Free-breathing Magnetic Resonance Imaging Assessment of Body Composition in Healthy and Overweight Children: An Observational Study.
Ontology highlight
ABSTRACT:
SUBMITTER: Ly KV
PROVIDER: S-EPMC6752952 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature
Publications
Free-breathing Magnetic Resonance Imaging Assessment of Body Composition in Healthy and Overweight Children: An Observational Study.
Ly Karrie V KV Armstrong Tess T Yeh Joanna J Ghahremani Shahnaz S Kim Grace H GH Wu Holden H HH Calkins Kara L KL
Journal of pediatric gastroenterology and nutrition 20190601 6
<h4>Objective</h4>Conventional, breath-holding magnetic resonance imaging (MRI) assesses body composition by measuring fat volumes and proton density fat fraction (PDFF). However, breath-holding MRI is not always feasible in children. This study's objective was to use free-breathing MRI to quantify visceral and subcutaneous fat volumes and PDFFs and correlate these measurements with hepatic PDFF.<h4>Methods</h4>This was an observational, hypothesis-forming study that enrolled 2 groups of childre ...[more]
Similar Datasets
Project description:To develop a simplified magnetic resonance imaging method (MRI) to assess total adipose tissue (AT) and adipose tissue free mass (ATFM) from three single MRI slices in people with overweight/obesity in order to implement body composition follow-up in a clinical research setting. Body composition of 310 participants (70 women and 240 men, age: 50.8 ± 10.6 years, BMI: 31.3 ± 5.6 kg.m-2) was assessed with 3 single slices (T6-T7, L4-L5 and at mid-thigh) MRI. Multiple regression analysis was used to develop equations predicting AT and ATFM from these three single slices. Then we implemented a longitudinal phase consisting in a 2-month exercise training program during which we tested the sensitivity of these equations in a subgroup of participants with overweight/obesity (n = 79) by comparing the exercise-induced variations between predicted and measured AT and ATFM. The following equations: total AT = - 12.74105 + (0.02919 × age) + (4.27634 × sex (M = 0, F = 1)) + (0.22008 × weight) + (26.92234 × AT T6-T7) + (23.70142 × AT L4-L5) + (37.94739 × AT mid-thigh) and total ATFM = - 33.10721 + (- 0.02363 × age) + (- 3.58052 × sex (M = 0, F = 1)) + (30.02252 × height) + (0.08549 × weight) + (11.36859 × ATFM T6-T7) + (27.82244 × ATFM L4-L5) + (58.62648 × ATFM mid-thigh) showed an excellent prediction (adjusted R2 = 97.2% and R2 = 92.5%; CCC = 0.986 and 0.962, respectively). There was no significant difference between predicted and measured methods regarding the AT variations (- 0.07 ± 2.02 kg, p = 0.70) and the ATFM variations (0.16 ± 2.41 kg, p = 0.49) induced by 2-months of exercise training. This simplified method allows a fully accurate assessment of the body composition of people with obesity in less than 20 min (10 min for images acquisition and analysis, respectively), useful for a follow-up.
| S-EPMC10333272 | biostudies-literature
Project description:PURPOSE:To develop and validate a new prospective respiratory motion compensation algorithm for free-breathing whole-heart 3D cine steady-state free precession (SSFP) imaging. METHODS:In a 3D cine SSFP sequence, 4 excitations per cardiac cycle are re-purposed to prospectively track heart position. Specifically, their 1D image is reconstructed and routed into the scanner's standard diaphragmatic navigator processing system. If all 4 signals are in end-expiration, cine image data from the entire cardiac cycle is accepted for image reconstruction. Prospective validation was carried out in patients (N?=?17) by comparing in each a conventional breath-hold 2D cine ventricular short-axis stack and a free-breathing whole-heart 3D cine data set. RESULTS:All 3D cine SSFP acquisitions were successful and the mean scan time was 5.9?±?2.7?min. Left and right ventricular end-diastolic, end-systolic, and stroke volumes by 3D cine SSFP were all larger than those from 2D cine SSFP. This bias was?<?6% except for right ventricular end-systolic volume that was 12%. The 3D cine images had a lower ventricular blood-to-myocardium contrast ratio, contrast-to-noise ratio, mass, and subjective quality score. CONCLUSION:The novel prospective respiratory motion compensation method for 3D cine SSFP imaging was robust and efficient and yielded slightly larger ventricular volumes and lower mass compared to breath-hold 2D cine imaging. Magn Reson Med 80:181-189, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
| S-EPMC5876089 | biostudies-literature
Project description:Dynamic contrast-enhanced quantitative first-pass perfusion using magnetic resonance imaging enables non-invasive objective assessment of myocardial ischemia without ionizing radiation. However, quantification of perfusion is challenging due to the non-linearity between the magnetic resonance signal intensity and contrast agent concentration. Furthermore, respiratory motion during data acquisition precludes quantification of perfusion. While motion correction techniques have been proposed, they have been hampered by the challenge of accounting for dramatic contrast changes during the bolus and long execution times. In this work we investigate the use of a novel free-breathing multi-echo Dixon technique for quantitative myocardial perfusion. The Dixon fat images, unaffected by the dynamic contrast-enhancement, are used to efficiently estimate rigid-body respiratory motion and the computed transformations are applied to the corresponding diagnostic water images. This is followed by a second non-linear correction step using the Dixon water images to remove residual motion. The proposed Dixon motion correction technique was compared to the state-of-the-art technique (spatiotemporal based registration). We demonstrate that the proposed method performs comparably to the state-of-the-art but is significantly faster to execute. Furthermore, the proposed technique can be used to correct for the decay of signal due to T2* effects to improve quantification and additionally, yields fat-free diagnostic images.
| S-EPMC7392760 | biostudies-literature
Project description:The aims of this study were to observe the pattern of transient motion after gadoxetic acid administration including incidence, onset, and duration, and to evaluate the clinical feasibility of free-breathing gadoxetic acid-enhanced liver magnetic resonance imaging using golden-angle radial sparse parallel (GRASP) imaging with respiratory gating.In this institutional review board-approved prospective study, 59 patients who provided informed consents were analyzed. Free-breathing dynamic T1-weighted images (T1WIs) were obtained using GRASP at 3 T after a standard dose of gadoxetic acid (0.025 mmol/kg) administration at a rate of 1 mL/s, and development of transient motion was monitored, which is defined as a distinctive respiratory frequency alteration of the self-gating MR signals. Early arterial, late arterial, and portal venous phases retrospectively reconstructed with and without respiratory gating and with different temporal resolutions (nongated 13.3-second, gated 13.3-second, gated 6-second T1WI) were evaluated for image quality and motion artifacts. Diagnostic performance in detecting focal liver lesions was compared among the 3 data sets.Transient motion (mean duration, 21.5 ± 13.0 seconds) was observed in 40.0% (23/59) of patients, 73.9% (17/23) of which developed within 15 seconds after gadoxetic acid administration. On late arterial phase, motion artifacts were significantly reduced on gated 13.3-second and 6-second T1WI (3.64 ± 0.34, 3.61 ± 0.36, respectively), compared with nongated 13.3-second T1WI (3.12 ± 0.51, P < 0.0001). Overall, image quality was the highest on gated 13.3-second T1WI (3.76 ± 0.39) followed by gated 6-second and nongated 13.3-second T1WI (3.39 ± 0.55, 2.57 ± 0.57, P < 0.0001). Only gated 6-second T1WI showed significantly higher detection performance than nongated 13.3-second T1WI (figure of merit, 0.69 [0.63-0.76]) vs 0.60 [0.56-0.65], P = 0.004).Transient motion developed in 40% (23/59) of patients shortly after gadoxetic acid administration, and gated free-breathing T1WI using GRASP was able to consistently provide acceptable arterial phase imaging in patients who exhibited transient motion.
| S-EPMC6080614 | biostudies-literature
Project description:BackgroundMagnetic resonance imaging (MRI) is the gold standard for evaluating body composition. However, the reference ranges have not been established.MethodsThree lean tissue and seven adipose tissue parameters based on MRI data from the UK Biobank were used in this study. Participants with European ancestry and data on at least one parameter were screened. Age- and sex-specific percentile curves were generated using the lambda-mu-sigma method. Three levels of reference ranges were provided, which were equivalent to the mean ± 1 standard deviation (SD), 2 SDs and 2.5 SDs.ResultsThe final analysis set for each parameter ranged from 4842 to 14 148 participants (53.4%-56.6% women) with a median age of 61. For lean tissue parameters, compared with those at age 45, the median total lean tissue volume and total thigh fat-free muscle volume at age 70 were 2.83 and 1.73 L, and 3.02 and 1.51 L lower in men and women, respectively. The median weight-to-muscle ratios at age 45 were 0.51 and 0.83 kg/L lower compared with those at age 70 in men and women, respectively. Adipose tissue parameters showed inconsistent differences. In men, the median muscle fat infiltration, visceral adipose tissue (VAT) volume, total abdominal adipose tissue index and abdominal fat ratio were 1.48%, 0.32 L, 0.08 L/m2 and 0.4 higher, and the median abdominal subcutaneous adipose tissue (ASAT) volume and total adipose tissue volume were 0.47 and 0.41 L lower, respectively, at age 70 than at age 45. The median total trunk fat volume was approximately 9.53 L at all ages. In women, the median muscle fat infiltration and VAT volume were 1.68% and 0.76 L higher, respectively, at age 70 than at age 45. The median ASAT volume, total adipose tissue volume, total trunk fat volume, total abdominal adipose tissue index and abdominal fat ratio were 0.35 L, 0.78 L, 1.12 L, 0.49 L/m2 and 0.06 higher, respectively, at age 60 than at age 45. The medians of the former three parameters were 0.33 L, 0.14 L and 0.20 L lower, at age 70 than at age 60. The medians of the latter two parameters were approximately 3.64 L/m2 and 0.55 at ages between 60 and 70.ConclusionsWe have established reference ranges for MRI-measured body composition parameters in a large community-dwelling population. These findings provide a more accurate assessment of abnormal adipose and muscle conditions.
| S-EPMC10067500 | biostudies-literature
Project description:BackgroundEndogenous contrast T1? cardiovascular magnetic resonance (CMR) can detect scar or infiltrative fibrosis in patients with ischemic or non-ischemic cardiomyopathy. Existing 2D T1? techniques have limited spatial coverage or require multiple breath-holds. The purpose of this project was to develop an accelerated, free-breathing 3D T1? mapping sequence with whole left ventricle coverage using a multicoil, compressed sensing (CS) reconstruction technique for rapid reconstruction of undersampled k-space data.MethodsWe developed a cardiac- and respiratory-gated, free-breathing 3D T1? sequence and acquired data using a variable-density k-space sampling pattern (A?=?3). The effect of the transient magnetization trajectory, incomplete recovery of magnetization between T1?-preparations (heart rate dependence), and k-space sampling pattern on T1? relaxation time error and edge blurring was analyzed using Bloch simulations for normal and chronically infarcted myocardium. Sequence accuracy and repeatability was evaluated using MnCl2 phantoms with different T1? relaxation times and compared to 2D measurements. We further assessed accuracy and repeatability in healthy subjects and compared these results to 2D breath-held measurements.ResultsThe error in T1? due to incomplete recovery of magnetization between T1?-preparations was T1?healthy =?6.1% and T1?infarct =?10.8% at 60?bpm and T1?healthy =?13.2% and T1?infarct =?19.6% at 90?bpm. At a heart rate of 60?bpm, error from the combined effects of readout-dependent magnetization transients, k-space undersampling and reordering was T1?healthy =?12.6% and T1?infarct =?5.8%. CS reconstructions had improved edge sharpness (blur metric?=?0.15) compared to inverse Fourier transform reconstructions (blur metric?=?0.48). There was strong agreement between the mean T1? estimated from the 2D and accelerated 3D data (R2 =?0.99; P <?0.05) acquired on the MnCl2 phantoms. The mean R1? estimated from the accelerated 3D sequence was highly correlated with MnCl2 concentration (R2 =?0.99; P?<?0.05). 3D T1? acquisitions were successful in all human subjects. There was no significant bias between undersampled 3D T1? and breath-held 2D T1? (mean bias?=?0.87) and the measurements had good repeatability (COV2D =?6.4% and COV3D =?7.1%).ConclusionsThis is the first report of an accelerated, free-breathing 3D T1? mapping of the left ventricle. This technique may improve non-contrast myocardial tissue characterization in patients with heart disease in a scan time appropriate for patients.
| S-EPMC6327532 | biostudies-literature
Project description:PURPOSE:To evaluate the accuracy and repeatability of a free-breathing, non-electrocardiogram (ECG), continuous myocardial T1 and extracellular volume (ECV) mapping technique adapted from the Multitasking framework. METHODS:The Multitasking framework is adapted to quantify both myocardial native T1 and ECV with a free-breathing, non-ECG, continuous acquisition T1 mapping method. We acquire interleaved high-spatial resolution image data and high-temporal resolution auxiliary data following inversion-recovery pulses at set intervals and perform low-rank tensor imaging to reconstruct images at 344 inversion times, 20 cardiac phases, and 6 respiratory phases. The accuracy and repeatability of Multitasking T1 mapping in generating native T1 and ECV maps are compared with conventional techniques in a phantom, a simulation, 12 healthy subjects, and 10 acute myocardial infarction patients. RESULTS:In phantoms, Multitasking T1 mapping correlated strongly with the gold-standard spin-echo inversion recovery (R2 = 0.99). A simulation study demonstrated that Multitasking T1 mapping has similar myocardial sharpness to the fully sampled ground truth. In vivo native T1 and ECV values from Multitasking T1 mapping agree well with conventional MOLLI values and show good repeatability for native T1 and ECV mapping for 60 seconds, 30 seconds, or 15 seconds of data. Multitasking native T1 and ECV in myocardial infarction patients correlate positively with values from MOLLI. CONCLUSION:Multitasking T1 mapping can quantify native T1 and ECV in the myocardium with free-breathing, non-ECG, continuous scans with good image quality and good repeatability in vivo in healthy subjects, and correlation with MOLLI T1 and ECV in acute myocardial infarction patients.
| S-EPMC6372325 | biostudies-literature
Project description:BackgroundMulti-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction.MethodsA high-dimensional model-guided deep dictionary learning (HMDDL) algorithm is proposed for the acceleration. The HMDDL combines the powers of the high-dimensional dictionary learning neural network (hdDLNN) and the chemical shift model. The neural network utilizes the prior information of the dynamic multi-echo data in spatial respiratory motion, and echo dimensions to exploit the features of images. The chemical shift model is used to guide the reconstruction of field maps, R2∗ maps, water images, and fat images. Data acquired from ten healthy subjects and ten subjects with clinically diagnosed nonalcoholic fatty liver disease (NAFLD) were selected for training. Data acquired from one healthy subject and two NAFLD subjects were selected for validation. Data acquired from five healthy subjects and five NAFLD subjects were selected for testing. A three-dimensional (3D) blipped golden-angle stack-of-stars multi-gradient-echo pulse sequence was designed to accelerate the data acquisition. The retrospectively undersampled data were used for training, and the prospectively undersampled data were used for testing. The performance of the HMDDL was evaluated in comparison with the compressed sensing-based water-fat separation (CS-WF) algorithm and a parallel non-Cartesian recurrent neural network (PNCRNN) algorithm.ResultsFour-dimensional water-fat images with ten motion states for whole-liver are demonstrated at several R values. In comparison with the CS-WF and PNCRNN, the HMDDL improved the mean peak signal-to-noise ratio (PSNR) of images by 9.93 and 2.20 dB, respectively, and improved the mean structure similarity (SSIM) of images by 0.058 and 0.009, respectively, at R=10. The paired t-test shows that there was no significant difference between HMDDL and ground truth for proton-density fat fraction (PDFF) and R2∗ values at R up to 10.ConclusionsThe proposed HMDDL enables features of water images and fat images from the highly undersampled multi-echo data along spatial, respiratory motion, and echo dimensions, to improve the performance of accelerated four-dimensional (4D) free-breathing water-fat imaging.
| S-EPMC11007520 | biostudies-literature
Project description:In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice's coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice's coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice's coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice's coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future.
| S-EPMC10866998 | biostudies-literature
Project description:Background Adiposity is associated with larger left ventricular mass in children and adults. The role of body fat distribution in these associations is not clear. We examined the associations of body fat distribution and overweight with cardiac measures obtained by cardiac magnetic resonance imaging in school-age children. Methods and Results In a population-based cohort study including 2836 children, 10 years of age, we used anthropometric measures, dual-energy X-ray absorptiometry, and magnetic resonance imaging to collect information on body mass index, lean mass index, fat mass index, and abdominal visceral adipose tissue index. Indexes were standardized by height. Cardiac measures included right and left ventricular end-diastolic volume, left ventricular mass, and mass-to-volume ratio as a marker for concentricity. All body fat measures were positively associated with right and left ventricular end-diastolic volumes and left ventricular mass, with the strongest associations for lean mass index (all P<0.05). Obese children had a 1.12 standard deviation score (95% CI, 0.94-1.30) larger left ventricular mass and a 0.35 standard deviation score (95% CI, 0.14-0.57) higher left ventricular mass-to-volume ratio than normal weight children. Conditional on body mass index, higher lean mass index was associated with higher right and left ventricular end-diastolic volume and left ventricular mass, whereas higher fat mass measures were inversely associated with these cardiac measures (all P<0.05). Conclusions Higher childhood body mass index is associated with a larger right and left ventricular size. This association is influenced by higher lean mass. In childhood, lean mass may be a stronger determinant of heart growth than fat mass. Fat mass may influence cardiac structures at older ages.
| S-EPMC7670529 | biostudies-literature