Share:
Share this content in WeChat
X
Technical Article
3D mDixon Quant based on compressed SENSE for quantitative study of lumbar vertebral body fat content
SONG Yu  SONG Qingwei  ZHANG Haonan  ZHANG Nan  PU Renwang  LIU Ailian  MIAO Yanwei 

Cite this article as: Song Y, Song QW, Zhang HN, et al. 3D mDixon Quant based on compressed SENSE for quantitative study of lumbar vertebral body fat content[J]. Chin J Magn Reson Imaging, 2021, 12(4): 51-56. DOI:10.12015/issn.1674-8034.2021.04.010.


[Abstract] Objective To investigate the effects of different acceleration factors (AF) on lumbar vertebra fat quantification using 3D mDixon Quant sequence accelerated by sensitivity coding (SENSE) and compressed SENSE (CS-SENSE), and analyze the relationship among lumbar body fat fraction (FF), age, sex and body mass index (BMI). Materials andMethods From January to July 2020, 96 healthy volunteers were recruited, including 45 males and 51 females, from 16 to 79 years old, with an average age of 43.85±17.98 years. Volunteers were divided into three groups according to age: young group (<40 years old), middle-aged group (40—60 years old), and elderly group (>60 years old). All volunteers were imaged at Philips Ingenia CX 3.0 T MRI with a fat quantification sequence (3D mDixon Quant) for the entire lumbar spine, and the sequence was accelerated at different folds with either SENSE (acceleration factor S=2, 4) or CS-SENSE (acceleration factor CS=2, 3, 4, 5, 6, 7, 8). FF, signal-noise-ratio (SNR), and contrast-noise-ration (CNR) were measured for the L1—L5 vertebra by two radiologists independently with a double-blind method, measurement carried out on a IntelliSpace Portal workstation (ISP version 7.0; Philips Healthcare, Best, the Netherlands). The measured parameters were compared among different AFs.Results The measurement results of the two observers showed good agreement (ICC value>0.75). There was no statistically significant difference in the FF values measured by 3D mDixon Quant sequence with different AF (P=0.653), but there were statistically significant differences in SNR and CNR with different AF (P=0.001, 0.006). Among them, there were statistically significant differences in SNR and CNR between CS3 and CS7 groups, CS4 and CS7 groups, and CS4 and CS8 groups (P<0.05). The scanning time of CS6 was 60.66% shorter than that of SENSE 2, but there were no statistically significant differences in FF values, SNR and CNR values compared with those of other groups (S2, S4, CS2, CS3, CS4 and CS5) (P>0.05). FF values were significantly different between the three age groups (F=20.876, P<0.01). Among them, FF of the young group was significantly lower (P<0.01) than that of the middle-aged and the elderly groups, while the difference between the middle-aged and the elderly groups was not statistically significant (P=0.086). In the young group, the lumbar vertebra FF of the male was higher than that of the female (P<0.05), while in the middle-aged group and the elderly group, the FF of the male was slightly lower than that of the female, albeit not significantly (P>0.05). The lumbar vertebrae FF in men was moderately positively correlated with BMI (r=0.634, P<0.01), while in females such correlation was not observed (r=0.207, P=0.146).Conclusions The 3D mDixon Quant sequence combined with CS technology is reliable for assessing the lumbar vertebral body fat content. When the maximum AF of CS was selected to 6, the image quality and the measurement accuracy were maintained while the imaging time dramatically reduced. Age, gender, and BMI are all factors that may affect the lumbar vertebra fat content. These factors should be considered in the analysis and evaluation of lumbar vertebra fat content in different individuals.
[Keywords] magnetic resonance imaging;lumbar spine;fat content;3D mDixon Quant;compressed SENSE;acceleration factors

SONG Yu1, 2   SONG Qingwei2*   ZHANG Haonan2   ZHANG Nan2   PU Renwang2   LIU Ailian2   MIAO Yanwei2  

1 Department of Radiology, West China Second University, Sichuan University, Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defect of Ministry of Education, Chengdu 610041, China

2 Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China

Song QW, E-mail: songqw1964@163.com

Conflicts of interest   None.

This work was part of National Natural Science Foundation of China (No. 81901712).
Received  2020-12-17
Accepted  2021-02-10
DOI: 10.12015/issn.1674-8034.2021.04.010
Cite this article as: Song Y, Song QW, Zhang HN, et al. 3D mDixon Quant based on compressed SENSE for quantitative study of lumbar vertebral body fat content[J]. Chin J Magn Reson Imaging, 2021, 12(4): 51-56. DOI:10.12015/issn.1674-8034.2021.04.010.

1
Tarantino U, Iolascon G, Cianferotti L, et al. Clinical guidelines for the prevention and treatment of osteoporosis: summary statements and recommendations from the Italian Society for Orthopaedics and Traumatology[J]. J Orthop Traumatol, 2017, 18(Suppl 1): 33-36. DOI: 10.1007/s10195-017-0474-7.
2
Kaufman JJ, Luo G, Siffert RS. Ultrasound simulation in bone[J]. IEEE Trans Ultrason Ferroelectr Freq Control, 2008, 55(6): 1205-1218. DOI: 10.1109/TUFFC.2008.784.
3
Al-Saleh Y, Sulimani R, Sabico S, et al. 2015 guidelines for osteoporosis in saudi arabia: Recommendations from the saudi osteoporosis society[J]. Ann Saudi Med, 2015, 35(1): 1-12. DOI: 10.5144/0256-4947.2015.1.
4
Baum T, Lorenz C, Buerger C, et al. Automated assessment of paraspinal muscle fat composition based on the segmentation of chemical shift encoding-based water/fat-separated images[J]. Eur Radiol Exp, 2018, 2(1): 32. DOI: 10.1186/s41747-018-0065-2.
5
Patro SN, Chakraborty S, Sheikh A. The use of adaptive statistical iterative reconstruction (ASiR) technique in evaluation of patients with cervical spine trauma: impact on radiation dose reduction and image quality[J]. Br J Radiol, 2016, 89(1060): 20150082. DOI: 10.1259/bjr.20150082.
6
Aja-Fernández S, Vegas-Sánchez-Ferrero G, Tristán-Vega A. Noise estimation in parallel MRI: GRAPPA and SENSE[J]. Magn Reson Imaging, 2014, 32(3): 281-290. DOI: 10.1016/j.mri.2013.12.001.
7
Geethanath S, Reddy R, Konar AS, et al. Compressed sensing MRI: a review[J]. Crit Rev Biomed Eng, 2013, 41(3): 183-204. DOI: 10.1615/critrevbiomedeng.2014008058.
8
Chun IY, Adcock B, Talavage TM. Efficient compressed sensing SENSE pMRI reconstruction with joint sparsity promotion[J]. IEEE Trans Med Imaging, 2016, 35(1): 354-368. DOI: 10.1109/TMI.2015.2474383.
9
Sartoretti E, Sartoretti T, Binkert C, et al. Reduction of procedure times in routine clinical practice with compressed SENSE magnetic resonance imaging technique[J]. PLoS One, 2019, 14(4): e0214887. DOI: 10.1371/journal.pone.0214887.
10
Vranic JE, Cross NM, Wang Y, et al. Compressed sensing-sensitivity encoding (CS-SENSE) accelerated brain imaging: Reduced scan time without reduced image quality[J]. AJNR Am J Neuroradiol, 2019, 40(1): 92-98. DOI: 10.3174/ajnr.A5905.
11
Wang Z, Zhuang J, Gao Z, et al. A fast scanning ion conductance microscopy imaging method using compressive sensing and low-discrepancy sequences[J]. Rev Sci Instrum, 2018, 89(11): 113709. DOI: 10.1063/1.5048656.
12
Aguilar JA, Kenwright AM. Compressed NMR: Combining compressive sampling and pure shift NMR techniques[J]. Magn Reson Chem, 2018, 56(10): 983-992. DOI: 10.1002/mrc.4705.
13
Kido T, Kido T, Nakamura M, et al. Compressed sensing real-time cine cardiovascular magnetic resonance: accurate assessment of left ventricular function in a single-breath-hold[J]. J Cardiovasc Magn Reson, 2016, 18(1): 50. DOI: 10.1186/s12968-016-0271-0.
14
He M, Xu J, Sun Z, et al. Comparison and evaluation of the efficacy of compressed SENSE (CS) and gradient- and spin-echo (GRASE) in breath- hold (BH) magnetic resonance cholangiopancreatography (MRCP)[J]. J Magn Reson Imaging, 2020, 51(3): 824-832. DOI: 10.1002/jmri.26863.
15
Toledano-Massiah S, Sayadi A, de Boer R, et al. Accuracy of the compressed sensing accelerated 3D-FLAIR sequence for the detection of MS plaques at 3 T[J]. AJNR Am J Neuroradiol, 2018, 39(3): 454-458. DOI: 10.3174/ajnr.A5517.
16
Gulati GL, Ashton JK, Hyun BH. Structure and function of the bone marrow and hematopoiesis[J]. Hematol Oncol Clin North Am, 1988, 2(4): 495-511.
17
Chu C, Feng Q, Zhang H, et al. Evaluation of salivary gland fat fraction values in patients with primary Sjögren's syndrome by mDIXON quant imaging: Initial findings[J]. Eur J Radiol, 2020, 123: 108776. DOI: 10.1016/j.ejrad.2019.108776.
18
Guo RM, Zhao RZ, Zhang J, et al. Quantification of fat deposition in the testis and epididymis using mDIXON Quant sequence: correlation with age and ejaculation[J]. Abdom Radiol (NY), 2019, 44(4): 1528-1534. DOI: 10.1007/s00261-018-1826-3.
19
Kise Y, Chikui T, Yamashita Y, et al. Clinical usefulness of the mDIXON Quant the method for estimation of the salivary gland fat fraction: comparison with MR spectroscopy[J]. Br J Radiol, 2017, 90(1077): 20160704. DOI: 10.1259/bjr.20160704.
20
Zhang Y, Zhou Z, Wang C, et al. Reliability of measuring the fat content of the lumbar vertebral marrow and paraspinal muscles using MRI mDIXON-Quant sequence[J]. Diagn Interv Radiol, 2018, 24(5): 302-307. DOI: 10.5152/dir.2018.17323.
21
Zhao Y, Huang M, Ding J, et al. Prediction of abnormal bone density and osteoporosis from lumbar spine MR using modified dixon quant in 257 subjects with quantitative computed yomography as reference[J]. J Magn Reson Imaging, 2019, 49(2): 390-399. DOI: 10.1002/jmri.26233.
22
Liney GP, Bernard CP, Manton DJ, et al. Age, gender, and skeletal variation in bone marrow composition: a preliminary study at 3.0 Tesla[J]. J Magn Reson Imaging, 2007, 26(3): 787-793. DOI: 10.1002/jmri.21072.
23
Roldan-Valadez E, Piña-Jimenez C, Favila R, et al. Gender and age groups interactions in the quantification of bone marrow fat content in lumbar spine using 3T MR spectroscopy: a multivariate analysis of covariance (Mancova)[J]. Eur J Radiol, 2013, 82(11): e697-e702. DOI: 10.1016/j.ejrad.2013.07.012.
24
Imai Y, Youn MY, Kondoh S, et al. Estrogens maintain bone mass by regulating expression of genes controlling function and life span in mature osteoclasts[J]. Ann N Y Acad Sci, 2009, 1173(Suppl 1): E31-E39. DOI: 10.1111/j.1749-6632.2009.04954.x.
25
Bermeo S, Gunaratnam K, Duque G. Fat and bone interactions[J]. Curr Osteoporos Rep, 2014, 12(2): 235-242. DOI: 10.1007/s11914-014-0199-y.
26
Zhang XT, Chen QM, Chen JL, et al. Correlation of lumbar bone marrow fat content with gender, age, body mass index, waistline and visceral adipose tissue by using mDIXON-quant[J]. J Clin Radiol, 2019, 38(7): 1292-1296. DOI: 10.13437/j.cnki.jcr.2019.07.019.
27
Bao XX, Wang N, Li YK. Advances in the relationship between obesity and osteoporosis[J]. Chin J Clinicians(Electronic Edition), 2015, 9(14): 2749-2753. DOI: 10.3877/cma.j.issn.1674-0785.2015.14.030.
28
Cordes C, Dieckmeyer M, Ott B, et al. MR-detected changes in liver fat, abdominal fat, and vertebral bone marrow fat after a four-week calorie restriction in obese women[J]. J Magn Reson Imaging, 2015, 42(5): 1272-1280. DOI: 10.1002/jmri.24908.
29
Arner P, Spalding KL. Fat cell turnover in humans[J]. Biochem Biophys Res Commun, 2010, 396(1): 101-104. DOI: 10.1016/j.bbrc.2010.02.165.
30
Cordes C, Dieckmeyer M, Ott B, et al. MR-detected changes in liver fat, abdominal fat, and vertebral bone marrow fat after a four-week calorie restriction in obese women[J]. J Magn Reson Imaging, 2015, 42(5): 1272-1280. DOI: 10.1002/jmri.24908.
31
Kong X, Xing X, Zhang X, et al. Sexual dimorphism of a genetic risk score for obesity and related traits among Chinese patients with type 2 diabetes[J]. Obes Facts, 2019, 12(3): 328-343. DOI: 10.1159/000500490.
32
Numao S, Katayama Y, Nakata Y, et al. Association of abdominal fat with metabolic syndrome components in overweight women: effect of menopausal status[J]. J Physiol Anthropol, 2020, 39(1): 12. DOI: 10.1186/s40101-020-00222-0.

PREV Functional connectivity between prefrontal lobe and thalamus and its relationship with individual,s craving for internet game: A rs-fMRI study
NEXT A meta-analysis of diagnostic efficacy of four-dimensional magnetic resonance angiography in arteriovenous malformations
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn