that the subjective image quality of the deep learning-based images was superior. However, they also noted an increased frequency of blurring artifacts in these images.

“The improved subjective image quality of the cine-deep learning sequence likely in part relates to the sequence’s respiratory synchronization, in comparison with the standard sequence’s reliance on adequate breath-holding, which may be challenging in dyspneic patients,” concluded David Monteuuis, MD, at Amiens University Hospital.

Related Links:
Amiens University Hospital

Post-Processing Imaging System
DynaCAD Prostate
Digital Radiographic System
OMNERA 300M
Digital Intelligent Ferromagnetic Detector
Digital Ferromagnetic Detector
Ultrasound Needle Guidance System
SonoSite L25

Channels

Nuclear Medicine

view channel
Image: LHSCRI scientist Dr. Glenn Bauman stands in front of the PET scanner (Photo courtesy of LHSCRI)

New Imaging Solution Improves Survival for Patients with Recurring Prostate Cancer

Detecting recurrent prostate cancer remains one of the most difficult challenges in oncology, as standard imaging methods such as bone scans and CT scans often fail to accurately locate small or early-stage tumors.... 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.