Purpose There is an absence of reproducibility studies on MRI‐based body composition analysis in current literature. Therefore, the aim of this study was to investigate the between‐scanner reproducibility and the repeatability of a method for MRI‐based body composition analysis. Methods Eighteen healthy volunteers of varying body mass index and adiposity were each scanned twice on five different 1.5T and 3T scanners from three different vendors. Two‐point Dixon neck‐to knee images and two additional liver scans were acquired with similar protocols. Visceral adipose tissue (VAT) volume, abdominal subcutaneous adipose tissue (ASAT) volume, thigh muscle volume, and muscle fat infiltration (MFI) in the thigh muscle were measured. Liver proton density fat fraction (PDFF) was assessed using two different methods, the scanner vendor's 6‐point method and an in‐house 2‐point method. Within‐scanner test‐retest repeatability and between‐scanner reproducibility were calculated using analysis of variance. Results Repeatability coefficients were 13 centiliters (cl) (VAT), 24 cl (ASAT), 17 cl (total thigh muscle volume), 0.53% (MFI), and 1.27‐1.37% for liver PDFF. Reproducibility coefficients were 24 cl (VAT), 42 cl (ASAT), 31 cl (total thigh muscle volume), 1.44% (MFI), and 2.37‐2.40% for liver PDFF. Conclusion For all measures except MFI, the within‐scanner repeatability explained much of the overall reproducibility. The two methods for measuring liver fat had similar reproducibility. This study showed that the investigated method eliminates effects due to scanner differences. The results can be used for power calculations in clinical studies or to better understand the scanner‐induced variability in clinical applications.
There is an unmet need to identify biomarkers sensitive to change in rare, slowly progressive neuromuscular diseases. Quantitative magnetic resonance imaging (MRI) of muscle may offer this opportunity, as it is noninvasive and can be carried out almost independent of patient cooperation and disease severity. Muscle fat content correlates with muscle function in neuromuscular diseases, and changes in fat content precede changes in function, which suggests that muscle MRI is a strong biomarker candidate to predict prognosis and treatment efficacy. In this paper, we review the evidence suggesting that muscle MRI may be an important biomarker for diagnosis and to monitor change in disease severity.
A noninvasive prediction of whole-muscle extensibility may directly guide pre-operative planning to determine if the torn edge could efficiently cover the original footprint while aiding in postoperative evaluation of RC repair. Muscle Nerve 57: 129-135, 2018.
this study aimed to validate a fully automatic method to quantify knee-extensor muscle volume and exercise-induced hypertrophy. By using a magnetic resonance imaging-based fat-water separated twopoint Dixon sequence, the agreement between automated and manual segmentation of a specific ~15cm region (partial volume) of the quadriceps muscle was assessed. We then explored the sensitivity of the automated technique to detect changes in both complete and partial quadriceps volume in response to 8 weeks of resistance training in 26 healthy men and women. There was a very strong correlation (r = 0.98, P < 0.0001) between the manual and automated method for assessing partial quadriceps volume, yet the volume was 9.6% greater with automated compared with manual analysis (P < 0.0001, 95% limits of agreement −93.3 ± 137.8 cm 3 ). Partial muscle volume showed a 6.0 ± 5.0% (manual) and 4.8 ± 8.3% (automated) increase with training (P < 0.0001). Similarly, the complete quadriceps increased 5.1 ± 5.5% with training (P < 0.0001). The intramuscular fat proportion decreased (P < 0.001) from 4.1% to 3.9% after training. In conclusion, the automated method showed excellent correlation with manual segmentation and could detect clinically relevant magnitudes of exercise-induced muscle hypertrophy. this method could have broad application to accurately measure muscle mass in sports or to monitor clinical conditions associated with muscle wasting and fat infiltration.Body composition plays a crucial role for overall health but also in specific sports and clinical settings. A number of pathological conditions are associated with reduced muscle mass, including muscular dystrophies, spinal cord injuries, sarcopenia, cancer, heart failure, neurological disease and inflammatory myopathies. In sports, muscle mass can be a major determinant of performance, and athletic injuries are typically associated with reduced muscle mass 1 . In all of the scenarios where muscle atrophy is evident, loss of strength and functional capacity most often occur in parallel 2 .Numerous methods and techniques have been developed to assess body composition. These techniques include hydro-densitometry, air-displacement plethysmography, dual-energy x-ray absorptiometry (DXA), ultrasound and bio-impedance. In particular, the use of the DXA-method has increased in popularity over recent years, and is now commonly used in research studies assessing lean mass in cross-sectional or interventional studies 3,4 . While the DXA-method is relatively easy to use and requires essentially no manual data analysis, it is still subject to a number of limitations when detailed measurements of regional muscle mass are warranted 4 . The DXA scan uses ionizing radiation, provides only 2-dimensional projections of the body, and is based on several assumptions regarding segment constancy in tissue composition 5 . Moreover, the DXA-method underestimates the degree of age-related loss of muscle mass 6 , and it is not possible to separate between different muscle groups, or to quantify mus...
Background and Objectives:Facioscapulohumeral muscular dystrophy (FSHD) is a rare, debilitating disease characterized by progressive muscle weakness. MRI is a sensitive assessment of disease severity and progression. We developed a quantitative whole-body (WB) musculoskeletal MRI (WB-MSK-MRI) protocol analyzing muscles in their entirety. This study aimed to assess WB-MSK-MRI as a potential imaging biomarker providing reliable measurements of muscle health that capture disease heterogeneity and clinically meaningful composite assessments correlating with severity and more responsive to change in clinical trials.Methods:Participants 18 to 65 years, genetically confirmed FSHD1, clinical severity 2 to 4 (Ricci’s scale, range 0-5), and ≥1 short tau inversion recovery (STIR)-positive lower extremity muscle eligible for needle biopsy enrolled at 6 sites; imaged twice 4 - 12 weeks apart. Volumetric analysis of muscle fat infiltration (MFI), muscle fat fraction (MFF), and lean muscle volume (LMV) in 18 (36 total) muscles from bilateral shoulder, proximal arm, trunk, and legs was performed after automated atlas-based segmentation followed by manual verification. A WB composite score, including muscles at highest risk for progression, and functional cross-sectional composites for correlation with relevant functional outcomes including timed up and go (TUG), FSHD-TUG, and reachable workspace (RWS) were developed.Results:Seventeen participants;16 follow-up MRIs performed at 52 days (range 36 to 85). Functional cross-sectional composites (MFF and MFI) showed moderate to strong correlations: TUG (rho=0.71, rho=0.83), FSHD-TUG (rho=0.73, rho=0.73), and RWS (left arm: rho=-0.71, rho=-0.53; right arm: rho=-0.61, rho=-0.65). WB composite variability:LMVtot, coefficient of variation (CV) 1.9% and 3.4%; MFFtot, within-subject standard deviation (Sw) 0.5% and 1.5%; MFItot, (Sw), 0.3% and 0.4% for normal and intermediate muscles respectively. CV and Sw were higher in intermediate (MFI≥0.10; MFF<0.50) than in normal (MFI<0.10, MFF<0.50) muscles.Discussion:We developed a WB-MSK-MRI protocol and composite measures that capture disease heterogeneity and assess muscle involvement as it correlates with FSHD-relevant clinical endpoints. Functional composites robustly correlate with functional assessments. Stability of the WB composite shows it could be an assessment of change in therapeutic clinical trials.Classification of evidence:This study provides Class II evidence that quantitative WB-MSK-MRI findings associate with FSHD1 severity measured using established functional assessments.
Objectives: We examined the longitudinal and cross-sectional relationship between automated MRI-analysis and single-slice axial CT imaging for determining muscle size and muscle fat infiltration (MFI) of the anterior thigh. Methods: Twenty-two patients completing sex-hormone treatment expected to result in muscle hypertrophy (n = 12) and atrophy (n = 10) underwent MRI scans using 2-point Dixon fat/water-separated sequences and CT scans using a system operating at 120 kV and a fixed flux of 100 mA. At baseline and 12 months after, automated volumetric MRI analysis of the anterior thigh was performed bilaterally, and fat-free muscle volume and MFI were computed. In addition, cross-sectional area (CSA) and radiological attenuation (RA) (as a marker of fat infiltration) were calculated from single slice axial CT-images using threshold-assisted planimetry. Linear regression models were used to convert units. Results: There was a strong correlation between MRI-derived fat-free muscle volume and CT-derived CSA (R = 0.91), and between MRI-derived MFI and CT-derived RA (R = −0.81). The 95% limits of agreement were ±0.32 L for muscle volume and ±1.3% units for %MFI. The longitudinal change in muscle size and MFI was comparable across imaging modalities. Conclusions: Both automated MRI and single-slice CT-imaging can be used to reliably quantify anterior thigh muscle size and MFI. Advances in knowledge: This is the first study examining the intermodal agreement between automated MRI analysis and CT-image assessment of muscle size and MFI in the anterior thigh muscles. Our results support that both CT- and MRI-derived measures of muscle size and MFI can be used in clinical settings.
Introduction/Aims: Functional performance tests are the gold standard to assess disease progression and treatment effects in neuromuscular disorders. These tests can be confounded by motivation, pain, fatigue, and learning effects, increasing variability and decreasing sensitivity to disease progression, limiting efficacy assessment in clinical trials with small sample sizes. We aimed to develop and validate a quantitative and objective method to measure skeletal muscle volume and fat content based on whole-body fat-referenced magnetic resonance imaging (MRI) for use in multisite clinical trials. Methods: Subjects aged 18 to 65 years, genetically confirmed facioscapulohumeral muscular dystrophy 1 (FSHD1), clinical severity 2 to 4 (Ricci's scale, range 0-5), were enrolled at six sites and imaged twice 4-12 weeks apart with T1-weighted two-point Dixon MRI covering the torso and upper and lower extremities. Thirty-six muscles were volumetrically segmented using semi-automatic multi-atlas-based segmentation. Muscle fat fraction (MFF), muscle fat infiltration (MFI), and lean muscle volume (LMV) were quantified for each muscle using fat-referenced quantification.Results: Seventeen patients (mean age ± SD, 49.4 years ±13.02; 12 men) were enrolled. Within-patient SD ranged from 1.00% to 3.51% for MFF and 0.40% to 1.48% for MFI in individual muscles. For LMV, coefficients of variation ranged from 2.7% to 11.7%. For the composite score average of all muscles, observed SDs were 0.70% and 0.32% for MFF and MFI, respectively; composite LMV coefficient of variation was 2.0%. Discussion:We developed and validated a method for measuring skeletal muscle volume and fat content for use in multisite clinical trials of neuromuscular disorders.
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