Literature DB >> 31654542

Denoising of diffusion MRI improves peripheral nerve conspicuity and reproducibility.

Darryl B Sneag1, Kelly C Zochowski1, Ek T Tan2, Sophie C Queler1, Alissa Burge1, Yoshimi Endo1, Bin Lin1, Maggie Fung3, Jaemin Shin3.   

Abstract

BACKGROUND: Quantitative diffusion MRI is a promising technique for evaluating peripheral nerve integrity but low signal-to-noise ratio (SNR) can impede measurement accuracy.
PURPOSE: To evaluate principal component analysis (PCA) and generalized spherical deconvolution (genSD) denoising techniques to improve within-subject reproducibility and peripheral nerve conspicuity. STUDY TYPE: Prospective.
SUBJECTS: Seven healthy volunteers and three peripheral neuropathy patients. FIELD STRENGTH/SEQUENCE: 3T/multiband single-shot echo planar diffusion sequence using multishell 55-direction scheme. ASSESSMENT: Images were processed using four methods: "original" (no denoising), "average" (10 repetitions), "PCA-only," and "PCA + genSD." Tibial and common peroneal nerve segmentations and masks were generated from volunteer diffusion data. Quantitative (SNR and contrast-to-noise ratio [CNR]) values were calculated. Three radiologists qualitatively evaluated nerve conspicuity for each method. The two denoising methods were also performed in three patients with peripheral neuropathies. STATISTICAL TESTS: For healthy volunteers, calculations included SNR and CNRFA (computed using FA values). Coefficient of variation (CV%) of CNRFA quantified within-subject reproducibility. Groups were compared with two-sample t-tests (significance P < 0.05; two-tailed, Bonferroni-corrected). Odds ratios (ORs) quantified the relative rates of each of three radiologists confidently identifying a nerve, per slice, for the four methods.
RESULTS: "PCA + genSD" yielded the highest SNR (meanoverall = 14.83 ± 1.99) and tibial and common peroneal nerve CNRFA (meantibial = 3.45, meanperoneal = 2.34) compared to "original" (P SNR < 0.001; P CNR = 0.011) and "PCA-only" (P SNR < 0.001, P CNR < 0.001). "PCA + genSD" had higher within-subject reproducibility (low CV%) for tibial (6.04 ± 1.98) and common peroneal nerves (8.27 ± 2.75) compared to "original" and "PCA-only." The mean FA was higher for "original" than "average" (P < 0.001), but did not differ significantly between "average" and "PCA + genSD" (P = 0.14). "PCA + genSD" had higher tibial and common peroneal nerve conspicuity than "PCA-only" (ORtibial = 2.50, P < 0.001; ORperoneal = 1.86, P < 0.001) and "original" (ORtibial = 2.73, P < 0.001; ORperoneal = 2.43, P < 0.001). DATA
CONCLUSION: PCA + genSD denoising method improved SNR, CNRFA , and within-subject reproducibility (CV%) without biasing FA and nerve conspicuity. This technique holds promise for facilitating more reliable, unbiased diffusion measurements of peripheral nerves. LEVEL OF EVIDENCE: 2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1128-1137.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  3T; MRI; denoising; diffusion tensor imaging; peripheral nerve

Mesh:

Year:  2019        PMID: 31654542     DOI: 10.1002/jmri.26965

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  4 in total

Review 1.  Technological Advancements in Magnetic Resonance Neurography.

Authors:  Darryl B Sneag; Sophie Queler
Journal:  Curr Neurol Neurosci Rep       Date:  2019-08-24       Impact factor: 5.081

2.  Diffusion MRI fiber diameter for muscle denervation assessment.

Authors:  Ek T Tan; Kelly C Zochowski; Darryl B Sneag
Journal:  Quant Imaging Med Surg       Date:  2022-01

3.  Denoising and Multiple Tissue Compartment Visualization of Multi-b-Valued Breast Diffusion MRI.

Authors:  Ek T Tan; Lisa J Wilmes; Bonnie N Joe; Natsuko Onishi; Vignesh A Arasu; Nola M Hylton; Luca Marinelli; David C Newitt
Journal:  J Magn Reson Imaging       Date:  2020-07-02       Impact factor: 4.813

4.  Clinical Application of Diffusion Tensor Imaging for a Brachial Plexus Injury.

Authors:  Giulio Vara; Gianmarco Tuzzato; Giuseppe Bianchi; Marco Miceli; Luca Spinardi; Rita Golfieri; Raffaella Rinaldi; Giancarlo Facchini
Journal:  Diagnostics (Basel)       Date:  2022-07-11
  4 in total

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