Vertebral bone marrow T2* mapping using chemical shift encoding-based water-fat separation in the quantitative analysis of lumbar osteoporosis and osteoporotic fractures.

Background Chemical shift encoding-based water-fat separation techniques have been used for fat quantification [proton density fat fraction (PDFF)], but they also enable the assessment of bone marrow T2*, which has previously been reported to be a potential biomarker for osteoporosis and may give insight into the cause of vertebral fractures (i.e., osteoporotic vs. traumatic) and the microstructure of the bone when applied to vertebral bone marrow. Methods The 32 patients (78.1% with low-energy osteopenic/osteoporotic fractures, mean age 72.3±9.8 years, 76% women; 21.9% with high-energy traumatic fractures, 47.3±12.8 years, no women) were frequency-matched for age and sex to subjects without vertebral fractures (n=20). All study patients underwent 3T-MRI of the lumbar spine including sagittally acquired spoiled gradient echo sequences for chemical shift encoding-based water-fat separation, from which T2* values were obtained. Volumetric trabecular bone mineral density (BMD) and trabecular bone parameters describing the three-dimensional structural integrity of trabecular bone were derived from quantitative CT. Associations between T2* measurements, fracture status and trabecular bone parameters were assessed using multivariable linear regression models. Results Mean T2* values of non fractured vertebrae in all patients showed a significant correlation with BMD (r=-0.65, P<0.001), trabecular number (TbN) (r=-0.56, P<0.001) and trabecular spacing (TbSp) (r=0.61, P<0.001); patients with low-energy osteoporotic vertebral fractures showed significantly higher mean T2* values than those with traumatic fractures (13.6±4.3 vs. 8.4±2.2 ms, P=0.01) as well as a significantly lower TbN (0.69±0.08 vs. 0.93±0.03 mm-1, P<0.01) and a significantly larger trabecular spacing (1.06±0.16 vs. 0.56±0.08 mm, P<0.01). Mean T2* values of osteoporotic patients with and without vertebral fracture showed no significant difference (13.5±3.4 vs. 15.6±3.5 ms, P=0.40). When comparing the mean T2* of the fractured vertebrae, no significant difference could be detected between low-energy osteoporotic fractures and high-energy traumatic fractures (12.6±5.4 vs. 8.1±2.4 ms, P=0.10). Conclusions T2* mapping of vertebral bone marrow using using chemical shift encoding-based water-fat separation allows for assessing osteoporosis as well as the trabecular microstructure and enables a radiation-free differentiation between patients with low-energy osteoporotic and high-energy traumatic vertebral fractures, suggesting its potential as a biomarker for bone fragility.

[1]  M. Makowski,et al.  Improved body quantitative susceptibility mapping by using a variable‐layer single‐min‐cut graph‐cut for field‐mapping , 2020, Magnetic resonance in medicine.

[2]  Chunlei Liu,et al.  Generalized parameter estimation in multi-echo gradient-echo-based chemical species separation. , 2020, Quantitative imaging in medicine and surgery.

[3]  B. Gao,et al.  Correlation of bone mineral density with MRI T2* values in quantitative analysis of lumbar osteoporosis , 2020, Archives of Osteoporosis.

[4]  F. Pfeiffer,et al.  Bone mineral density measurements derived from dual-layer spectral CT enable opportunistic screening for osteoporosis , 2019, European Radiology.

[5]  C. Zimmer,et al.  Improved prediction of incident vertebral fractures using opportunistic QCT compared to DXA , 2019, European Radiology.

[6]  Mingqian Huang,et al.  Prediction of Abnormal Bone Density and Osteoporosis From Lumbar Spine MR Using Modified Dixon Quant in 257 Subjects With Quantitative Computed Tomography as Reference , 2018, Journal of magnetic resonance imaging : JMRI.

[7]  H. Schild,et al.  Quantitative evaluation of T2* relaxation times for the differentiation of acute benign and malignant vertebral body fractures. , 2018, European journal of radiology.

[8]  A. Haase,et al.  Correction of phase errors in quantitative water–fat imaging using a monopolar time‐interleaved multi‐echo gradient echo sequence , 2017, Magnetic resonance in medicine.

[9]  T. Baum,et al.  Quantitative MRI and spectroscopy of bone marrow , 2017, Journal of magnetic resonance imaging : JMRI.

[10]  P. Miller Management of severe osteoporosis , 2016, Expert opinion on pharmacotherapy.

[11]  E. Rummeny,et al.  Modeling of T2* decay in vertebral bone marrow fat quantification , 2015, NMR in biomedicine.

[12]  M. Weiger,et al.  Characterization of trabecular bone density with ultra‐short echo‐time MRI at 1.5, 3.0 and 7.0 T – comparison with micro‐computed tomography , 2014, NMR in biomedicine.

[13]  Nicholas Harvey,et al.  The Osteoporosis Treatment Gap , 2014, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[14]  Tian-wu Chen,et al.  GRE T2∗-Weighted MRI: Principles and Clinical Applications , 2014, BioMed research international.

[15]  Yuan Tian,et al.  Quantitative evaluation of vertebral marrow adipose tissue in postmenopausal female using MRI chemical shift-based water-fat separation. , 2014, Clinical radiology.

[16]  Umberto Sabatini,et al.  Potential diagnostic role of the MRI-derived internal magnetic field gradient in calcaneus cancellous bone for evaluating postmenopausal osteoporosis at 3T. , 2013, Bone.

[17]  C. Cooper,et al.  Osteoporosis in the European Union: medical management, epidemiology and economic burden , 2013, Archives of Osteoporosis.

[18]  R. Laqua,et al.  Proton-density fat fraction and simultaneous R2* estimation as an MRI tool for assessment of osteoporosis , 2013, European Radiology.

[19]  M. Hochberg,et al.  The Epidemiology of Low- and High-Energy Distal Radius Fracture in Middle-Aged and Elderly Men and Women in Southern Norway , 2012, PloS one.

[20]  E. Rummeny,et al.  BMD measurements of the spine derived from sagittal reformations of contrast-enhanced MDCT without dedicated software. , 2011, European journal of radiology.

[21]  S. Majumdar,et al.  T1‐corrected fat quantification using chemical shift‐based water/fat separation: Application to skeletal muscle , 2011, Magnetic resonance in medicine.

[22]  Bejoy Thomas,et al.  Principles, techniques, and applications of T2*-based MR imaging and its special applications. , 2009, Radiographics : a review publication of the Radiological Society of North America, Inc.

[23]  A. Sherry,et al.  Composition of adipose tissue and marrow fat in humans by 1H NMR at 7 Tesla* , 2008, Journal of Lipid Research.

[24]  R. Daffner,et al.  ACR Appropriateness Criteria® on Suspected Spine Trauma , 2007 .

[25]  Sharmila Majumdar,et al.  Analysis of Trabecular Bone Structure with Multidetector Spiral Computed Tomography in a Simulated Soft-Tissue Environment , 2007, Calcified Tissue International.

[26]  A. Wright,et al.  Quantitative MRI for the assessment of bone structure and function , 2006, NMR in biomedicine.

[27]  F. Eckstein,et al.  Structural Analysis of Trabecular Bone of the Proximal Femur Using Multislice Computed Tomography: A Comparison with Dual X-Ray Absorptiometry for Predicting Biomechanical Strength In Vitro , 2006, Calcified Tissue International.

[28]  Ping Chung Leung,et al.  Vertebral bone mineral density, marrow perfusion, and fat content in healthy men and men with osteoporosis: dynamic contrast-enhanced MR imaging and MR spectroscopy. , 2005, Radiology.

[29]  J. L. Melton,et al.  Epidemiology of Spinal Osteoporosis , 1997, Spine.

[30]  C. Christiansen,et al.  Consensus development conference: diagnosis, prophylaxis, and treatment of osteoporosis. , 1993, The American journal of medicine.

[31]  S Majumdar,et al.  Quantitation of the susceptibility difference between trabecular bone and bone marrow: Experimental studies , 1991, Magnetic resonance in medicine.

[32]  F. Wehrli,et al.  Trabecular structure: preliminary application of MR interferometry. , 1991, Radiology.

[33]  S. Peiró,et al.  Vertebral fracture risk factors in postmenopausal women over 50 in Valencia, Spain. A population-based cross-sectional study. , 2013, Bone.