ArticleMagnetic resonance imaging2021
Improved nerve conspicuity with water-weighting and denoising in two-point Dixon magnetic resonance neurography.
Article in Magnetic resonance imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Efficient and complete fat suppression in two-point Dixon MR imaging: sequence considerations and assessment in lumbar plexus imaging.Skeletal radiology · 2026Article
- An Adaptive Learning Image Denoising Algorithm Based on Eigenvalue Extraction and the GAN Model.Computational intelligence and neuroscience · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
backgroundT PURPOSE: To quantify effects of principal component analysis (PCA) denoising on tissue signal intensities and fat fraction (FF) and to determine qualitative image quality improvements from both denoising and water-weighting (WW) algorithms to improve nerve conspicuity and fat suppression. STUDY TYPE: Prospective. SUBJECTS: Twenty-one subjects undergoing MR neurography evaluation (11/10 male/female, mean age = 46.3±13.7 years) with 60 image volumes. Twelve subjects (23 image volumes) were determined to have muscle denervation based on diffusely elevated T FIELD STRENGTH/SEQUENCE: 3 T, 2D, two-point Dixon FSE. ASSESSMENT: Qualitative assessment included overall image quality, nerve conspicuity, fat suppression, pulsation and ringing artifacts by 3 radiologists separately on a three-point scale (1 = poor, 2 = average, 3 = excellent). Quantitative measurements for FF and signal intensity relative to normal muscle were made for nerve, abnormal muscle and subcutaneous fat. STATISTICAL TESTS: Linear and ordinal regression models were used for quantitative and qualitative comparisons, respectively; 95% confidence intervals (CIs) and p-values for pairwise comparisons were adjusted using the Holm-Bonferroni method. Inter-rater agreement was assessed using Gwet's agreement coefficient (AC
resultsSimulations showed PCA-denoising reduced FF error from 2.0% to 1.0%, and from 7.6% to 3.1% at noise levels of 10% and 30%, respectively. In human subjects, PCA-denoising did not change signal levels and FF quantitatively. WW decreased fat signal significantly (-83.6%, p < 0.001). Nerve conspicuity was improved by WW (odds ratio, OR = 5.8, p < 0.001). Fat suppression was improved by both PCA (OR = 3.6, p < 0.001) and WW (OR = 2.2, p < 0.001). Overall image quality was improved by PCA + WW (OR = 1.7, p = 0.04).
conclusionsWW and PCA-denoising improved nerve conspicuity and fat suppression in MR neurography. Denoising can potentially provide improved accuracy of FF maps for assessing fat-infiltrated muscle.
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