Abstract
Purpose
The purpose of this study was to evaluate different renal proton density fat fraction (PDFF) analysis approaches. Additionally, we assessed renal fat in obese individuals and lean individuals.
Methods
This was a retrospective observational case–control study. Twenty-eight obese individuals and 14 lean controls underwent MRI with multi-point Dixon technique for PDFF maps. The following renal PDFF image analysis approaches were performed and compared: (1) five circular regions of interest (ROIs) in six slices, (2) three circular ROIs in one slice, (3) freehand segmentation of renal parenchyma in one slice, and (4) freehand segmentation of renal parenchyma avoiding the renal border in one slice. Furthermore, renal PDFF was compared between obese and lean individuals.
Results
Methods 1, 2, and 4 were positively correlated (r ≥ 0.498, p ≤ 0.001). Renal PDFF values varied more with regards to ROI placement within slices than mean PDFF between slices. Using all methods, the obese individuals had significantly higher renal PDFF values compared with the lean controls.
Conclusion
Renal PDFF should be measured covering large areas of the kidney while excluding artifacts. This can be achieved using multiple circular ROIs. Increased lipid accumulation in the kidneys was related to obesity.
Graphical abstract
Similar content being viewed by others
References
Zou Y, Sheng G, Yu M, Xie G. The association between triglycerides and ectopic fat obesity: An inverted U-shaped curve. PLoS One. 2020;15:e0243068.
Wahba IM, Mak RH. Obesity and Obesity-Initiated Metabolic Syndrome: Mechanistic Links to Chronic Kidney Disease. Clin J Am Soc Nephrol. 2007;2:550–62.
Britton KA, Fox CS. Ectopic Fat Depots and Cardiovascular Disease. Circulation. 2011;124.
Lim S, Meigs JB. Links between ectopic fat and vascular disease in humans. Arterioscler Thromb Vasc Biol. 2014;34:1820–6.
Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6–10.
Elhady M, Elazab AAAM, Bahagat KA, Abdallah NA, Ibrahim GE-S. Fatty pancreas in relation to insulin resistance and metabolic syndrome in children with obesity. J Pediatr Endocrinol Metab. 2019;32:19–26.
Younossi Z, Tacke F, Arrese M, Chander Sharma B, Mostafa I, Bugianesi E, et al. Global Perspectives on Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis. Hepatology. 2019;69:2672–82.
Jonker JT, de Heer P, Engelse MA, van Rossenberg EH, Klessens CQF, Baelde HJ, et al. Metabolic imaging of fatty kidney in diabesity: validation and dietary intervention. Nephrol Dial Transplant. 2018;33:224–30.
Li Z, Woollard JR, Wang S, Korsmo MJ, Ebrahimi B, Grande JP, et al. Increased glomerular filtration rate in early metabolic syndrome is associated with renal adiposity and microvascular proliferation. Am J Physiol Physiol. 2011;301:F1078–87.
Bobulescu IA, Lotan Y, Zhang J, Rosenthal TR, Rogers JT, Adams-Huet B, et al. Triglycerides in the Human Kidney Cortex: Relationship with Body Size. PLoS One. 2014;9:e101285.
Bobulescu IA. Renal lipid metabolism and lipotoxicity. Curr Opin Nephrol Hypertens. 2010;19:393–402.
Sijens PE. MRI-determined fat content of human liver, pancreas and kidney. World J Gastroenterol. 2010;16:1993.
Schaapman JJ, Tushuizen ME, Coenraad MJ, Lamb HJ. Multiparametric MRI in Patients With Nonalcoholic Fatty Liver Disease. J Magn Reson Imaging. 2021;53:1623–31.
Lee H, Jun DW, Kang B-K, Nam E, Chang M, Kim M, et al. Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting. Medicine (Baltimore). 2017;96:e7778.
Di Martino M, Pacifico L, Bezzi M, Di Miscio R, Sacconi B, Chiesa C, et al. Comparison of magnetic resonance spectroscopy, proton density fat fraction and histological analysis in the quantification of liver steatosis in children and adolescents. World J Gastroenterol. 2016;22:8812.
Caussy C, Reeder SB, Sirlin CB, Loomba R. Noninvasive, Quantitative Assessment of Liver Fat by MRI-PDFF as an Endpoint in NASH Trials. Hepatology. 2018;68:763–72.
Bannas P, Kramer H, Hernando D, Agni R, Cunningham AM, Mandal R, et al. Quantitative magnetic resonance imaging of hepatic steatosis: Validation in ex vivo human livers. Hepatology. 2015;62:1444–55.
Yokoo T, Clark HR, Pedrosa I, Yuan Q, Dimitrov I, Zhang Y, et al. Quantification of renal steatosis in type II diabetes mellitus using dixon-based MRI. J Magn Reson Imaging. 2016;44:1312–9.
Idilman IS, Tuzun A, Savas B, Elhan AH, Celik A, Idilman R, et al. Quantification of liver, pancreas, kidney, and vertebral body MRI-PDFF in non-alcoholic fatty liver disease. Abdom Imaging. 2015;40:1512–9.
Huang SY, Seethamraju RT, Patel P, Hahn PF, Kirsch JE, Guimaraes AR. Body MR Imaging: Artifacts, k-Space, and Solutions. RadioGraphics. 2015;35:1439–60.
de Vries APJ, Ruggenenti P, Ruan XZ, Praga M, Cruzado JM, Bajema IM, et al. Fatty kidney: emerging role of ectopic lipid in obesity-related renal disease. Lancet Diabetes Endocrinol. 2014;2:417–26.
Zhao R, Hernando D, Harris DT, Hinshaw LA, Li K, Ananthakrishnan L, et al. Multisite multivendor validation of a quantitative MRI and CT compatible fat phantom. Med Phys. 2021;48:4375–86.
Hernando D, Sharma SD, Aliyari Ghasabeh M, Alvis BD, Arora SS, Hamilton G, et al. Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. Magn Reson Med. 2017;77:1516–24.
Acknowledgements
None.
Funding
No funds, grants, or other support were received.
Author information
Authors and Affiliations
Contributions
MG contributed to investigation, formal analysis, data curation, writing of the original draft, and visualization. AA contributed to investigation, data curation, project administration, and writing, reviewing, and editing of the manuscript. JBF contributed to methodology, resources, writing, reviewing, and editing of the manuscript, and supervision. MM contributed to methodology and writing, reviewing, and editing of the manuscript. AH contributed to conceptualization, methodology, resources, writing, reviewing, and editing of the manuscript, and supervision.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by The North Denmark Region Committee on Health Research Ethics (N-20200013).
Consent to participate
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Gjela, M., Askeland, A., Frøkjær, J.B. et al. MRI-based quantification of renal fat in obese individuals using different image analysis approaches. Abdom Radiol 47, 3546–3553 (2022). https://doi.org/10.1007/s00261-022-03603-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00261-022-03603-4