Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
467-02-005 ISMRM Abstract

Diffusion MRI-Based Virtual Elastography for Chronic Kidney Disease Assessment: initial study

Accepted
Yanping Lin1, Liujun Liu1, Yunyi Liu1, Qingyun Wang1, Xiaoyan Su1, Yunyu Gao2, Zhaoyong Li 1
1Department of Radiology, DongGuan Tungwah Hospital, Dongguan Key Laboratory of Radiology and Molecular Imaging, Dongguan, China
2Clinical and Technical Support, Philips Healthcare (Guangzhou), Guangzhou, China
Presenting Author: Zhaoyong Li

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Zhou, Huan, et al. “Effectiveness of Functional Magnetic Resonance Imaging for Early Identification of Chronic Kidney Disease: A Systematic Review and Network Meta-Analysis.” European Journal of Radiology, vol. 160, Mar. 2023, p. 110694. Crossref, https://doi.org/10.1016/j.ejrad.2023.110694. [doi]
2. Schawkat, Khoschy, et al. “Diagnostic Accuracy of Texture Analysis and Machine Learning for Quantification of Liver Fibrosis in MRI: Correlation with MR Elastography and Histopathology.” European Radiology, vol. 30, no. 8, Apr. 2020, pp. 4675–4685. Crossref, https://doi.org/10.1007/s00330-020-06831-8. [doi]
3. Tagliabue, Marta, et al. “The Prognostic Role of MRI-Based Radiomics in Tongue Carcinoma: A Multicentric Validation Study.” La Radiologia Medica, vol. 129, no. 9, Aug. 2024, pp. 1369–1381. Crossref, https://doi.org/10.1007/s11547-024-01859-y. [doi]
4. Le Bihan, Denis. “From Brownian Motion to Virtual Biopsy: A Historical Perspective from 40 Years of Diffusion MRI.” Japanese Journal of Radiology, vol. 42, no. 12, Sept. 2024, pp. 1357–1371. Crossref, https://doi.org/10.1007/s11604-024-01642-z. [doi]
5. Jang, Weon, et al. “Comparison of Diffusion-Weighted Imaging and MR Elastography in Staging Liver Fibrosis: A Meta-Analysis.” Abdominal Radiology, vol. 46, no. 8, Mar. 2021, pp. 3889–3907. Crossref, https://doi.org/10.1007/s00261-021-03055-2. [doi]
6. Huang, Xutong, et al. “Optimized DWI-Based Virtual MR Elastography for Diagnosis and Therapeutic Monitoring of Focal Liver Lesions.” European Journal of Radiology, vol. 191, Oct. 2025, p. 112285. Crossref, https://doi.org/10.1016/j.ejrad.2025.112285. [doi]
7. Lee, Jeong Hyun, et al. “Magnetic Resonance Elastography as a Preoperative Assessment for Predicting Intrahepatic Recurrence in Patients with Hepatocellular Carcinoma.” Magnetic Resonance Imaging, vol. 109, June 2024, pp. 127–133. Crossref, https://doi.org/10.1016/j.mri.2024.03.014. [doi]
8. Hectors, Stefanie J., et al. “Fully Automated Prediction of Liver Fibrosis Using Deep Learning Analysis of Gadoxetic Acid–Enhanced MRI.” European Radiology, vol. 31, no. 6, Nov. 2020, pp. 3805–3814. Crossref, https://doi.org/10.1007/s00330-020-07475-4. [doi]
9. Korsmo, Michael James, et al. “Magnetic Resonance Elastography (MRE) Detects Medullary Renal Fibrosis.” The FASEB Journal, vol. 26, no. S1, Apr. 2012. Crossref, https://doi.org/10.1096/fasebj.26.1_supplement.523.3. [doi]
10. Duan, Suyan, et al. “Utilization of the Corticomedullary Difference in Magnetic Resonance Imaging-Derived Apparent Diffusion Coefficient for Noninvasive Assessment of Chronic Kidney Disease in Type 2 Diabetes.” Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 18(2), Feb. 2024, p. 102963. Crossref, https://doi.org/10.1016/j.dsx.2024.102963. [doi]
11. Li, Yiming, et al. “Renal Stiffness Measured by Shear Wave Elastography and Its Relationship with Perirenal Fat in Patients with Chronic Kidney Disease.” Journal of Clinical Ultrasound, vol. 52, no. 1, Oct. 2023, pp. 3–12. Crossref, https://doi.org/10.1002/jcu.23598. [doi]
12. Maralescu, Felix-Mihai, et al. “#613 Is There a Relationship between Kidney Stiffness Identified by 2D Shear Wave Elastography and the Estimated Glomerular Filtration Rate?” Nephrology Dialysis Transplantation, vol. 39, no. Supplement_1, May 2024. Crossref, https://doi.org/10.1093/ndt/gfae069.495. [doi]
13. Liang, Ping, et al. “Non-Invasive Evaluation of the Pathological and Functional Characteristics of Chronic Kidney Disease by Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion Imaging: Comparison with Conventional DWI.” The British Journal of Radiology, vol. 96, no. 1141, Dec. 2022. Crossref, https://doi.org/10.1259/bjr.20220644. [doi]
14. Sayed, Shaimaa, et al. “Assessment of Kidney Tissue Stiffness in Different Stages of Pediatric Chronic Kidney Disease Using Shear Wave Elastography: A Case–Control Study.” Egyptian Journal of Radiology and Nuclear Medicine, vol. 56, no. 1, Mar. 2025. Crossref, https://doi.org/10.1186/s43055-025-01438-9. [doi]
15. Sun, Kun, et al. “Diffusion‐Weighted <scp>MRI</scp>‐Based Virtual Elastography and Shear-Wave Elastography for the Assessment of Breast Lesions.” Journal of Magnetic Resonance Imaging, Feb. 2024. Crossref, https://doi.org/10.1002/jmri.29302. [doi]
16. Jiang, Buchun, et al. “Advances in Imaging Techniques to Assess Kidney Fibrosis.” Renal Failure, vol. 45, no. 1, Feb. 2023. Crossref, https://doi.org/10.1080/0886022x.2023.2171887. [doi]
17. Duan, Suyan, et al. “Utilization of the Corticomedullary Difference in Magnetic Resonance Imaging-Derived Apparent Diffusion Coefficient for Noninvasive Assessment of Chronic Kidney Disease in Type 2 Diabetes.” Diabetes & Metabolic Syndrome: Clinical Research & Reviews,18( 2), Feb. 2024, p. 102963. Crossref, https://doi.org/10.1016/j.dsx.2024.102963. [doi]

Cite this abstract