Skip to main content
SpringerLink
Log in

Arterial spin labeling and diffusion-weighted MR imaging: quantitative assessment of renal pathological injury in chronic kidney disease

  • Kidneys, Ureters, Bladder, Retroperitoneum
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

The aim of the study was to investigate the performance of arterial spin labeling (ASL), diffusion-weighted imaging (DWI), and clinical biomarkers in assessing renal pathological injury in CKD.

Materials and methods

Forty-five biopsy-proven CKD patients and 17 healthy volunteers underwent DWI and ASL examinations. Renal cortical blood flow (RBF) and apparent diffusion coefficient (ADC) values were acquired. Correlations between RBF, ADC, serum creatinine (SCr), estimated glomerular filtration rate (eGFR), and pathological scores were assessed. The diagnostic efficacy of SCr, eGFR, RBF, and ADC in assessing renal pathological injury was assessed by ROC curve analysis.

Results

The cortical RBF, ADC, SCr, and eGFR were significantly correlated with the renal histology score (all p < 0.01). The AUC values of SCr, eGFR, RBF, and ADC were 0.705 (95% confidence interval (CI): 0.536–0.827), 0.718 (0.552–0.839), 0.823 (0.658–0.916), and 0.624 (0.451–0.786), respectively, in discriminating the minimal–mild renal pathological injury group (N = 30) from the control group (N = 17). The diagnostic ability of ASL was significantly higher than that of DWI (p = 0.049) and slightly but not significantly higher than that of eGFR and SCr (p = 0.151 and p = 0.129, respectively). When compared with that of eGFR, the sensitivity of ASL in detecting early renal injury increased from 50 to 70% (p = 0.014). However, in differentiating between the minimal–mild and moderate–severe renal injury groups (N = 15), there was no significant difference in diagnostic ability among the four parameters (all p > 0.05).

Conclusion

ASL is practicable for noninvasive evaluation of renal pathology, especially for predicting early renal pathological injury in CKD patients.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

All authors had control of the participants’ data and study information.

References

  1. 1 Webster AC, Nagler EV, Morton RL, Masson P (2017) Chronic Kidney Disease. The Lancet 389:1238-1252. https://doi.org/10.1016/s0140-6736(16)32064-5

    Article  Google Scholar 

  2. 2 Collaboration GBDCKD (2020) Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 395:709-733. https://doi.org/10.1016/S0140-6736(20)30045-3

    Article  Google Scholar 

  3. 3 Trevisani F, Di Marco F, Capitanio U et al (2021) Renal histology across the stages of chronic kidney disease. J Nephrol 34:699-707. https://doi.org/10.1007/s40620-020-00905-y

    Article  CAS  PubMed  Google Scholar 

  4. 4 Wang YN, Ma SX, Chen YY et al (2019) Chronic kidney disease: Biomarker diagnosis to therapeutic targets. Clinica Chimica Acta 499:54-63.https://doi.org/10.1016/j.cca.2019.08.030

    Article  CAS  Google Scholar 

  5. 5 Granata A, Distefano G, Pesce F et al (2021) Performing an Ultrasound-Guided Percutaneous Needle Kidney Biopsy: An Up-To-Date Procedural Review. Diagnostics (Basel) https://doi.org/10.3390/diagnostics11122186

    Article  PubMed  PubMed Central  Google Scholar 

  6. 6 Gao J, Perlman A, Kalache S et al (2017) Multiparametric Quantitative Ultrasound Imaging in Assessment of Chronic Kidney Disease. Journal of Ultrasound in Medicine 36:2245-2256. https://doi.org/10.1002/jum.14209

    Article  PubMed  PubMed Central  Google Scholar 

  7. 7 Gupta S, Singh AH, Shabbir A, Hahn PF, Harris G, Sahani D (2012) Assessing renal parenchymal volume on unenhanced CT as a marker for predicting renal function in patients with chronic kidney disease. Academic Radiology 19:654-660. https://doi.org/10.1016/j.acra.2012.02.006

    Article  PubMed  Google Scholar 

  8. 8 von Stillfried S, Apitzsch JC, Ehling J et al (2016) Contrast-enhanced CT imaging in patients with chronic kidney disease. Angiogenesis 19:525-535. https://doi.org/10.1007/s10456-016-9524-7

    Article  CAS  Google Scholar 

  9. 9 Wang Y, Liu K, Xie X, Song B (2021) Contrast-associated acute kidney injury: An update of risk factors, risk factor scores, and preventive measures. Clinical Imaging 69:354-362. https://doi.org/10.1016/j.clinimag.2020.10.009

    Article  PubMed  Google Scholar 

  10. 10 Rosar F, Pauly P, Ries M et al (2020) Determination of split renal function by PSMA imaging: comparison of (68)Ga-PSMA-11 PET with (99m)Tc-MAG3 scintigraphy. American Journal of Nuclear Medicine and Molecular Imaging 10:249-256.

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11 Liu Z, Xu Y, Zhang J et al (2015) Chronic kidney disease: pathological and functional assessment with diffusion tensor imaging at 3T MR. European Radiology 25:652-660. https://doi.org/10.1007/s00330-014-3461-x

    Article  PubMed  Google Scholar 

  12. 12 Mao W, Ding Y, Ding X et al (2021) Pathological assessment of chronic kidney disease with DWI: Is there an added value for diffusion kurtosis imaging? Journal of Magnetic Resonance Imaging 54:508-517. https://doi.org/10.1002/jmri.27569

    Article  PubMed  Google Scholar 

  13. 13 Nassar MK, Khedr D, Abu-Elfadl HG et al (2021) Diffusion Tensor Imaging in early prediction of renal fibrosis in patients with renal disease: Functional and histopathological correlations. International Journal of Clinical Practice 75:e13918. https://doi.org/10.1111/ijcp.13918

    Article  CAS  PubMed  Google Scholar 

  14. 14 Li Q, Li J, Zhang L, Chen Y, Zhang M, Yan F (2014) Diffusion-weighted imaging in assessing renal pathology of chronic kidney disease: A preliminary clinical study. European Journal of Radiology 83:756-762. https://doi.org/10.1016/j.ejrad.2014.01.024

    Article  PubMed  Google Scholar 

  15. 15 Hueper K, Khalifa AA, Brasen JH et al (2016) Diffusion-Weighted imaging and diffusion tensor imaging detect delayed graft function and correlate with allograft fibrosis in patients early after kidney transplantation. Journal of Magnetic Resonance Imaging 44:112-121. https://doi.org/10.1002/jmri.25158

    Article  PubMed  Google Scholar 

  16. 16 Zhao J, Wang ZJ, Liu M et al (2014) Assessment of renal fibrosis in chronic kidney disease using diffusion-weighted MRI. Clinical Radiology 69:1117-1122. https://doi.org/10.1016/j.crad.2014.06.011

    Article  CAS  PubMed  Google Scholar 

  17. 17 Kim DW, Shim WH, Yoon SK et al (2017) Measurement of arterial transit time and renal blood flow using pseudocontinuous ASL MRI with multiple post-labeling delays: Feasibility, reproducibility, and variation. Journal of Magnetic Resonance Imaging 46:813-819. https://doi.org/10.1002/jmri.25634

    Article  PubMed  Google Scholar 

  18. 18 Cai YZ, Li ZC, Zuo PL et al (2017) Diagnostic value of renal perfusion in patients with chronic kidney disease using 3D arterial spin labeling. Journal of Magnetic Resonance Imaging 46:589-594. https://doi.org/10.1002/jmri.25601

    Article  PubMed  Google Scholar 

  19. 19 Lu F, Yang J, Yang S et al (2021) Use of Three-Dimensional Arterial Spin Labeling to Evaluate Renal Perfusion in Patients With Chronic Kidney Disease. Journal of Magnetic Resonance Imaging 54:1152-1163. https://doi.org/10.1002/jmri.27609

    Article  PubMed  Google Scholar 

  20. 20 Li LP, Tan H, Thacker JM et al (2017) Evaluation of Renal Blood Flow in Chronic Kidney Disease Using Arterial Spin Labeling Perfusion Magnetic Resonance Imaging. Kidney Int Rep 2:36-43. https://doi.org/10.1016/j.ekir.2016.09.003

    Article  PubMed  Google Scholar 

  21. 21 Gillis KA, McComb C, Patel RK et al (2016) Non-Contrast Renal Magnetic Resonance Imaging to Assess Perfusion and Corticomedullary Differentiation in Health and Chronic Kidney Disease. Nephron 133:183-192. https://doi.org/10.1159/000447601

    Article  PubMed  Google Scholar 

  22. 22 Rutkowski M, Mann W, Derose S et al (2009) Implementing KDOQI CKD definition and staging guidelines in Southern California Kaiser Permanente. American Journal of Kidney Diseases 53:S86-99. https://doi.org/10.1053/j.ajkd.2008.07.052

    Article  PubMed  Google Scholar 

  23. 23 Andrew S. Levey LAS, Christopher H. Schmid, Yaping (Lucy) Zhang, Alejandro F. Castro III, Harold I. Feldman, John W. Kusek, Paul Eggers, Frederick Van Lente, Tom Greene, and Josef Coresh (2009) A new equation to estimate glomerular filtration rate Annals of Internal Medicine:604–612.

    Article  PubMed  PubMed Central  Google Scholar 

  24. 24 Buxton RB, Frank LR, Wong EC, Siewert B, Warach S, Edelman RR (1998) A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magnetic Resonance in Medicine 40:383-396. https://doi.org/10.1002/mrm.1910400308

    Article  CAS  PubMed  Google Scholar 

  25. 25 Sethi S, D'Agati VD, Nast CC et al (2017) A proposal for standardized grading of chronic changes in native kidney biopsy specimens. Kidney International 91:787-789. https://doi.org/10.1016/j.kint.2017.01.002

    Article  PubMed  Google Scholar 

  26. 26 Brown RS, Sun MRM, Stillman IE, Russell TL, Rosas SE, Wei JL (2020) The utility of magnetic resonance imaging for noninvasive evaluation of diabetic nephropathy. Nephrology, Dialysis, Transplantation 35:970-978. https://doi.org/10.1093/ndt/gfz066

    Article  PubMed  Google Scholar 

  27. 27 Katafuchi R, Kiyoshi Y, Oh Y et al (1998) Glomerular score as a prognosticator in IgA nephropathy: its usefulness and limitation. Clinical Nephrology 49:1-8.

    CAS  PubMed  Google Scholar 

  28. 28 Srivastava A, Palsson R, Kaze AD et al (2018) The Prognostic Value of Histopathologic Lesions in Native Kidney Biopsy Specimens: Results from the Boston Kidney Biopsy Cohort Study. Journal of the American Society of Nephrology 29:2213-2224. https://doi.org/10.1681/asn.2017121260

    Article  PubMed  PubMed Central  Google Scholar 

  29. 29 Yu YM, Wang W, Wen J, Zhang Y, Lu GM, Zhang LJ (2021) Detection of renal allograft fibrosis with MRI: arterial spin labeling outperforms reduced field-of-view IVIM. European Radiology 31:6696-6707. https://doi.org/10.1007/s00330-021-07818-9

    Article  PubMed  Google Scholar 

  30. 30 Notohamiprodjo M, Reiser MF, Sourbron SP (2010) Diffusion and perfusion of the kidney. European Journal of Radiology 76:337-347. https://doi.org/10.1016/j.ejrad.2010.05.033

    Article  PubMed  Google Scholar 

  31. 31 Mathur M, Jones JR, Weinreb JC (2020) Gadolinium Deposition and Nephrogenic Systemic Fibrosis: A Radiologist's Primer. Radiographics 40:153-162. https://doi.org/10.1148/rg.2020190110

    Article  PubMed  Google Scholar 

  32. 32 Caraiani C, Petresc B, Dong Y, Dietrich CF (2019) Contraindications and adverse effects in abdominal imaging. Medical Ultrasonography 21:456-463. https://doi.org/10.11152/mu-2145

    Article  PubMed  Google Scholar 

  33. 33 Ritt M, Janka R, Schneider MP et al (2010) Measurement of kidney perfusion by magnetic resonance imaging: comparison of MRI with arterial spin labeling to para-aminohippuric acid plasma clearance in male subjects with metabolic syndrome. Nephrology, Dialysis, Transplantation 25:1126-1133. https://doi.org/10.1093/ndt/gfp639

    Article  CAS  PubMed  Google Scholar 

  34. 34 Buchanan CE, Mahmoud H, Cox EF et al (2020) Quantitative assessment of renal structural and functional changes in chronic kidney disease using multi-parametric magnetic resonance imaging. Nephrology, Dialysis, Transplantation 35:955-964. https://doi.org/10.1093/ndt/gfz129

    Article  PubMed  Google Scholar 

  35. 35 Friedli I, Crowe LA, Berchtold L et al (2016) New Magnetic Resonance Imaging Index for Renal Fibrosis Assessment: A Comparison between Diffusion-Weighted Imaging and T1 Mapping with Histological Validation. Scientific Reports 6:30088. https://doi.org/10.1038/srep30088

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. 36 Humphreys BD (2018) Mechanisms of Renal Fibrosis. Annual Review of Physiology 80:309-326. https://doi.org/10.1146/annurev-physiol-022516-034227

    Article  CAS  PubMed  Google Scholar 

  37. 37 Srivastava A, Cai X, Lee J et al (2020) Kidney Functional Magnetic Resonance Imaging and Change in eGFR in Individuals with CKD. Clinical Journal of the American Society of Nephrology 15:776-783. https://doi.org/10.2215/CJN.13201019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. 38 Sulkowska K, Palczewski P, Furmanczyk-Zawiska A et al (2020) Diffusion Weighted Magnetic Resonance Imaging in the Assessment of Renal Function and Parenchymal Changes in Chronic Kidney Disease: A Preliminary Study. Annals of Transplantation 25:e920232. https://doi.org/10.12659/AOT.920232

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Funding

The authors state that this study has received funding by National Natural Science Foundation of China grant 91959118 (JW) and 82271973 (JW), Clinical Research Foundation of the 3rd Affiliated Hospital of Sun Yat-Sen University YHJH201901 (JW), Key Research and Development Program of Guangdong Province 2019B020235002 (JW), Guangdong Basic and Applied Research Foundation 2021A1515010582 (JW), SKY Radiology Department International Medical Research Foundation of China Z-2014–07-2101 (JW), and National Natural Science Foundation of China grant 82000727 (YL).

Author information

Author notes

  1. Shan Pi and Yin Li were contributed equally to the study concept and design, acquisition of data, statistical analysis, analysis and interpretation of data, drafting of the manuscript, and critical revision of the manuscript for important intellectual content.

Authors and Affiliations

  1. Department of Radiology, Third Affiliated Hospital, Sun Yat-Sen University (SYSU), Tianhe Road, No 600, Guangzhou, 510630, Guangdong, People’s Republic of China

    Shan Pi, Churong Lin, Gang Li, Huiquan Wen & Jin Wang

  2. Department of Nephrology, Third Affiliated Hospital, Sun Yat-Sen University (SYSU), Tianhe Road, No 600, Guangzhou, 510630, Guangdong, People’s Republic of China

    Yin Li & Hui Peng

Authors
  1. Shan Pi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Churong Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Huiquan Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hui Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Material preparation, data collection, and analysis were mainly performed by SP and YL. Meanwhile, CL and GL helped to collect the patients’ data. HP helped to revise the manuscript. HW helped to perform MRI scanning. JW and HP participated in the design of the study. JW also supervised the study. The first draft of the manuscript was written by SP and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. I would like to declare on behalf of my co-authors that the work described was original study that has not been published previously. All the authors listed have approved the manuscript that is enclosed.

Corresponding authors

Correspondence to Hui Peng or Jin Wang.

Ethics declarations

Conflict of interest

The authors declare that they do not have any conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This study has been approved by an institutional review board of the hospital.

Consent to participate

This study has been approved by an institutional review board of the hospital. Written informed consent was obtained from all participants before the renal MRI examination.

Consent to publication

Not applicable for that section.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This Work originated from Department of Radiology, The Third Affiliated Hospital of Sun Yat-Sen University, 600 Tianhe Rd, Guangzhou 510630, People's Republic of China.

Supplementary Information

Below is the link to the electronic supplementary material.

261_2022_3770_MOESM1_ESM.tif

Supplementary file1 Bland–Altman plot showing the difference between the cortical RBF (a) and ADC (b) values obtained by Reviewer 1 and Reviewer 2 versus the mean cortical RBF and ADC values for 45 CKD patients. The solid line indicates the mean difference, and the dashed line represents the 95% prediction interval as the mean of the difference ± 1.96 times the standard deviation. (TIF 911 KB)

261_2022_3770_MOESM2_ESM.tif

Supplementary file2 Negative correlations are observed between the chronic lesion score (a), tubulointerstitial fibrosis score (b), interstitial inflammation score (c) and eGFR. Positive correlations are observed between the chronic lesion score (d), tubulointerstitial fibrosis score (e), interstitial inflammation score (f) and SCr. eGFR, estimated glomerular filtration rate; Scr, serum creatinine (TIF 662 KB)

261_2022_3770_MOESM3_ESM.tif

Supplementary file3 Comparison of the SCr and eGFR among the control group, minimal–mild renal injury group and moderate–severe renal injury group. (a) Bar graphs show that the SCr were significantly higher in the moderate–severe renal injury group than in the control group (**p < 0.001) and minimal–mild renal injury group (*p <0.05). (b) Bar graphs show that the eGFR in the moderate–severe renal injury group were significantly lower than those in the control group (**p < 0.001) and minimal–mild renal injury group (**p < 0.001). SCr and eGFR were not significantly different between the minimal–mild renal injury group and the control group. (TIF 1257 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pi, S., Li, Y., Lin, C. et al. Arterial spin labeling and diffusion-weighted MR imaging: quantitative assessment of renal pathological injury in chronic kidney disease. Abdom Radiol 48, 999–1010 (2023). https://doi.org/10.1007/s00261-022-03770-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-022-03770-4

Keywords

Search

Navigation