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• Clinical Article •
Quantitative comparative study of Dixon-MRI and BOLD-MRI on early renal injury in adult male with metabolic syndrome
ZHONG Qiaoling  LI Shisi  CHEN Yanjun  DING Youbin  ZHANG Xiaodong 

Cite this article as: Zhong QL, Li SS, Chen YJ, et al. Quantitative comparative study of Dixon-MRI and BOLD-MRI on early renal injury in adult male with metabolic syndrome[J]. Chin J Magn Reson Imaging, 2022, 13(2): 16-21. DOI:10.12015/issn.1674-8034.2022.02.004.


[Abstract] Objective To compare the diagnostic value of Dixon-MRI and blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) in the early renal injury of adult males with metabolic syndrome.Materials and Methods Forty-two adult male volunteers (age 33.88±8.30) were enrolled prospectively. Renal Dixon-MRI and BOLD-MRI examinations were performed in all patients. The height, weight, waist circumference, hip circumference, and blood pressure were recorded. Serological indicators were determined and the glomerular filtration rate (eGFR) was calculated. According to the presence of metabolic syndrome (MetS), patients were divided into MetS group (n=24) and non-MetS group (n=18). The fat fraction (FF) and apparent relaxation rate (R2*) of renal cortex and medulla were measured, and the differences between groups were compared. The correlations between FF, R2*, eGFR, serum creatinine (Scr) and homeostasis model assessment 2-IR (HOMA2-IR) were further analyzed. Then compared the diagnostic efficacy of Dixon-MRI and BOLD-MRI in mild renal injury.Results The fat fraction (FF) values of renal cortex in MetS group were significantly higher than that in non-MetS group, P＜0.001. The R2* values of the renal medulla in the MetS group (27.02±1.38 s-1) were significantly lower than that in the non-MetS group (31.29±1.17 s-1), P=0.008, but there were no statistically significant differences in FF values of renal medulla and R2* values of cortex between the two groups (P＞0.05). After adjusting for age, the FF values of renal cortex and the R2* values of medulla were still statistically significant between two groups (P＜0.001 and 0.035, respectively), while the FF values of renal cortex were negatively correlated with eGFR (r=-0.37, P=0.017), and positively correlated with Scr and HOMA2-IR (r=0.39, P=0.012; r=0.34, P=0.026), while the R2* values of renal medulla were not correlated with eGFR and Scr (r=-0.25, P=0.119; r=0.27, P=0.086). The area under the curve (AUC), sensitivity, and specificity of cortical FF in differentiating normal renal function from mild renal function injury were 82.7%, 85.7%, and 71.4%, respectively. The AUC, sensitivity, and specificity of medullary R2* in differentiating normal renal function from mild renal function injury were 74.2%, 50.0%, and 89.3%, respectively.Conclusions Dixon-MRI and BOLD-MRI can noninvasively and quantitatively detect MetS-related potential or early renal injury, but Dixon-MRI has more potential to evaluate Mets-related potential or early renal injury than BOLD-MRI.
[Keywords] Dixon；blood oxygenation level-dependent magnetic resonance imaging；metabolic syndrome；kidney injury

ZHONG Qiaoling   LI Shisi   CHEN Yanjun   DING Youbin   ZHANG Xiaodong*  

Department of Radiology, the Third Affiliated Hospital of Southern Medical University (Academy of Orthopedics Guangdong Province), Guangzhou 510630, China

Zhang XD, E-mail: ddautumn@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81801653).
Received  2021-08-16
Accepted  2021-12-29
DOI: 10.12015/issn.1674-8034.2022.02.004
Cite this article as: Zhong QL, Li SS, Chen YJ, et al. Quantitative comparative study of Dixon-MRI and BOLD-MRI on early renal injury in adult male with metabolic syndrome[J]. Chin J Magn Reson Imaging, 2022, 13(2): 16-21. DOI:10.12015/issn.1674-8034.2022.02.004.

[1]
Huh JH, Yadav D, Kim JS, et al. An association of metabolic syndrome and chronic kidney disease from a 10-year prospective cohort study[J]. Metabolism, 2017, 67: 54-61. DOI: 10.1016/j.metabol.2016.11.003.
[2]
Rodriguez RR, Gonzalez-Bulnes A, Garcia-Contreras C, et al. The Iberian pig fed with high-fat diet: a model of renal disease in obesity and metabolic syndrome[J]. Int J Obes (Lond), 2020, 44(2): 457-465. DOI: 10.1038/s41366-019-0434-9.
[3]
Li Z, Woollard JR, Wang S, et al. Increased glomerular filtration rate in early metabolic syndrome is associated with renal adiposity and microvascular proliferation[J]. Am J Physiol Renal Physiol, 2011, 301(5): F1078-1087. DOI: 10.1152/ajprenal.00333.2011.
[4]
Donini LM, Merola G, Poggiogalle E, et al. Disability, Physical Inactivity, and Impaired Health-Related Quality of Life Are Not Different in Metabolically Healthy vs. Unhealthy Obese Subjects[J]. Nutrients, 2016, 8(12): 759. DOI: 10.3390/nu8120759.
[5]
Herrmann SM, Saad A, Eirin A, et al. Differences in GFR and Tissue Oxygenation, and Interactions between Stenotic and Contralateral Kidneys in Unilateral Atherosclerotic Renovascular Disease[J]. Clin J Am Soc Nephrol, 2016, 11(3): 458-469. DOI: 10.2215/CJN.03620415.
[6]
Fu S, Yao Y, Luan F, et al. Prevalence of metabolic syndrome risk factors and their relationships with renal function in Chinese centenarians[J]. Sci Rep, 2018, 8(1): 9863. DOI: 10.1038/s41598-018-28316-x.
[7]
Herman-Edelstein M, Scherzer P, Tobar A, et al. Altered renal lipid metabolism and renal lipid accumulation in human diabetic nephropathy[J]. J Lipid Res, 2014, 55(3): 561-572. DOI: 10.1194/jlr.P040501.
[8]
Bobulescu IA. Renal lipid metabolism and lipotoxicity[J]. Curr Opin Nephrol Hypertens, 2010, 19(4): 393-402. DOI: 10.1097/MNH.0b013e32833aa4ac.
[9]
Macisaac RJ, Ekinci EI, Jerums G. Markers of and risk factors for the development and progression of diabetic kidney disease[J]. Am J Kidney Dis, 2014, 63(2Suppl 2): S39-S62. DOI: 10.1053/j.ajkd.2013.10.048.
[10]
Ma XM, He JW, Chang FX, et al. Research progress of functional magnetic resonance imaging in chronic kidney disease[J]. Chin J Magn Reson Imaging, 2020, 11(10): 950-953. DOI: 10.12015/issn.1674-8034.2020.10.030.
[11]
Wang ZY, Li SH, Yu SS, et al. Progress of blood oxygen level dependent MRI in diabetic kidney disease[J]. Chin J Magn Reson Imaging, 2020, 11(5): 382-385. DOI: 10.12015/issn.1674-8034.2020.05.015.
[12]
Zhang X, Lerman LO. The metabolic syndrome and chronic kidney disease[J]. Transl Res, 2017, 183: 14-25. DOI: 10.1016/j.trsl.2016.12.004.
[13]
Zhang X, Li ZL, Woollard JR, et al. Obesity-metabolic derangement preserves hemodynamics but promotes intrarenal adiposity and macrophage infiltration in swine renovascular disease[J]. Am J Physiol Renal Physiol, 2013, 305(3): F265-276. DOI: 10.1152/ajprenal.00043.2013.
[14]
Eirin A, Woollard JR, Ferguson CM, et al. The metabolic syndrome induces early changes in the swine renal medullary mitochondria[J]. Transl Res, 2017, 184: 45-56. DOI: 10.1016/j.trsl.2017.03.002.
[15]
Neugarten J. Renal BOLD-MRI and assessment for renal hypoxia[J]. Kidney Int, 2012, 81(7): 613-614. DOI: 10.1038/ki.2011.462.
[16]
Pruijm M, Milani B, Burnier M. Blood Oxygenation Level-Dependent MRI to Assess Renal Oxygenation in Renal Diseases: Progresses and Challenges[J]. Front Physiol, 2016, 7: 667. DOI: 10.3389/fphys.2016.00667.
[17]
Khatir DS, Pedersen M, Jespersen B, et al. Evaluation of Renal Blood Flow and Oxygenation in CKD Using Magnetic Resonance Imaging [J]. Am J Kidney Dis, 2015, 66(3): 402-411. DOI: 10.1053/j.ajkd.2014.11.022.
[18]
Li LP, Thacker JM, Li W, et al. Medullary Blood Oxygen Level-Dependent MRI Index (R2*) is Associated with Annual Loss of Kidney Function in Moderate CKD[J]. Am J Nephrol, 2020, 51(12): 966-974. DOI: 10.1159/000512854.
[19]
Selby NM, Blankestijn PJ, Boor P, et al. Magnetic resonance imaging biomarkers for chronic kidney disease: a position paper from the European Cooperation in Science and Technology Action PARENCHIMA[J]. Nephrol Dial Transplant, 2018, 33(suppl_2): ii4-ii14. DOI: 10.1093/ndt/gfy152.
[20]
Gansevoort RT, Matsushita K, van der Velde M, et al. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts[J]. Kidney Int, 2011, 80(1): 93-104. DOI: 10.1038/ki.2010.531.
[21]
Hirakawa Y, Tanaka T, Nangaku M. Renal Hypoxia in CKD; Pathophysiology and Detecting Methods [J]. Frontiers in Physiology, 2017, 8: 99. DOI: 10.3389/fphys.2017.00099.

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