What type of study is this?

This is a Quantitative Study study.

September 17, 2025

Specialized Coil Informed Deep Learning for High SNR Carotid Imaging

Key Points

Significant improvements in signal-to-noise ratio (SNR) were achieved in carotid imaging, enhancing plaque evaluation.
Deep learning effectively matched the image quality obtained from standard head-neck coils to that of specialized carotid coils.
Multi-contrast images and T1/T2 maps showed marked enhancements, increasing diagnostic confidence and efficiency.
The findings indicate that high SNR images can be produced without costly specialized coils, broadening accessibility.

Abstract

Motivation: Noise from standard commercial head-neck coils used for carotid MR hinders effective evaluation of high-risk plaque characteristics, while specialized carotid coils remain costly and are not widely available. Goal(s): We aim to match the signal-to-noise ratio and quality of images obtained from standard head-neck coils to those of dedicated carotid coils. Approach: A supervised deep learning method was developed to improve carotid MR image quality using data acquired with specialized carotid coil as the reference. Results: Significant improvements in SNR and image quality were observed for multi-contrast images and T1/ T2 maps. Impact: With the use of our DL model, high SNR images are achievable with standard head-neck coils, which may help radiologists to be more confident and efficient in evaluating carotid plaque characteristics.

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