Breath‐hold MR measurements of fat fraction, T1, and T2* of water and fat in vertebral bone marrow

Ster, Caroline Le; Gambarota, Giulio; Lasbleiz, J.; Guillin, Raphaël; Decaux, Olivier; Saint‐Jalmes, Hervé

doi:10.1002/jmri.25205

Cited by 29 publications

(31 citation statements)

References 25 publications

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“…The fat spectrum varies from organ to organ and a fat spectrum suitable to liver may not give accurate values for bone marrow. In several previous studies, the fat spectrum was modeled using the liver fat spectrum characterized by Hamilton et al and only the three main peaks (0.9, 1.3, and 2–2.2 ppm) were considered . In our work, the presence of multiple peaks in the fat spectrum was considered using a precalibrated fat spectrum characterized in the red bone marrow .…”

Section: Discussionmentioning

confidence: 98%

“…The majority of CSE imaging that correct for T 2 * decay to improve the accuracy of marrow fat quantification assume a common (single‐ T 2 *) for water and fat, which is valid for liver applications at relatively low fat content. However, water and fat signals have independent T 2 * that may influence estimation of fat content, particularly at regions of high fat content and short T 2 *, which can be frequently encountered in bone marrow . In liver fat quantification, a single‐ T 2 * correction was chosen because of the advantage of a range of clinically relevant signal‐to‐noise ratios and water/fat ratios at low fat concentrations compared to dual‐ T 2 * correction .…”

Section: Discussionmentioning

confidence: 99%

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Comparison of chemical shift-encoded water-fat MRI and MR spectroscopy in quantification of marrow fat in postmenopausal females

Zheng

Gu³

et al. 2016

J. Magn. Reson. Imaging

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Purpose To validate a chemical shift‐encoded (CSE) water–fat imaging for quantifying marrow fat fraction (FF), using proton magnetic resonance spectroscopy (MRS) as reference. Materials and Methods Multiecho T2‐corrected MRS and CSE imaging with eight‐echo gradient‐echo acquisitions at 3T were performed to calculate marrow FF in 83 subjects, including 41 with normal bone mineral density (BMD), 26 with osteopenia, and 16 with osteoporosis (based on DXA). Eight participants were scanned three times with repositioning to assess the repeatability of CSE FF map measurements. Pearson correlation coefficient, Bland–Altman 95% limit of agreement, and Lin's concordance correlation coefficient were calculated. Results The Pearson correlation coefficient was 0.979 and Lin's concordance correlation coefficient was 0.962 between CSE‐based FF and MRS‐based FF. All data points, calculated using the Bland–Altman method, were within the limits of agreement. The intra‐ and interrater agreement for average CSE‐based FF was excellent (intrarater, intraclass correlation coefficient [ICC] = 0.993; interrater, ICC = 0.976–0.982 for different BMD groups). In the subgroups of varying BMD, inverse correlations were observed to be very similar between BMD (r = –0.560 to –0.710), T‐score (r = –0.526 to –0.747), and CSE‐based FF, and between BMD (r = –0.539 to –0.706), T‐score (r = –0.501 to –0.742), and MRS‐based FF even controlling for age, years since menopause, and body mass index. The repeatability for CSE FF map measurements expressed as absolute precision error was 1.45%. Conclusion CSE imaging is equally accurate in characterizing marrow fat content as MRS. Given its excellent correlation and concordance with MRS, the CSE sequence could be used as a potential replacement technique for marrow fat quantification. Level of Evidence: 1 J. Magn. Reson. Imaging 2017;45:66–73.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Comparison of chemical shift-encoded water-fat MRI and MR spectroscopy in quantification of marrow fat in postmenopausal females

Zheng

Gu³

et al. 2016

J. Magn. Reson. Imaging

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“…Therefore, approaches with a single T 2 * correction or with a T 2 ′ correction (where T 2 ′ denotes the reversible spin dephasing relaxation constant) with a priori known water T 2 have been used. A dual T 2 * correction might be not severely affected by noise effects, when the fat quantification is performed not on a voxel‐by‐voxel basis but on a region of interest (ROI) level . After correcting all confounding effects, a good agreement has been reported in vivo between MRS‐based and imaging‐based PDFF in both the proximal femur and spine …”

Section: Technical Aspects Of Quantitative Bone Marrow Mri and Mrsmentioning

confidence: 99%

Quantitative MRI and spectroscopy of bone marrow

Karampinos

Ruschke

Dieckmeyer

et al. 2017

Magnetic Resonance Imaging

200

241

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Bone marrow is one of the largest organs in the human body, enclosing adipocytes, hematopoietic stem cells, which are responsible for blood cell production, and mesenchymal stem cells, which are responsible for the production of adipocytes and bone cells. Magnetic resonance imaging (MRI) is the ideal imaging modality to monitor bone marrow changes in healthy and pathological states, thanks to its inherent rich soft‐tissue contrast. Quantitative bone marrow MRI and magnetic resonance spectroscopy (MRS) techniques have been also developed in order to quantify changes in bone marrow water–fat composition, cellularity and perfusion in different pathologies, and to assist in understanding the role of bone marrow in the pathophysiology of systemic diseases (e.g. osteoporosis). The present review summarizes a large selection of studies published until March 2017 in proton‐based quantitative MRI and MRS of bone marrow. Some basic knowledge about bone marrow anatomy and physiology is first reviewed. The most important technical aspects of quantitative MR methods measuring bone marrow water–fat composition, fatty acid composition, perfusion, and diffusion are then described. Finally, previous MR studies are reviewed on the application of quantitative MR techniques in both healthy aging and diseased bone marrow affected by osteoporosis, fractures, metabolic diseases, multiple myeloma, and bone metastases. Level of Evidence: 3 Technical Efficacy: Stage 2J. Magn. Reson. Imaging 2018;47:332–353.

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“…8 The fat-fraction of muscle tissue is not only relevant for the assessment of neuromuscular diseases, but is also utilized for investigations of other diseases such as lower back pain 9,10 as well as traumatic neck pain. 11,12 Approaches for segmentation so far make use of unsupervised techniques, such as active contours, 13 clustering, 14,15 random walks, 16,17 or atlas approaches. 18,19 It was shown that approaches for segmenting healthy muscle tissue in general do not perform well on pathological tissue.…”

mentioning

confidence: 99%

Domain‐specific data augmentation for segmenting MR images of fatty infiltrated human thighs with neural networks

Gadermayr

Müller

et al. 2019

Magnetic Resonance Imaging

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Background Fat‐fraction has been established as a relevant marker for the assessment and diagnosis of neuromuscular diseases. For computing this metric, segmentation of muscle tissue in MR images is a first crucial step. Purpose To tackle the high degree of variability in combination with the high annotation effort for training supervised segmentation models (such as fully convolutional neural networks). Study Type Prospective. Subjects In all, 41 patients consisting of 20 patients showing fatty infiltration and 21 healthy subjects. Field Strength/Sequence: The T1‐weighted MR‐pulse sequences were acquired on a 1.5T scanner. Assessment To increase performance with limited training data, we propose a domain‐specific technique for simulating fatty infiltrations (i.e., texture augmentation) in nonaffected subjects' MR images in combination with shape augmentation. For simulating the fatty infiltrations, we make use of an architecture comprising several competing networks (generative adversarial networks) that facilitate a realistic artificial conversion between healthy and infiltrated MR images. Finally, we assess the segmentation accuracy (Dice similarity coefficient). Statistical Tests A Wilcoxon signed rank test was performed to assess whether differences in segmentation accuracy are significant. Results The mean Dice similarity coefficients significantly increase from 0.84–0.88 (P < 0.01) using data augmentation if training is performed with mixed data and from 0.59–0.87 (P < 0.001) if training is conducted with healthy subjects only. Data Conclusion Domain‐specific data adaptation is highly suitable for facilitating neural network‐based segmentation of thighs with feasible manual effort for creating training data. The results even suggest an approach completely bypassing manual annotations. Level of Evidence: 4 Technical Efficacy: Stage 3

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Breath‐hold MR measurements of fat fraction, T₁, and T₂* of water and fat in vertebral bone marrow

Abstract: Decaux, et al.. Breathhold MR measurements of fat fraction, T1 , and T2 * of water and fat in vertebral bone marrow.

Cited by 29 publications

References 25 publications

Comparison of chemical shift-encoded water-fat MRI and MR spectroscopy in quantification of marrow fat in postmenopausal females

Comparison of chemical shift-encoded water-fat MRI and MR spectroscopy in quantification of marrow fat in postmenopausal females

Quantitative MRI and spectroscopy of bone marrow

Domain‐specific data augmentation for segmenting MR images of fatty infiltrated human thighs with neural networks

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