4.2 Article

Image quality and lesion detectability of deep learning-accelerated T2-weighted Dixon imaging of the cervical spine

Journal

SKELETAL RADIOLOGY
Volume -, Issue -, Pages -

Publisher

SPRINGER
DOI: 10.1007/s00256-023-04364-x

Keywords

Deep learning; Deep learning acceleration; Deep learning accelerated Dixon imaging; Cervical spine magnetic resonance imaging

Ask authors/readers for more resources

The objective of this study was to compare the subjective image quality and lesion detectability of deep learning-accelerated Dixon (DL-Dixon) imaging with routine Dixon imaging of the cervical spine. Results showed that DL-Dixon imaging reduced acquisition time by 23.76% compared to routine Dixon imaging and provided better visibility of anatomical structures. There were no significant differences in lesion detectability between the two imaging methods.
ObjectivesTo validate the subjective image quality and lesion detectability of deep learning-accelerated Dixon (DL-Dixon) imaging of the cervical spine compared with routine Dixon imaging. Materials and methodsA total of 50 patients underwent sagittal routine Dixon and DL-Dixon imaging of the cervical spine. Acquisition parameters were compared and non-uniformity (NU) values were calculated. Two radiologists independently assessed the two imaging methods for subjective image quality and lesion detectability. Interreader and intermethod agreements were estimated with weighted kappa values. ResultsCompared with the routine Dixon imaging, the DL-Dixon imaging reduced the acquisition time by 23.76%. The NU value is slightly higher in DL-Dixon imaging (p value: 0.015). DL-Dixon imaging showed superior visibility of all four anatomical structures (spinal cord, disc margin, dorsal root ganglion, and facet joint) for both readers (p value: < 0.001 similar to 0.002). The motion artifact scores were slightly higher in the DL-Dixon images than in routine Dixon images (p value = 0.785). Intermethod agreements were almost perfect for disc herniation, facet osteoarthritis, uncovertebral arthritis, central canal stenosis (kappa range: 0.830 similar to 0.980, all p values < 0.001) and substantial to almost perfect for foraminal stenosis (kappa = 0.955, 0.705 for each reader). There was an improvement in the interreader agreement of foraminal stenosis by DL-Dixon images, from moderate to substantial agreement. ConclusionThe DLR sequence can substantially decrease the acquisition time of the Dixon sequence with subjective image quality at least as good as the conventional sequence. And no significant differences in lesion detectability were observed between the two sequence types.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available