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
GLOBETECH PUBLISHING LLC

Download Mobile App




Deep Learning-Based Reconstruction Algorithm Halves Lumbar MRI Scan Times

By MedImaging International staff writers
Posted on 06 Jul 2023
Print article
Image: A deep learning-based reconstruction algorithm has been shown to improve lumbar MRI scan times (Photo courtesy of Freepik)
Image: A deep learning-based reconstruction algorithm has been shown to improve lumbar MRI scan times (Photo courtesy of Freepik)

Low back pain, with its myriad of common and potential causes, can often be identified through magnetic resonance imaging (MRI), a diagnostic imaging modality increasingly utilized in modern medicine. MRI offers superior soft tissue resolution and does not expose patients to ionizing radiation. However, it is impaired by lengthy acquisition times and the need for parameter adjustments to enhance image quality, which can further extend scan times. Over recent years, artificial intelligence (AI), specifically deep learning (DL), has made significant strides in various imaging areas, including image classification, segmentation, denoising, super-resolution, and image synthesis/transformation. Nevertheless, the impact of AI algorithms on routine whole MRI lumbar spine protocol acquisition has yet to be explored.

In a new study, researchers at Sant'Andrea University Hospital (Rome, Italy) compared quantitative and subjective image quality, scanning time, and diagnostic confidence between a novel deep learning-based reconstruction (DLR) algorithm and the standard MRI protocol for the lumbar spine. By using the DLR algorithm, researchers were able to cut the duration of lumbar MRI exams by half. Furthermore, these improved scan times did not compromise image quality but rather enhanced the signal-to-noise ratio. For this study, GE Healthcare's FDA-approved AIR Recon DL algorithm was applied to the exams of 80 healthy volunteers who underwent a 1.5T MRI examination of the lumbar spine between September 2021 and May 2023. Both the DLR algorithm and standard protocols were utilized to complete sequences, which were later assessed by two radiologists who were unaware of the reconstruction techniques used.

The DLR algorithm yielded a notable reduction in protocol scanning time, reducing it from almost 13 minutes to just over 6 minutes. The blinded radiologists reported that the reconstruction algorithm provided a higher SNR across all sequences and superior CNR for axial and sagittal T2-weighted fast spin echo images. Both readers rated the overall image quality for all sequences as superior with the DLR, leading the research team to suggest that the DLR protocol can be safely integrated into clinical practice. The team also noted additional benefits of shortening lumbar MRI protocols, including cost-effectiveness and enhanced patient compliance, especially for those who are claustrophobic or experiencing severe physical pain.

Related Links:
Sant'Andrea University Hospital 

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Ultrasound Color LCD
U156W
Remote Controlled Digital Radiography and Fluoroscopy System
Eco Track-DRF - MARS 50/MARS50+/MARS 65/MARS 80
New
Mobile Digital X-Ray System
MobileDiagnost wDR 2.1

Print article
Radcal

Channels

Radiography

view channel
Image: 3D cinematic renderings of the control and diseased heart in anatomic orientation (Photo courtesy of ESRF)

Innovative X-Ray Technique Captures Human Heart with Unprecedented Detail

Cardiovascular disease remains the leading cause of death globally. In 2019, ischemic heart disease, which weakens the heart due to reduced blood supply, accounted for approximately 8.9 million or 16%... Read more

Ultrasound

view channel
Image: The new FDA-cleared AI-enabled applications have been integrated into the EPIQ CVx and Affiniti CVx ultrasound systems (Photo courtesy of Royal Philips)

Next-Gen AI-Enabled Cardiovascular Ultrasound Platform Speeds Up Analysis

Heart failure is a significant global health challenge, affecting approximately 64 million individuals worldwide. It is associated with high mortality rates and poor quality of life, placing a considerable... Read more

General/Advanced Imaging

view channel
Image: HeartFlow Plaque Analysis leverages cutting-edge AI for assessment of plaque quantity and composition (Photo courtesy of HeartFlow, Inc.)

Next Gen Interactive Plaque Analysis Platform Assesses Patient Risk in Suspected Coronary Artery Disease

A first-of-its-kind plaque analysis tool to be fully integrated with FFRCT (when FFRCT is performed) provides impactful insights that enhance clinical decision-making and enable personalized patient treatment... 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

Industry News

view channel
Image: The new collaborations aim to further advance AI foundation models for medical imaging (Photo courtesy of Microsoft)

Microsoft collaborates with Leading Academic Medical Systems to Advance AI in Medical Imaging

Medical imaging is a critical component of healthcare, with health systems spending roughly USD 65 billion annually on imaging alone, and about 80% of all hospital and health system visits involve at least... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.