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Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

A Commentary to this article was published on 25 May 2023

Abstract

Objectives

To identify optimized MRI markers for evaluating chronic kidney disease (CKD) and renal interstitial fibrosis (IF).

Materials and methods

This prospective study included 43 patients with CKD and 20 controls. The CKD group was divided into mild and moderate-to-severe subgroups based on pathological results. Scanned sequences included T1 mapping, R2* mapping, intravoxel incoherent motion imaging, and diffusion-weighted imaging. One-way analyses of variance were used to compare MRI parameters among groups. Correlations of MRI parameters with estimated glomerular filtration rate (eGFR) and renal IF were analyzed using age as covariates. The support vector machine (SVM) model was used to evaluate the diagnostic efficacy of multiparametric MRI.

Results

Compared to control values, renal cortical apparent diffusion coefficient (cADC), medullary ADC (mADC), cortical pure diffusion coefficient (cDt), medullary Dt (mDt), cortical shifted apparent diffusion coefficient (csADC), and medullary sADC (msADC) values gradually decreased in the mild and moderate-to-severe groups, while cortical T1 (cT1) and medullary T1 (mT1) values gradually increased. Values of cADC, mADC, cDt, mDt, cT1, mT1, csADC, and msADC were significantly associated with eGFR and IF (p < 0.001). The SVM model indicated that multiparametric MRI combining cT1 and csADC can distinguish patients with CKD from controls with high accuracy (0.84), sensitivity (0.70), and specificity (0.92) (AUC: 0.96). Multiparametric MRI combining cT1 and cADC exhibited high accuracy (0.91), sensitivity (0.95), and specificity (0.81) for evaluating IF severity (AUC: 0.96).

Conclusion

Multiparametric MRI combining T1 mapping and diffusion imaging may be of clinical utility in non-invasive assessment of CKD and IF.

Clinical relevance statement

This study shows that multiparametric MRI combining T1 mapping and diffusion imaging may be clinically useful in the non-invasive assessment of chronic kidney disease (CKD) and interstitial fibrosis; this could provide information for risk stratification, diagnosis, treatment, and prognosis.

Key Points

• Optimized MRI markers for evaluating chronic kidney disease and renal interstitial fibrosis were investigated.

• Renal cortex/medullary T1 values increased as interstitial fibrosis increased; cortical shifted apparent diffusion coefficient (csADC) correlated significantly with eGFR and interstitial fibrosis.

• Support vector machine (SVM) combining cortical T1 (cT1) and csADC/cADC effectively identifies chronic kidney disease and accurately predicts renal interstitial fibrosis.

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Abbreviations

ADC:

Apparent diffusion coefficient

Dp:

Pseudo-diffusion coefficient

Dt:

Pure diffusion coefficient

DWI:

Diffusion-weighted imaging

eGFR:

Estimated glomerular filtration rate

Fp:

Perfusion score

IF:

Interstitial fibrosis

IVIM:

Intravoxel incoherent motion imaging

sADC:

Shifted apparent diffusion coefficient

T1:

Longitudinal relaxation time

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Acknowledgements

We would like to express our gratitude to the participants and all the staff members for their cooperation to help finish the study.

Funding

This study has received funding by the National Natural Science Foundation of China (grant no. 81900698); Natural Science Foundation of Jiangsu Province (grant no. BK20210067); and Precision Medicine Key Project of Wuxi Health Commission (grant no. J202107).

Author information

Authors and Affiliations

  1. Diagnostic Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, No. 299 Qingyang Road, Wuxi, China

    Chenchen Hua, Bin Xu & Xiangming Fang

  2. Department of Diagnostic Radiology, The Affiliated Wuxi Children’s Hospital of Nanjing Medical University, No. 299 Qingyang Road, Wuxi, China

    Chenchen Hua, Lu Qiu, Yi Zhuang & Haoxiang Jiang

  3. Department of Nephrology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, No. 299 Qingyang Road, Wuxi, China

    Leting Zhou, Ting Cai & Liang Wang

  4. Siemens Healthineers Digital Technology (Shanghai) CO., Ltd, Shanghai, China

    Shaowei Hao

Authors
  1. Chenchen Hua
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  2. Lu Qiu
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Corresponding authors

Correspondence to Liang Wang or Haoxiang Jiang.

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Guarantor

The scientific guarantor of this publication is Haoxiang Jiang.

Conflict of interest

One of the authors (Shaowei Hao) is an employee of Siemens Healthineers. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

No study subjects or cohorts have been previously reported.

Methodology

  • prospective

  • diagnostic study/observational

  • performed at one institution

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Chenchen Hua, Lu Qiu, and Leting Zhou contributed equally to this work as co-first authors.

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Supplementary file1 (PDF 585 KB)

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Hua, C., Qiu, L., Zhou, L. et al. Value of multiparametric magnetic resonance imaging for evaluating chronic kidney disease and renal fibrosis. Eur Radiol 33, 5211–5221 (2023). https://doi.org/10.1007/s00330-023-09674-1

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  • DOI: https://doi.org/10.1007/s00330-023-09674-1

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