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

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.