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
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+
New
X-Ray QA Meter
Piranha CT
Wireless Handheld Ultrasound System
TE Air
Silver Member
Mobile X-Ray Barrier
Lead Acrylic Mobile X-Ray Barriers

Print article

Channels

Nuclear Medicine

view channel
Image: Researchers have identified a new imaging biomarker for tumor responses to ICB therapy (Photo courtesy of 123RF)

New PET Biomarker Predicts Success of Immune Checkpoint Blockade Therapy

Immunotherapies, such as immune checkpoint blockade (ICB), have shown promising clinical results in treating melanoma, non-small cell lung cancer, and other tumor types. However, the effectiveness of these... 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 © 2000-2024 Globetech Media. All rights reserved.