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Research progress of magnetic resonance water-fat separation technology in the degree of kidney damage in chronic kidney disease
LÜ Yanan  GU Congcong  REN Rui  JIANG Xingyue 

DOI:10.12015/issn.1674-8034.2026.02.027.


[Abstract] Chronic kidney disease (CKD) is a complex syndrome with a high incidence rate (the global prevalence has reached as high as 14.3%), characterized by irreversible changes in kidney function and structure. It has now become a global public health issue. Therefore, early diagnosis and dynamic monitoring of CKD have become the key to improving prognosis. Currently, renal pathological biopsy is the gold standard for diagnosing CKD, but due to its invasiveness, it cannot be used as a routine examination method. In recent years, magnetic resonance water-fat separation technology (such as multi-echo Dixon technique) provides a new perspective for evaluating the degree of kidney damage in CKD by non-invasively quantifying renal fat deposition and oxygen metabolism status. This article reviews the physical basis and evolution of the technology, systematically summarizes its application progress in quantitatively assessing key pathological features such as renal fat infiltration, iron deposition, and local hypoxia in CKD patients, and explores its correlation with clinical indicators and potential in disease staging and differential diagnosis. At the same time, this article focuses on analyzing the current challenges and cutting-edge directions in research. The aim of this article is to provide a systematic reference for a comprehensive understanding of the clinical value and limitations of the technology and to promote its transformation from research to a precise diagnostic and therapeutic tool.
[Keywords] chronic kidney disease；perirenal fat；magnetic resonance imaging；multi-echo Dixon technique；fat fraction；R2* value

LÜ Yanan   GU Congcong   REN Rui   JIANG Xingyue*  

Department of Radiology, Affiliated Hospital of Binzhou Medical College, Binzhou 256603, China

Corresponding author: JIANG X Y, E-mail: xyjiang188@sina.com

Conflicts of interest   None.

Received  2025-10-16
Accepted  2026-02-03
DOI: 10.12015/issn.1674-8034.2026.02.027
DOI:10.12015/issn.1674-8034.2026.02.027.

[1]
STEVENS P E, AHMED S B, CARRERO J J, et al. KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease[J]. Kidney Int, 2024, 105(4): S117-S314. DOI: 10.1016/j.kint.2023.10.018.
[2]
KALANTAR-ZADEH K, JAFAR T H, NITSCH D, et al. Chronic kidney disease[J]. Lancet, 2021, 398(10302): 786-802. DOI: 10.1016/S0140-6736(21)00519-5.
[3]
Chinese Society of Nephrology Prevention and Control of Chinese Preventive Medicine Association. Guidelines for the early evaluation and management of chronic kidney disease in China[J]. Chin J Intern Med, 2023, 62(8): 902-930. DOI: 10.3760/cma.j.cn112138-20221013-00755.
[4]
NAWAZ S, CHINNADURAI R, AL-CHALABI S, et al. Obesity and chronic kidney disease: a current review[J]. Obes Sci Pract, 2023, 9(2): 61-74. DOI: 10.1002/osp4.629.
[5]
CASTRO B B A, FORESTO-NETO O, SARAIVA-CAMARA N O, et al. Renal lipotoxicity: Insights from experimental models[J]. Clin Exp Pharmacol Physiol, 2021, 48(12): 1579-1588. DOI: 10.1111/1440-1681.13556.
[6]
PAN X Y. Cholesterol metabolism in chronic kidney disease: physiology, pathologic mechanisms, and treatment[M]//Sphingolipid Metabolism and Metabolic Disease. Singapore: Springer, 2022: 119-143.
[7]
CHEN X J, MAO Y, HU J B, et al. Perirenal fat thickness is significantly associated with the risk for development of chronic kidney disease in patients with diabetes[J]. Diabetes, 2021, 70(10): 2322-2332. DOI: 10.2337/db20-1031.
[8]
NAKAGAWA T, SANCHEZ-LOZADA L G, ANDRES-HERNANDO A, et al. Endogenous fructose metabolism could explain the Warburg effect and the protection of SGLT2 inhibitors in chronic kidney disease[J/OL]. Front Immunol, 2021, 12: 694457 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/34220855/. DOI: 10.3389/fimmu.2021.694457.
[9]
DONG J Q. Correlation study between hepcidin and diabetic kidney disease[D]. Shenzhen: Shenzhen University, 2023. DOI: 10.27321/d.cnki.gszdu.2023.002920.
[10]
LEI L, FAN Y, LI Y L, et al. Iron death and its research progress in renal fibrosis[J]. J Med Res, 2024, 53(7): 173-176. DOI: 10.11969/j.issn.1673-548X.2024.07.034.
[11]
XU W C, ZHU Y T, WANG S Y, et al. From adipose to ailing kidneys: the role of lipid metabolism in obesity-related chronic kidney disease[J/OL]. Antioxidants (Basel), 2024, 13(12): 1540 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/39765868/. DOI: 10.3390/antiox13121540.
[12]
LAR SENG N S HTI, LOHANA P, CHANDRA S, et al. The fatty kidney and beyond: a silent epidemic[J]. Am J Med, 2023, 136(10): 965-974. DOI: 10.1016/j.amjmed.2023.06.025.
[13]
WANG L M, XU X, ZHANG M, et al. Prevalence of chronic kidney disease in China: results from the sixth China chronic disease and risk factor surveillance[J]. JAMA Intern Med, 2023, 183(4): 298-310. DOI: 10.1001/jamainternmed.2022.6817.
[14]
QIN L H, CHEN J, XIANG Y D, et al. An analysis of disease burden and risk factors of chronic kidney disease in China from 1990 to 2021[J]. New Med, 2024, 34(9): 957-969. DOI: 10.12173/j.issn.1004-5511.202408076.
[15]
LI X M, LIU Q Q, LIU Y Q. Risk factors and delay strategies for progression of chronic kidney disease[J]. Int Med Health Guid News, 2024, 30(11): 1766-1770. DOI: 10.3760/cma.j.issn.1007-1245.2024.11.002.
[16]
WANG N, JIANG X R, QIU J H, et al. Study on establishing information management for chronic kidney disease patients to delay disease progression[J]. Clin Res, 2025, 33(3): 85-88. DOI: 10.12385/j.issn.2096-1278(2025)03-0085-04.
[17]
Shanghai Municipal Clinical Quality Control Center for Nephrology Expert Group. Guidelines for early screening, diagnosis, prevention and treatment of chronic kidney disease (2022 Edition)[J]. Chin J Nephrol, 2022, 38(5): 453-464. DOI: 10.3760/cma.j.cn441217-20210819-00067.
[18]
黄浩成. Risk factors of severe bleeding after percutaneous renal biopsy in patients with advanced chronic kidney disease[J]. China Medical Abstracts (Internal Medicine), 2025, 42(1): 46-47.
[19]
MCROBBIE D W, MOORE E A, GRAVES M J, et al. MRI from Picture to Proton[M]. 3rd Ed. Cambridge, UK: Cambridge University Press, 2017. DOI: 10.1017/9781107706958.
[20]
ZHANG Y K, LI L, LI J F. "Principles and Techniques Interpretation of Practical Magnetic Resonance Imaging"[M]. Beijing: Peking University Medical Press, 2021: P221-P225.
[21]
DIXON W T. Simple proton spectroscopic imaging[J]. Radiology, 1984, 153(1): 189-194. DOI: 10.1148/radiology.153.1.6089263.
[22]
LIU N, ZHANG H N, ZHANG Y K, et al. A comparation analysis between IDEAL-IQ and mDixon Quant techniques in fat quantification of abdomen and vertebrae[J]. Chin J Magn Reson Imaging, 2022, 13(3): 49-53. DOI: 10.12015/issn.1674-8034.2022.03.010.
[23]
XIONG X Q, LIN Q T, SITU D K, et al. Application of new magnetic resonance water-fat separation technology IDEAL-IQ[J]. J Jinan Univ Nat Sci Med Ed, 2020, 41(5): 427-433. DOI: 10.11778/j.jdxb.2020.05.007.
[24]
QUAN J W, GUO D Q, E L N, et al. Research advancements of functional MRI for assessment of early kidney injury in type 2 diabetes mellitus[J]. Chin J Interv Imaging Ther, 2023, 20(5): 312-315. DOI: 10.13929/j.issn.1672-8475.2023.05.014.
[25]
LI L X, LONG Y J, PENG X, et al. Clinical application progress of functional magnetic resonance imaging in evaluating renal function of chronic kidney disease[J]. J Clin Radiol, 2025, 44(4): 759-763. DOI: 10.13437/j.cnki.jcr.2025.04.013.
[26]
ZHOU J Y. Application value of functional magnetic resonance imaging in chronic kidney disease[D]. Nanchong: North Sichuan Medical College, 2021. DOI: 10.27755/d.cnki.gcbyx.2021.000262.
[27]
CHEN L, HU H, CHEN H H, et al. Usefulness of two-point Dixon T2-weighted imaging in thyroid-associated ophthalmopathy: comparison with conventional fat saturation imaging in fat suppression quality and staging performance[J/OL]. Br J Radiol, 2021, 94(1118): 20200884 [2025-10-15]. https://www.birpublications.org/doi/10.1259/bjr.20200884. DOI: 10.1259/bjr.20200884.
[28]
WENDL C M, EIGLSPERGER J, DENDL L M, et al. Fat suppression in magnetic resonance imaging of the head and neck region: is the two-point DIXON technique superior to spectral fat suppression [J/OL]. Br J Radiol, 2018, 91(1085): 20170078 [2025-10-15]. https://www.birpublications.org/doi/10.1259/bjr.20170078. DOI: 10.1259/bjr.20170078.
[29]
YANG H, ZOU L G. Clinical practical MRI palm treasure[M]. 2nd ed. Guangzhou: Guangdong Science & Technology Press, 2018.
[30]
YU H Z, SHIMAKAWA A, MCKENZIE C A, et al. Multiecho water-fat separation and simultaneous R estimation with multifrequency fat spectrum modeling[J]. Magn Reson Med, 2008, 60(5): 1122-1134. DOI: 10.1002/mrm.21737.
[31]
YOO Y H, KIM H S, LEE Y H, et al. Comparison of multi-echo Dixon methods with volume interpolated breath-hold gradient echo magnetic resonance imaging in fat-signal fraction quantification of paravertebral muscle[J]. Korean J Radiol, 2015, 16(5): 1086-1095. DOI: 10.3348/kjr.2015.16.5.1086.
[32]
KIM D, KIM S K, LEE S J, et al. Simultaneous estimation of the fat fraction and r₂* via t₂*-corrected 6-echo Dixon volumetric interpolated breath-hold examination imaging for osteopenia and osteoporosis detection: correlations with sex, age, and menopause[J]. Korean J Radiol, 2019, 20(6): 916-930. DOI: 10.3348/kjr.2018.0032.
[33]
YING J, LIU D, YANG Q, et al. 3.0 T MRI double-echo hydro-lipid separation Dixon technique for quantitative determination of liver fat in patients with nonalcoholic fatty liver disease[J]. Chin J Magn Reson Imaging, 2020, 11(7): 577-580. DOI: 10.12015/issn.1674-8034.2020.07.020.
[34]
YAO R H, GAO B L, HU J H, et al. Characteristics of mDIXON-Quant and proton magnetic resonance spectroscopy imaging of thigh skeletal muscles in patients with stroke-related sarcopenia: a prospective case-control study[J/OL]. J Yeungnam Med Sci, 2025, 42: 49 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/40874399/. DOI: 10.12701/jyms.2025.42.49.
[35]
LI X H. The impact of ACBP on ectopic lipid deposition and lipophagy in diabetic nephropathy[D]. Changsha: Central South University, 2023. DOI: 10.27661/d.cnki.gzhnu.2023.000633.
[36]
CHENG J M, LUO W X, PAN J, et al. Renal ectopic lipid deposition in rats with early-stage diabetic nephropathy evaluated by the MR mDixon-Quant technique: association with the expression of SREBP-1 and PPARα in renal tissue[J]. Quant Imaging Med Surg, 2023, 13(7): 4504-4513. DOI: 10.21037/qims-22-1167.
[37]
ZHU C L. Experimental study of quantitative susceptibility mapping and water-fat separation technology in the detection of brown adipose tissue in rat[D]. Guangzhou: Southern Medical University, 2021. DOI: 10.27003/d.cnki.gojyu.2021.000774.
[38]
LIU J, YANG D Y, TIAN C, et al. Magnetic resonance imaging for noninvasive assessment of renal fat deposition and hypoxia in diabetic kidney disease[J/OL]. BMC Med Imaging, 2025, 25(1): 272 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/40619382/. DOI: 10.1186/s12880-025-01816-9.
[39]
YANG C, WANG Z, ZHANG J L, et al. Mri assessment of renal lipid deposition and abnormal oxygen metabolism of type 2 diabetes mellitus based on mDixon-Quant[J]. Magnetic Resonance Imaging, 2023, 58(5): 1408-1417. DOI: 10.1002/jmri.28701.
[40]
XIE L H. A correlation study of renal fat quantification and kidney damage based on magnetic resonance[D]. Chongqing: Chongqing Medical University, 2023. DOI: 10.27674/d.cnki.gcyku.2023.001678.
[41]
WANG Y, JU Y, AN Q, et al. mDIXON-Quant for differentiation of renal damage degree in patients with chronic kidney disease[J/OL]. Front Endocrinol, 2023, 14: 1187042 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/37547308/. DOI: 10.3389/fendo.2023.1187042.
[42]
WANG Y, JU Y, HU W J, et al. T1 mapping combined with R2* maps for diagnosing chronic kidney disease[J]. Chin J Med Imag Technol, 2023, 39(5): 727-731. DOI: 10.13929/j.issn.1003-3289.2023.05.020.
[43]
WANG G G, MENG L P, HU M X, et al. Prediction of renal function development in patients with chronic kidney disease by BOLD and mDIXON-Quant sequences[J]. J Med Imaging, 2024, 34(8): 86-89. DOI: 10.20258/j.cnki.1006-9011.2024.08.021.
[44]
BAI L T, LU Y J, ZHANG X L, et al. Quantitative assessment of iron overload in patients with chronic kidney disease using MRI technique[J]. Chin Comput Med Imag, 2023, 29(2): 167-172. DOI: 10.19627/j.cnki.cn31-1700/th.2023.02.008.
[45]
WU Z J, CAI A P, XU L, et al. Clinical characteristics of hospitalized patients with ischemic cardiomyopathy complicated with chronic kidney disease[J]. South China J Cardiovasc Dis, 2021, 27(4): 478-485. DOI: 10.3969/j.issn.1007-9688.2021.04.19.
[46]
WANG Y, LIU A L, JU Y, et al. Study on the correlation between APT and mDixon-Quant in the right renal cortex and medulla of patients with chronic kidney disease[J]. Chin J Magn Reson Imag, 2022, 13(3): 71-75. DOI: 10.12015/issn.1674-8034.2022.03.014.
[47]
JU Y, WANG Y, LUO R N, et al. Evaluation of renal function in chronic kidney disease (CKD) by mDIXON-Quant and Amide Proton Transfer weighted (APTw) imaging[J]. Magn Reson Imaging, 2023, 103: 102-108. DOI: 10.1016/j.mri.2023.07.005.
[48]
SUO LANG N, MAO W, ZENG M S, et al. The value of T1-mapping to evaluate renal function injury in chronic kidney disease[J]. Radiol Pract, 2023, 38(8): 1039-1043. DOI: 10.13609/j.cnki.1000-0313.2023.08.014.
[49]
HUA C C, QIU L, ZHOU L T, et al. Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis[J]. Eur Radiol, 2023, 33(8): 5211-5221. DOI: 10.1007/s00330-023-09674-1.
[50]
ZHONG Q L, LI S S, CHEN Y J, 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 Imag, 2022, 13(2): 16-21. DOI: 10.12015/issn.1674-8034.2022.02.004.
[51]
SUN H Z, SONG X Y, LU S. Effect of BOLD-fMRI on early renal function in patients with type 2 diabetes mellitu[J]. Chin J Magn Reson Imaging, 2023, 14(7): 61-66. DOI: 10.12015/issn.1674-8034.2023.07.011.
[52]
ZHANG X Y, YE C Y, LU F, et al. Evaluation of renal oxygenation and perfusion in patients with chronic kidney disease: a preliminary prospective study based on functional magnetic resonance[J/OL]. Ren Fail, 2024, 46(2): 2428337 [2025-10-15]. https://pubmed.ncbi.nlm.nih.gov/39584486/. DOI: 10.1080/0886022X.2024.2428337.
[53]
MAO W, DING Y Q, DING X Q, et al. Capability of arterial spin labeling and intravoxel incoherent motion diffusion-weighted imaging to detect early kidney injury in chronic kidney disease[J]. Eur Radiol, 2023, 33(5): 3286-3294. DOI: 10.1007/s00330-022-09331-z.
[54]
PI S, LI Y, LIN C R, et al. Arterial spin labeling and diffusion-weighted MR imaging: quantitative assessment of renal pathological injury in chronic kidney disease[J]. Abdom Radiol, 2023, 48(3): 999-1010. DOI: 10.1007/s00261-022-03770-4.

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