BACKGROUND: T2-weighted, two-point Dixon fast-spin-echo (FSE) is an effective technique for magnetic resonance neurography (MRN) that can provide quantitative assessment of muscle denervation. Low signal-to-noise ratio and inadequate fat suppression, however, can impede accurate interpretation. 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 T2 signal intensity. 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 (AC2). RESULTS: Simulations 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). CONCLUSIONS: WW 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.
BACKGROUND: T2-weighted, two-point Dixon fast-spin-echo (FSE) is an effective technique for magnetic resonance neurography (MRN) that can provide quantitative assessment of muscle denervation. Low signal-to-noise ratio and inadequate fat suppression, however, can impede accurate interpretation. 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 T2 signal intensity. 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 (AC2). RESULTS: Simulations 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). CONCLUSIONS: WW 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.
Authors: Scott B Reeder; Zhifei Wen; Huanzhou Yu; Angel R Pineda; Garry E Gold; Michael Markl; Norbert J Pelc Journal: Magn Reson Med Date: 2004-01 Impact factor: 4.668
Authors: Scott B Reeder; Angel R Pineda; Zhifei Wen; Ann Shimakawa; Huanzhou Yu; Jean H Brittain; Garry E Gold; Christopher H Beaulieu; Norbert J Pelc Journal: Magn Reson Med Date: 2005-09 Impact factor: 4.668
Authors: Ami Mankodi; Courtney A Bishop; Sungyoung Auh; Rexford D Newbould; Kenneth H Fischbeck; Robert L Janiczek Journal: Neuromuscul Disord Date: 2016-07-28 Impact factor: 4.296
Authors: Robert L Janiczek; Giulio Gambarota; Christopher D J Sinclair; Tarek A Yousry; John S Thornton; Xavier Golay; Rexford D Newbould Journal: Magn Reson Med Date: 2011-05-20 Impact factor: 4.668