Fatty infiltrate and neck muscle volume in individuals with chronic whiplash associated disorders compared to healthy controls - a cross sectional case-control study.

BACKGROUND: The underlying pathophysiological mechanisms of chronic Whiplash Associated Disorders (WAD) are not fully understood. More knowledge of morphology is needed to better understand the disorder, improve diagnostics and treatments. The aim was to investigate dorsal neck muscle volume (MV) and muscle fat infiltration (MFI) in relation to self-reported neck disability among 30 participants with chronic WAD grade II-III compared to 30 matched healthy controls. METHODS: MV and MFI at spinal segments C4 through C7 in both sexes with mild- to moderate chronic WAD (n = 20), severe chronic WAD (n = 10), and age- and sex matched healthy controls (n = 30) was compared. Muscles: trapezius, splenius, semispinalis capitis and semispinalis cervicis were segmented by a blinded assessor and analyzed. RESULTS: Higher MFI was found in right trapezius (p = 0.007, Cohen's d = 0.9) among participants with severe chronic WAD compared to healthy controls. No other significant difference was found for MFI (p = 0.22-0.95) or MV (p = 0.20-0.76). CONCLUSIONS: There are quantifiable changes in muscle composition of right trapezius on the side of dominant pain and/or symptoms, among participants with severe chronic WAD. No other statistically significant differences were shown for MFI or MV. These findings add knowledge of the association between MFI, muscle size and self-reported neck disability in chronic WAD. TRIAL REGISTRATION: NA. This is a cross-sectional case-control embedded in a cohort study.

The effect on precision and T1 bias comparing two flip angles when estimating muscle fat infiltration using fat-referenced chemical shift-encoded imaging.

Investigation of the effect on accuracy and precision of different parameter settings is important for quantitative MRI. The purpose of this study was to investigate T1 bias and precision for muscle fat infiltration (MFI) measurements using fat-referenced chemical shift MFI measurements at flip angles of 5° and 10°. The fat-referenced measurements were compared with fat fractions, which is a more commonly used measure of MFI. This retrospective study was performed on data from a clinical intervention study including 40 postmenopausal women. Test and retest images were acquired with a 3-T scanner using four-point 3D spoiled gradient multiecho acquisition. Postprocessing included T2* correction and fat-referenced calibration, where the fat signal was calibrated using adipose tissue as reference. The mean MFI was calculated in six different muscle regions using both the fat-referenced fat signal and the fat fraction, defined as the fat signal divided by the sum of the fat and water signals. Both methods used the same fat and water images as input. The variance of the difference between mean MFI from test and retest was used as the measure of precision. The signal-to-noise ratio (SNR) characteristics were analyzed by measuring the full width at half maximum (FWHM) of the fat signal distribution. There was no difference in the mean MFI at different flip angles for the fat-referenced technique (p = 0.66), while the measured fat fractions were 3.3 percentage points larger for 10° compared with 5° (p < 0.001). No significant difference in the precision was found in any of the muscles analyzed. However, the FWHM of the fat signal distribution was significantly (p = 0.01) lower at 10°. This strenghtens the hypothesis that fat-referenced MFI is insensitive to flip angle-induced T1 bias in CSE-MRI, enabling usage of a higher and more SNR-effective flip angle. The lower FWHM in fat-referenced MFI at 10° indicates that high flip angle acquisition is advantageous even although no significant differences in precision were observed comparing 5° and 10°.

Reproducibility and repeatability of MRI-based body composition analysis.

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.

Pathophysiology behind prolonged whiplash associated disorders: study protocol for an experimental study.

BACKGROUND: There is insufficient knowledge of pathophysiological parameters to understand the mechanism behind prolonged whiplash associated disorders (WAD), and it is not known whether or not changes can be restored by rehabilitation. The aims of the projects are to investigate imaging and molecular biomarkers, cervical kinaesthesia, postural sway and the association with pain, disability and other outcomes in individuals with longstanding WAD, before and after a neck-specific exercise intervention. Another aim is to compare individuals with WAD with healthy controls. METHODS: Participants are a sub-group (n = 30) of individuals recruited from an ongoing randomized controlled study (RCT). Measurements in this experimental prospective study will be carried out at baseline (before intervention) and at a three month follow-up (end of physiotherapy intervention), and will include muscle structure and inflammation using magnetic resonance imaging (MRI), brain structure and function related to pain using functional MRI (fMRI), muscle function using ultrasonography, biomarkers using samples of blood and saliva, cervical kinaesthesia using the "butterfly test" and static balance test using an iPhone app. Association with other measures (self-reported and clinical measures) obtained in the RCT (e.g. background data, pain, disability, satisfaction with care, work ability, quality of life) may be investigated. Healthy volunteers matched for age and gender will be recruited as controls (n = 30). DISCUSSION: The study results may contribute to the development of improved diagnostics and improved rehabilitation methods for WAD. TRIAL REGISTRATION: Clinicaltrial.gov Protocol ID: NCT03664934, initial release 09/11/2018.

Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m2) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R2) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.

Robust water fat separated dual-echo MRI by phase-sensitive reconstruction.

PURPOSE: The purpose of this work was to develop and evaluate a robust water-fat separation method for T1-weighted symmetric two-point Dixon data. THEORY AND METHODS: A method for water-fat separation by phase unwrapping of the opposite-phase images by phase-sensitive reconstruction (PSR) is introduced. PSR consists of three steps; (1), identification of clusters of tissue voxels; (2), unwrapping of the phase in each cluster by solving Poisson's equation; and (3), finding the correct sign of each unwrapped opposite-phase cluster, so that the water-fat images are assigned the correct identities. Robustness was evaluated by counting the number of water-fat swap artifacts in a total of 733 image volumes. The method was also compared to commercial software. RESULTS: In the water-fat separated image volumes, the PSR method failed to unwrap the phase of one cluster and misclassified 10. One swap was observed in areas affected by motion and was constricted to the affected area. Twenty swaps were observed surrounding susceptibility artifacts, none of which spread outside the artifact affected regions. The PSR method had fewer swaps when compared to commercial software. CONCLUSION: The PSR method can robustly produce water-fat separated whole-body images based on symmetric two-echo spoiled gradient echo images, under both ideal conditions and in the presence of common artifacts. Magn Reson Med 78:1208-1216, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Test-retest reliability of rapid whole body and compartmental fat volume quantification on a widebore 3T MR system in normal-weight, overweight, and obese subjects.

PURPOSE: To measure the test-retest reliability of rapid (<15 min) whole body and visceral fat volume quantification in normal and obese subjects on a widebore 3T MR system and compare it with conventional manual segmentation. MATERIALS AND METHODS: Thirty participants (body mass index [BMI] 20.1-48.6 kg/m2 ) underwent two whole-body magnetic resonance imaging (MRI) examinations on a widebore 3T machine using a 2-point Dixon technique. Phase sensitive reconstruction and intensity inhomogeneity correction produced quantitative datasets of total adipose tissue (TAT), abdominal subcutaneous adipose tissue (ASAT), and visceral adipose tissue (VAT). The quantification was performed automatically using nonrigid atlas-based segmentation and compared with manual segmentation (SliceOmatic). RESULTS: The mean TAT was 31.74 L with a coefficient of variation (CV) of 0.79% and a coefficient of repeatability (CR) of 0.49 L. The ASAT was 7.92 L with a CV of 2.98% and a CR of 0.46 L. There was no significant difference in the semiautomated and manually segmented VAT (P = 0.73) but there were differences in the reliability of the two techniques. The mean semiautomated VAT was 2.56 L, CV 1.8%, and CR 0.09 L compared to the mean manually segmented VAT of 3.12 L, where the CV was 6.3% and the CR was 0.39 L. CONCLUSION: Rapid semiautomated whole body and compartmental fat volume quantification can be derived from a widebore 3T system, for a range of body sizes including obese patients, with "almost perfect" test-retest reliability. J. Magn. Reson. Imaging 2016;44:1464-1473.

Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies.

Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat-muscle quantitation system (AMRA(TM) Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRA(TM) Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA(TM) Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA(TM) Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA(TM) Profiler, opening up the possibility of large-scale human phenotypic studies.

Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water-fat MRI.

PURPOSE: To develop and demonstrate a rapid whole-body magnetic resonance imaging (MRI) method for automatic quantification of total and regional skeletal muscle volume. MATERIALS AND METHODS: The method was based on a multi-atlas segmentation of intensity corrected water-fat separated image volumes. Automatic lean muscle tissue segmentations were achieved by nonrigid registration of atlas datasets with 10 different manually segmented muscle groups. Ten subjects scanned at 1.5 T and 3.0 T were used as atlases, initial validation and optimization. Further validation used 11 subjects scanned at 3.0 T. The automated and manual segmentations were compared using intraclass correlation, true positive volume fractions, and delta volumes. RESULTS: For the 1.5 T datasets, the intraclass correlation, true positive volume fractions (mean ± standard deviation, SD), and delta volumes (mean ± SD) were 0.99, 0.91 ± 0.02, -0.10 ± 0.70L (whole body), 0.99, 0.93 ± 0.02, 0.01 ± 0.07L (left anterior thigh), and 0.98, 0.80 ± 0.07, -0.08 ± 0.15L (left abdomen). The corresponding values at 3.0 T were 0.97, 0.92 ± 0.03, -0.17 ± 1.37L (whole body), 0.99, 0.93 ± 0.03, 0.03 ± 0.08L (left anterior thigh), and 0.89, 0.90 ± 0.04, -0.03 ± 0.42L (left abdomen). The validation datasets showed similar results. CONCLUSION: The method accurately quantified the whole-body skeletal muscle volume and the volume of separate muscle groups independent of field strength and image resolution.

Consistent intensity inhomogeneity correction in water-fat MRI.

PURPOSE: To quantitatively and qualitatively evaluate the water-signal performance of the consistent intensity inhomogeneity correction (CIIC) method to correct for intensity inhomogeneities METHODS: Water-fat volumes were acquired using 1.5 Tesla (T) and 3.0T symmetrically sampled 2-point Dixon three-dimensional MRI. Two datasets: (i) 10 muscle tissue regions of interest (ROIs) from 10 subjects acquired with both 1.5T and 3.0T whole-body MRI. (ii) Seven liver tissue ROIs from 36 patients imaged using 1.5T MRI at six time points after Gd-EOB-DTPA injection. The performance of CIIC was evaluated quantitatively by analyzing its impact on the dispersion and bias of the water image ROI intensities, and qualitatively using side-by-side image comparisons. RESULTS: CIIC significantly ( P1.5T≤2.3×10-4,P3.0T≤1.0×10-6) decreased the nonphysiological intensity variance while preserving the average intensity levels. The side-by-side comparisons showed improved intensity consistency ( Pint⁡≤10-6) while not introducing artifacts ( Part=0.024) nor changed appearances ( Papp≤10-6). CONCLUSION: CIIC improves the spatiotemporal intensity consistency in regions of a homogenous tissue type.

Characterization of brown adipose tissue by water-fat separated magnetic resonance imaging.

BACKGROUND: To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long echo time, dual-echo Dixon imaging protocol. METHODS: A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by using the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 4° or 22°C for 5 days. The rats were then scanned in a 70 cm bore 3.0 Tesla MRI scanner and a human dual energy CT. Interscapular, paraaortal, and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots. RESULTS: The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (P < 0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (P = 0.0064) and significantly larger iBAT and prBAT volumes (P = 0.0017) were observed in the cold stimulated rats. CONCLUSION: The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism.

Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system.

PURPOSE: To measure the test-retest reproducibility of an automated system for quantifying whole body and compartmental muscle volumes using wide bore 3 T MRI. MATERIALS AND METHODS: Thirty volunteers stratified by body mass index underwent whole body 3 T MRI, two-point Dixon sequences, on two separate occasions. Water-fat separation was performed, with automated segmentation of whole body, torso, upper and lower leg volumes, and manually segmented lower leg muscle volumes. RESULTS: Mean automated total body muscle volume was 19·32 L (SD9·1) and 19·28 L (SD9·12) for first and second acquisitions (Intraclass correlation coefficient (ICC) = 1·0, 95% level of agreement -0·32-0·2 L). ICC for all automated test-retest muscle volumes were almost perfect (0·99-1·0) with 95% levels of agreement 1.8-6.6% of mean volume. Automated muscle volume measurements correlate closely with manual quantification (right lower leg: manual 1·68 L (2SD0·6) compared to automated 1·64 L (2SD 0·6), left lower leg: manual 1·69 L (2SD 0·64) compared to automated 1·63 L (SD0·61), correlation coefficients for automated and manual segmentation were 0·94-0·96). CONCLUSION: Fully automated whole body and compartmental muscle volume quantification can be achieved rapidly on a 3 T wide bore system with very low margins of error, excellent test-retest reliability and excellent correlation to manual segmentation in the lower leg. KEY POINTS: Sarcopaenia is an important reversible complication of a number of diseases. Manual quantification of muscle volume is time-consuming and expensive. Muscles can be imaged using in and out of phase MRI. Automated atlas-based segmentation can identify muscle groups. Automated muscle volume segmentation is reproducible and can replace manual measurements.

Resistance training decreased abdominal adiposity in postmenopausal women.

OBJECTIVE: To investigate if abdominal adipose tissue volumes and ratios change after a 15-week structured resistance training intervention in postmenopausal women with vasomotor symptoms (VMS). STUDY DESIGN: Sixty-five postmenopausal women with VMS and low physical activity were randomized to either three days/week supervised resistance training or unchanged physical activity for 15 weeks. Women underwent clinical anthropometric measurements and magnetic resonance imaging (MRI) at baseline and after 15 weeks. MRI was done using a Philips Ingenia 3.0 T MR scanner (Philips, Best, The Netherlands). The per protocol principle was used in the analysis of data. MAIN OUTCOME MEASUREMENTS: The absolute change from baseline to week 15 in visceral adipose tissue (VAT) volume and the relative ratio (VAT ratio) between VAT and total abdominal adipose tissue (TAAT), i.e. the sum of abdominal subcutaneous adipose tissue (ASAT) and VAT. RESULTS: There were no significant differences between the groups in characteristics, anthropometry or MRI measures at baseline. Women who were compliant with the intervention (i.e. participated in at least two of the three scheduled training sessions per week) had significantly different reduction over time in ASAT (p = 0.006), VAT (p = 0.002), TAAT (p = 0.003) and fat ratio (p < 0.001) compared with women in the control group. CONCLUSIONS: Implementation of a 15-week resistance training regimen in midlife may help women to counteract the abdominal fat redistribution associated with the menopausal transition. CLINICAL TRIALS: gov registered ID: NCT01987778.

Generalizing the mean intercept length tensor for gray-level images.

PURPOSE: The mean intercept length tensor is the most used technique to estimate microstructure orientation and anisotropy of trabecular bone. This paper proposes an efficient extension of this technique to gray-scale images based on a closed formulation of the mean intercept length tensor and a generalization using different angular convolution kernels. METHODS: First, the extended Gaussian image is computed for the binary or gray-scale image. Second, the intercepts are computed for all possible orientations through an angular convolution with the half-cosine function. Finally, the tensor is computed by means of the covariance matrix. The complexity of the method is O(n + m) in contrast with O(nm) of traditional implementations, where n is the number of voxels in the image and m is the number of orientations used in the computations. The method is generalized by applying other angular convolution kernels instead of the half-cosine function. As a result, the anisotropy of the tensor can be controlled while keeping the eigenvectors intact. RESULTS: The proposed extension to gray-scale yields accurate results for reliable computations of the extended Gaussian image and, unlike the traditional methodology, is not affected by artifacts generated by discretizations during the sampling of different orientations. CONCLUSIONS: Experiments show that the computations on both binary and gray-scale images are correlated, and that computations in gray-scale are more robust, enabling the use of the mean intercept length tensor to clinical examinations of trabecular bone. The use of kernels based on the von Mises-Fisher distribution is promising as the anisotropy can be adjusted with a parameter in order to improve its power to predict mechanical properties of trabecular bone.

Assessment of anterior thigh muscle size and fat infiltration using single-slice CT imaging versus automated MRI analysis in adults.

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.

Cardiometabolic Health Outcomes Associated With Discordant Visceral and Liver Fat Phenotypes: Insights From the Dallas Heart Study and UK Biobank.

OBJECTIVE: To evaluate the cardiometabolic outcomes associated with discordant visceral adipose tissue (VAT) and liver fat (LF) phenotypes in 2 cohorts. PATIENTS AND METHODS: Participants in the Dallas Heart Study underwent baseline imaging from January 1, 2000, through December 31, 2002, and were followed for incident cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) through 2013. Associations between VAT-LF groups (low-low, high-low, low-high, and high-high) and outcomes were assessed using multivariable-adjusted regression and were replicated in the independent UK Biobank. RESULTS: The Dallas Heart Study included 2064 participants (mean ± SD age, 44±9 years; 54% female; 47% black). High VAT-high LF and high VAT-low LF were associated with prevalent atherosclerosis, whereas low VAT-high LF was not. Of 1731 participants without CVD/T2DM, 128 (7.4%) developed CVD and 95 (5.5%) T2DM over a median of 12 years. High VAT-high LF and high VAT-low LF were associated with increased risk of CVD (hazard ratios [HRs], 2.0 [95% CI, 1.3 to 3.2] and 2.4 [95% CI, 1.4 to 4.1], respectively) and T2DM (odds ratios [ORs], 7.8 [95% CI, 3.8 to 15.8] and 3.3 [95% CI, 1.4 to 7.8], respectively), whereas low VAT-high LF was associated with T2DM (OR, 2.7 [95% CI, 1.1 to 6.7]). In the UK Biobank (N=22,354; April 2014-May 2020), only high VAT-low LF remained associated with CVD after multivariable adjustment for age and body mass index (HR, 1.5 [95% CI, 1.2 to 1.9]). CONCLUSION: Although VAT and LF are each associated with cardiometabolic risk, these observations demonstrate the importance of separating their cardiometabolic implications when there is presence or absence of either or both in an individual.

Sub-phenotyping Metabolic Disorders Using Body Composition: An Individualized, Nonparametric Approach Utilizing Large Data Sets.

OBJECTIVE: This study performed individual-centric, data-driven calculations of propensity for coronary heart disease (CHD) and type 2 diabetes (T2D), utilizing magnetic resonance imaging-acquired body composition measurements, for sub-phenotyping of obesity and nonalcoholic fatty liver disease (NAFLD). METHODS: A total of 10,019 participants from the UK Biobank imaging substudy were included and analyzed for visceral and abdominal subcutaneous adipose tissue, muscle fat infiltration, and liver fat. An adaption of the k-nearest neighbors algorithm was applied to the imaging variable space to calculate individualized CHD and T2D propensity and explore metabolic sub-phenotyping within obesity and NAFLD. RESULTS: The ranges of CHD and T2D propensity for the whole cohort were 1.3% to 58.0% and 0.6% to 42.0%, respectively. The diagnostic performance, area under the receiver operating characteristic curve (95% CI), using disease propensities for CHD and T2D detection was 0.75 (0.73-0.77) and 0.79 (0.77-0.81). Exploring individualized disease propensity, CHD phenotypes, T2D phenotypes, comorbid phenotypes, and metabolically healthy phenotypes were found within obesity and NAFLD. CONCLUSIONS: The adaptive k-nearest neighbors algorithm allowed an individual-centric assessment of each individual's metabolic phenotype moving beyond discrete categorizations of body composition. Within obesity and NAFLD, this may help in identifying which comorbidities a patient may develop and consequently enable optimization of treatment.

The relation between local and distal muscle fat infiltration in chronic whiplash using magnetic resonance imaging.

The objective of this study was to investigate the relationship between fat infiltration in the cervical multifidi and fat infiltration measured in the lower extremities to move further into understanding the complex signs and symptoms arising from a whiplash trauma. Thirty-one individuals with chronic whiplash associated disorders, stratified into a mild/moderate group and a severe group, together with 31 age- and gender matched controls were enrolled in this study. Magnetic resonance imaging was used to acquire a 3D volume of the neck and of the whole-body. Cervical multifidi was used to represent muscles local to the whiplash trauma and all muscles below the hip joint, the lower extremities, were representing widespread muscles distal to the site of the trauma. The fat infiltration was determined by fat fraction in the segmented images. There was a linear correlation between local and distal muscle fat infiltration (p<0.001, r2 = 0.28). The correlation remained significant when adjusting for age and WAD group (p = 0.009) as well as when correcting for age, WAD group and BMI (p = 0.002). There was a correlation between local and distal muscle fat infiltration within the severe WAD group (p = 0.0016, r2 = 0.69) and in the healthy group (p = 0.022, r2 = 0.17) but not in the mild/moderate group (p = 0.29, r2 = 0.06). No significant differences (p = 0.11) in the lower extremities' MFI between the different groups were found. The absence of differences between the groups in terms of lower extremities' muscle fat infiltration indicates that, in this particular population, the whiplash trauma has a local effect on muscle fat infiltration rather than a generalized.

Simulation of patient specific cervical hip fracture surgery with a volume haptic interface.

The interest for surgery simulator systems with anatomical models generated from authentic patient data is growing as these systems evolve. With access to volumetric patient data, e.g., from a computer tomography scan, haptic and visual feedback can be created directly from this dataset. This opens the door for patient specific simulations. Hip fracture surgery is one area where simulator systems is useful to train new surgeons and plan operations. To simulate the drilling procedure in this type of surgery, a repositioning of the fractured bone into correct position is first needed. This requires a segmentation process in which the bone segments are identified and the position of the dislocated part is determined. The segmentation must be automatic to cope with the large amount of data from the computer tomography scan. This work presents the first steps in the development of a hip fracture surgery simulation with patient specific models. Visual and haptic feedback is generated from the computer tomography data by simulating fluoroscopic images and the drilling process. We also present an automatic segmentation method to identify the fractured bone and determine the dislocation. This segmentation method is based on nonrigid registration with the Morphon method.

MRI adipose tissue and muscle composition analysis-a review of automation techniques.

MRI is becoming more frequently used in studies involving measurements of adipose tissue and volume and composition of skeletal muscles. The large amount of data generated by MRI calls for automated analysis methods. This review article presents a summary of automated and semi-automated techniques published between 2013 and 2017. Technical aspects and clinical applications for MRI-based adipose tissue and muscle composition analysis are discussed based on recently published studies. The conclusion is that very few clinical studies have used highly automated analysis methods, despite the rapidly increasing use of MRI for body composition analysis. Possible reasons for this are that the availability of highly automated methods has been limited for non-imaging experts, and also that there is a limited number of studies investigating the reproducibility of automated methods for MRI-based body composition analysis.