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Combining Super-Resolution Imaging and Shear Wave Elastography for Enhanced Risk Assessment of Moderate-to-Severe Renal Fibrosis in Chronic Kidney Disease Patients

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Title: Combining Super-Resolution Imaging and Shear Wave Elastography for Enhanced Risk Assessment of Moderate-to-Severe Renal Fibrosis in Chronic Kidney Disease Patients
Authors: Xingyue Huang, Yao Zhang, Yugang Hu, Juhong Pan, Xin Huang, Jun Zhang, Huan Pu, Yueying Chen, Qing Deng, Qing Zhou
Source: Int J Nephrol Renovasc Dis
International Journal of Nephrology and Renovascular Disease, Vol Volume 18, Iss Issue 1, Pp 187-199 (2025)
Publisher Information: Informa UK Limited, 2025.
Publication Year: 2025
Subject Terms: shear wave elastography, Chronic kidney disease, RC870-923, renal fibrosis, super-resolution imaging, Diseases of the genitourinary system. Urology, Original Research
Description: OBJECTIVE: This study aims to evaluate the diagnostic efficacy of shear wave elastography (SWE) and super-resolution imaging (SRI) in detecting moderate-to-severe renal fibrosis (MSRF) among patients with chronic kidney disease (CKD). METHODS: In this prospective study, 202 CKD patients who underwent SWE and SRI prior to renal biopsy were enrolled. Based on pathological findings, patients were categorized into a mild renal fibrosis group (n=107) and an MSRF group (n=95). LASSO logistic regression was employed to identify independent risk factors for MSRF. Four diagnostic models—isolated, series, parallel, and integrated—were developed by combining elasticity values from SWE and vascular density values from SRI. Additionally, a nomogram incorporating clinical parameters and ultrasound composite parameters was constructed to assess MSRF in CKD patients. RESULTS: LASSO and subsequent logistic regression analysis revealed that age, diabetes history, estimated glomerular filtration rate (eGFR), elasticity, and vascular density were independently associated with MSRF. The integrated model, utilizing a logistic algorithm, demonstrated superior diagnostic performance with an area under the curve (AUC) of 0.83 (P < 0.001), sensitivity of 80.4%, and specificity of 75.8%, outperforming all other models. Furthermore, the nomogram, which integrated clinical factors and ultrasound composite parameters, exhibited excellent predictive performance (AUC = 0.878, 95% CI 0.782–0.974). Calibration and decision curve analyses confirmed the model’s robust calibration and clinical utility. CONCLUSION: The integration of SWE-derived elasticity and SRI-derived vascular density significantly enhances the diagnostic accuracy for MSRF in CKD patients. This comprehensive approach offers a promising non-invasive strategy for assessing renal fibrosis severity.
Document Type: Article
Other literature type
Language: English
ISSN: 1178-7058
DOI: 10.2147/ijnrd.s528614
Access URL: https://doaj.org/article/4a858b8b0343459eb1d695b7449f1246
Rights: CC BY NC
URL: http://creativecommons.org/licenses/by-nc/4.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at http://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v4.0) License (http://creativecommons.org/licenses/by-nc/4.0/ (http://creativecommons.org/licenses/by-nc/4.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (http://www.dovepress.com/terms.php).
Accession Number: edsair.doi.dedup.....95ed989681c0366fa8c53baa23d2bb7c
Database: OpenAIRE
Description
Abstract:OBJECTIVE: This study aims to evaluate the diagnostic efficacy of shear wave elastography (SWE) and super-resolution imaging (SRI) in detecting moderate-to-severe renal fibrosis (MSRF) among patients with chronic kidney disease (CKD). METHODS: In this prospective study, 202 CKD patients who underwent SWE and SRI prior to renal biopsy were enrolled. Based on pathological findings, patients were categorized into a mild renal fibrosis group (n=107) and an MSRF group (n=95). LASSO logistic regression was employed to identify independent risk factors for MSRF. Four diagnostic models—isolated, series, parallel, and integrated—were developed by combining elasticity values from SWE and vascular density values from SRI. Additionally, a nomogram incorporating clinical parameters and ultrasound composite parameters was constructed to assess MSRF in CKD patients. RESULTS: LASSO and subsequent logistic regression analysis revealed that age, diabetes history, estimated glomerular filtration rate (eGFR), elasticity, and vascular density were independently associated with MSRF. The integrated model, utilizing a logistic algorithm, demonstrated superior diagnostic performance with an area under the curve (AUC) of 0.83 (P < 0.001), sensitivity of 80.4%, and specificity of 75.8%, outperforming all other models. Furthermore, the nomogram, which integrated clinical factors and ultrasound composite parameters, exhibited excellent predictive performance (AUC = 0.878, 95% CI 0.782–0.974). Calibration and decision curve analyses confirmed the model’s robust calibration and clinical utility. CONCLUSION: The integration of SWE-derived elasticity and SRI-derived vascular density significantly enhances the diagnostic accuracy for MSRF in CKD patients. This comprehensive approach offers a promising non-invasive strategy for assessing renal fibrosis severity.
ISSN:11787058
DOI:10.2147/ijnrd.s528614