Sound touch viscosity imaging for chronic kidney disease staging: a novel biomarker for renal fibrosis

Introduction

Chronic kidney disease (CKD) is a progressive and irreversible pathological syndrome. Characterized by an insidious onset, CKD leads to renal dysfunction as it advances, ultimately progressing to end-stage kidney disease (ESKD). CKD is a silent disease. It has a global prevalence of 9.1%, and accounts for 4.6% of all-cause mortality (1). It is projected that CKD will become the fifth leading cause of death worldwide by 2040 (2).

ESKD is now recognized as a significant risk factor for other adverse outcomes, including cardiovascular diseases (3). Early detection and intervention are therefore critical for improving prognosis. However, the initial clinical manifestations of CKD are often non-specific, and conventional diagnostic tools, such as serum creatinine (SCr), proteinuria, estimated glomerular filtration rate (eGFR), and intrarenal Doppler resistance indices, exhibit incomplete concordance with disease progression (4).

Pathologically, CKD is defined by renal fibrosis (1), the extent of which is correlated with disease severity (5-7). Kidney biopsy remains the gold standard for assessing renal failure and diagnosing CKD (8,9); however, due to its invasive nature (10), it carries inherent risks of bleeding or infection, leading to some patients refusing the procedure. Although advanced imaging techniques have revealed that fibrotic deposition can be heterogeneous and patchy across the parenchyma, the overall burden of fibrosis is nonetheless correlated with disease severity (11). New, less invasive methods would bring more safety, comfort, and adherence for frequent monitoring (8).

Ultrasonography (US) is the most widely used imaging modality in the non-invasive evaluation of renal diseases. It primarily relies on measuring kidney size, cortical echogenicity, and cortical thickness as markers of CKD (12,13). Although these conventional US parameters correlate well with the eGFR and proteinuria severity, such morphological changes typically manifest only in relatively advanced stages of the disease (14). Conventional US is a safe and non-invasive tool for tracking renal morphology and structural changes; however, it faces challenges in identifying mild fibrosis (15). A study has shown that histological alterations, including glomerulosclerosis and interstitial fibrosis, occur before detectable decreases in the eGFR (14).

Sound touch viscosity imaging (STVi) has become a popular area of research in medical imaging due to its non-invasive ability to assess tissue viscoelastic properties. Extensive studies have shown that STVi is a reliable method for quantifying viscoelastic characteristics in various tissues, including the breast and thyroid glands, demonstrating its effectiveness in differentiating between healthy and diseased tissues (16,17). The technology measures the elasticity and viscosity of the region of interest (ROI) based on the relationship between shear wave propagation speed and frequency in tissues, and provides an intuitive quantitative visualization through color mapping.

This dual-parameter assessment provides comprehensive insights into renal pathology, where the elastic modulus primarily reflects fibrosis severity, whereas viscosity parameters show greater sensitivity to inflammatory activity and tissue edema (3,18,19). The elastic modulus (E) can be expressed by the following fundamental equation:

E=3ρcs2[1]

where ρ represents tissue density and cₛ denotes shear wave velocity (20). The distinct shear wave propagation speeds in healthy versus pathological tissues, resulting from their stiffness differences, form the physical basis for tissue characterization. In biological tissues, viscosity causes shear wave dispersion, such that the propagation speed of the shear wave increases with its frequency. The Voigt model, which combines elastic (spring) and viscous (dashpot) elements in parallel, is widely adopted to characterize soft tissue viscoelasticity due to its capacity to capture frequency-dependent shear wave propagation, as established in foundational biomechanical studies (21,22). Although the kidney has a distinctive tissue architecture, the Voigt model is well-suited for its analysis. This is supported by its successful application in renal tissue (23), and because the renal parenchyma—as a soft tissue comprising both elastic (e.g., fibrotic stroma) and viscous (e.g., interstitial fluid-rich regions) components—exhibits the very biomechanical behavior that the model depicts (24). Thus, we used Voigt model-based shear wave dispersion analysis; the equation can be expressed as follows (20,21):

cρ=2(μ12+ω2μ22)ρ(μ1+(μ12+ω2μ22))[2]

where μ₁ and μ₂ represent shear elasticity and viscosity, respectively, ω denotes frequency in radians/second, and ρ indicates material density.

Despite established correlations between renal stiffness measurements, and both fibrosis staging and the eGFR decline (25-30), several technical limitations have been identified (31). The inherent heterogeneity and anisotropic structure of renal tissue lead to direction-dependent shear wave propagation, resulting in significant measurement variability across different sampling sites (3). Further, physiological factors, including renal artery pulsation and variations in pelvic pressure, may cause fluctuations in stiffness values (3,32), whereas the overlapping ranges of elastic modulus between mild and moderate fibrosis stages present diagnostic challenges. These technical constraints may contribute to the inconsistent findings reported in the literature on the relationship between tissue stiffness changes and renal function deterioration (33-36). Notably, although studies have identified blood perfusion as a major confounding factor in renal elasticity measurements (15), viscosity parameters demonstrate superior stability, as they remain unaffected by hemodynamic variations (3).

Conversely, conventional shear wave elastography (SWE) techniques predominantly use a purely elastic medium model, which can only provide tissue shear modulus data (37,38). However, biological tissues are intrinsically viscoelastic media, possessing both elastic and viscous properties (20,39). Therefore, compared to conventional SWE, STVi can provide a more comprehensive assessment of pathological progression.

Ultrasound viscoelastic imaging has led to significant advancements in liver disease evaluation (40,41), and has been extensively applied to the non-invasive diagnosis of thyroid and breast lesions (16,42-44); however, systematic research regarding its efficacy in quantitatively assessing renal dysfunction in CKD patients is lacking. Further, no established diagnostic criteria are currently available for CKD staging using this technology. To address these issues, the present study sought to comprehensively evaluate the clinical utility of ultrasound viscoelastic imaging in CKD management. Through this investigation, we developed novel technical protocols and theoretical frameworks for non-invasive CKD assessment, thereby overcoming the limitations of existing imaging modalities. Additionally, this study examined whether tissue viscosity can serve as a potential novel biomarker or complement Young’s modulus for CKD detection, particularly in patients with comorbid conditions. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1526/rc).

Methods

Patient recruitment and grouping

This prospective cross-sectional study was approved by the Ethics Committee of the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University (No. K2025134), and written informed consent was provided by all participants or their legal guardians. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Sample size estimation incorporated a 9.1% population prevalence, anticipating 20% exclusions and 10% attrition. To detect an odds ratio (OR) =2.0 (α=0.05, power =80%), we required 140 CKD cases, derived from standard case-control power calculations. To maximize resource efficiency while preserving analytical rigor, we adopted an unmatched case-control study design. A total of 93 potential controls were screened, with 84 meeting all eligibility criteria and ultimately included in the final analysis.

CKD diagnosis followed the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines [i.e., an eGFR of 60–90 mL/min/1.73 m² and a urinary albumin-to-serum creatinine ratio (UACR) ≥30 mg/g or an eGFR <60 mL/min/1.73 m² even in the absence of albuminuria for ≥30 mg/g] (45). The healthy controls (HCs) had to meet the following criteria: an eGFR ≥90 mL/min/1.73 m², a UACR <30 mg/g, and no history of chronic diseases. Patients who visited the Nephrology Department of the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University between September 2024 and March 2025 were consecutively studied. A total of 140 patients were excluded for renal cysts (>3 cm in diameter) or other space-occupying lesions, renal artery stenosis [peak systolic velocity (PSV) >180 cm/s or resistive index (RI) >0.8], uncontrolled hypertension (blood pressure >160/100 mmHg), New York Heart Association (NYHA) class III–IV heart failure, massive ascites, skin-to-kidney measurement depth >8 cm, and poor image quality (reliability index <90%). The complete clinical data of the participants were collected, including demographics, laboratory tests, and comorbidities. As shown in Figure 1, a total of 127 patients diagnosed with CKD and 84 HCs from the International Healthcare Center of the same hospital during the same period were enrolled in this study. The CKD patients were stratified into G1–G5 stages based on the KDIGO criteria (45).

Figure 1 Flowchart of CKD patients and healthy volunteers screening. CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; NYHA, New York Heart Association; PSV, peak systolic velocity; RI, resistive index; UACR, urinary albumin-to-serum creatinine ratio.

Ultrasound equipment and imaging technology

This study used the Mindray Resona A20 diagnostic system (Mindray Bio-Medical Electronics, Shenzhen, China) with an SC7-1U probe (1.2–6.0 MHz), and a viscoelastic imaging software module. The following viscoelastic parameters derived from the Voigt model were employed: Cρ mean, representing shear wave velocity, and E mean, reflecting tissue stiffness (Eq. [1]). The viscosity coefficient (Vi mean) was calculated by analyzing shear wave dispersion slopes within the 50–400 Hz frequency range (Eq. [2]). Standardized ultrasound viscoelastic imaging protocols were implemented for all participants to ensure data consistency and comparability.

Image acquisition and processing

All examinations were performed by experienced sonographers with over 5 years of specialized training, who were blinded to the participants’ clinical information. To further ensure the reliability of the data, for each patient, the sonographer repeated the elasticity and viscosity imaging measurements at least three times. The average value of these measurements was used as the final data for analysis. This approach effectively reduced both inter- and intra-observer variability. The standardized imaging protocol required participants to assume a prone position with arms flexed and hands positioned under the forehead for support to ensure back muscle relaxation. Prior to the measurements, participants were asked to rest for 10 minutes in a temperature-controlled laboratory (22±1 ℃) to ensure physiological stability. Additionally, participants were required to fast for at least 6 hours before the examination to avoid potential interference from metabolic factors. B-mode ultrasound imaging was initially performed to capture the maximal longitudinal renal section, after which, simultaneous elasticity and viscosity imaging was performed in the identical plane. During the data acquisition, the participants were instructed to maintain a 6-second breath-hold while a standardized ROI (2 cm × 2 cm) was positioned within the parenchymal area, encompassing both the renal cortex and the medulla. The ROI was carefully placed to avoid major vasculature and the central renal sinus structures. This approach provides a composite measurement of the viscoelastic properties of the global renal parenchyma, as the current resolution of STVi does not allow for discrete sampling of the cortex alone. Both kidneys were measured separately, with at least three repeated measurements taken for each kidney, and the average value was finally calculated. Consecutive measurements were obtained with ROI repositioning (6-mm diameter) between acquisitions, ensuring no repeated sampling in identical tissue planes.

Strict quality criteria mandated an interquartile range/median ratio <30% (46), with additional acoustic attenuation correction (0.5 dB/cm/MHz) applied for deep cortical measurements (>6 cm depth). Image quality validation required achieving a 5-star Motion Stability Index rating, corresponding to a reliability index >90%, while maintaining minimal transducer contact pressure throughout the procedure.

The comprehensive renal evaluation incorporated grayscale ultrasound, viscosity mapping, and elasticity mapping, with all imaging data and corresponding quality metrics displayed in the synchronized quad-view mode. The tissue mechanical properties were quantitatively derived via an analysis of the shear wave dispersion characteristics within the ROIs, reflecting the frequency-dependent propagation velocity. Elastic modulus was calculated from shear wave speed (m/s), whereas dynamic viscosity was expressed in pascal-seconds (Pa·s). Advanced color-encoded parametric mapping technology enabled the spatial visualization of these biomechanical properties, providing an intuitive representation of the tissue stiffness and viscosity distribution patterns across the renal parenchyma.

Histopathological evaluation

All renal biopsy procedures were performed within three months prior to the ultrasound viscoelastic imaging examinations to ensure clinical stability without significant disease progression. This time interval was chosen based on the natural history of CKD, which typically progresses slowly in clinically stable patients. We operated under the assumption that the underlying renal pathology would not undergo substantial change during this period. Under ultrasound guidance, an 18-gauge biopsy needle was precisely positioned at the lower pole of the left kidney to obtain cortical tissue specimens. This biopsy site was consistent with the general area of ultrasound image acquisition for the left kidney, ensuring that the histopathological evaluation corresponded to the ROI in the ultrasound viscoelastic imaging. Immediately after collection, the samples were fixed in 10% neutral buffered formalin and subsequently processed at the pathology laboratory. The pathologists were unaware of the patients’ ultrasound test results or other clinical information when evaluating the renal biopsy results. In addition, the sonographers performing the ultrasound viscoelastic imaging were also blinded to the renal biopsy results. This was implemented to avoid any potential bias in image acquisition and interpretation, ensuring the objectivity of the ultrasound examination.

For the comprehensive histological assessment, paraffin-embedded tissue sections were prepared and stained with hematoxylin and eosin (H&E) for the general morphological evaluation; periodic acid-Schiff was used for the glomerular basement membrane and matrix analysis; Jones methenamine silver was used for enhanced glomerular architectural details; and Masson’s trichrome was used for the collagen deposition and fibrosis quantification. For fibrosis grading, renal cortical fibrosis severity was quantified using the Banff 2019 classification system, which provides standardized histopathological assessment criteria. Specifically, the tubulointerstitial fibrosis score (ci) was used to grade fibrosis severity: ci 0 (no fibrosis); ci 1 (<25% fibrosis); ci 2 (25–50% fibrosis); and ci 3 (>50% fibrosis). Concomitantly, other relevant Banff subscores were recorded to comprehensively characterize renal pathology, including the tubular atrophy score (ct: 0–3, corresponding to 0, <25%, 25–50%, and >50% tubular atrophy, respectively) and the interstitial inflammation score (ti: 0–3, indicating no, mild, moderate, and severe interstitial inflammatory cell infiltration, respectively). These Banff subscores were determined based on evaluations of Masson’s trichrome-stained and H&E-stained sections.

Statistical analysis

The statistical analyses were performed using the software SPSS 26.0 (IBM Corp., Armonk, NY, USA). The continuous variables with a normal distribution were expressed as the mean ± standard deviation (mean ± SD), and compared between groups using the independent samples t-test. Non-normally distributed data were analyzed using the Mann-Whitney U test. Categorical variables were reported as the count (percentage) [n (%)], and compared using the χ² test. A multivariate analysis of variance (MANOVA) was employed to compare continuous variables across multiple groups. The diagnostic performance of the viscosity parameters was evaluated by a receiver operating characteristic (ROC) curve analysis, which yielded the sensitivity, specificity, and area under the curve (AUC) with the 95% confidence interval (CI). To determine the best cutoff value, we calculated the Youden index (J = sensitivity + specificity − 1) for each point on the ROC curve. The value corresponding to the maximum Youden index was selected as the optimal cutoff, as it represents the best balance between sensitivity and specificity. Spearman’s rank correlation was used to assess the relationship between the renal viscoelastic parameters and histopathological grading. All statistical tests were two-tailed, and a P value <0.05 was considered statistically significant.

Results

Baseline characteristics of study participants

From September 2024 to March 2025, a total of 127 patients (age range, 14–91 years; mean age: 50.81±17.12 years) who met the inclusion criteria were prospectively enrolled in the study, as were 84 healthy volunteers (age range, 21–73 years; mean age: 40.81±10.77 years) who served as the HCs. The participants were stratified into six groups based on CKD stage: group 0 (normal controls, n=84), group 1 (CKD G1, n=35), group 2 (CKD G2, n=30), group 3 (CKD G3, n=19), group 4 (CKD G4, n=14), and group 5 (CKD G5, n=29).

As detailed in Table 1, significant intergroup differences (all P<0.001) were observed between the CKD groups and control groups in terms of age, hemoglobin, serum albumin, renal function marker (blood urea nitrogen, BUN), serum calcium, and glycated hemoglobin (HbA1c). No statistically significant differences were detected between the CKD groups and control groups in terms of body mass index (BMI, P=0.58) or gender (P=0.34). Notably, in the present study, the mean age of the CKD group was higher than that of the control group (50.81±17.12 vs. 40.81±10.77 years, P<0.001). Given that the CKD group had a higher mean age, there is a possibility that age-related confounding factors influenced these observed differences. Although we have analyzed and reported the differences in variables between the two groups, the potential impact of this age-related bias on our findings cannot be completely ruled out. Additional laboratory parameters are presented in the Table S1 for comprehensive reference.

Comparison of renal ultrasound and viscoelastic parameters between control and CKD groups

The results of the comparison of conventional renal ultrasound and viscoelastic parameters between the control group and the CKD group are displayed in Table 2. The bilateral kidney lengths of the CKD group (left kidney: 9.69±1.35 cm; right kidney: 9.56±1.32 cm) were significantly shorter than those of the control group (left kidney: 10.48±0.65 cm; right kidney: 10.34±0.57 cm) (all P<0.001), indicating possible renal atrophy in CKD patients. The renal elastic modulus (left kidney: 5.85±1.09 kPa; right kidney: 5.95±1.05 kPa) and viscosity values (left kidney: 2.03±0.29 Pa·s; right kidney: 2.03±0.29 Pa·s) of the CKD group were significantly higher than those of the control group (elastic modulus: left kidney 5.26±0.27 kPa, right kidney 5.31±0.29 kPa; viscosity: left kidney 1.61±0.03 Pa·s, right kidney 1.62±0.05 Pa·s) (all P<0.001), suggesting increased renal tissue stiffness and altered viscous properties in the CKD patients. Further, the differences in the bilateral kidney parameters (length, elasticity, and viscosity) between the CKD group and control group showed consistent trends. The elevation of these parameters may partially reflect fibrosis or inflammatory activity associated with CKD progression.

Relationship between ultrasound viscosity and CKD stages

As detailed in Table 3, the viscosity values demonstrated a stepwise elevation with advancing CKD stages. More specifically, right kidney viscosity increased from stage 1 (1.71±0.11 Pa·s) to stage 5 (2.36±0.21 Pa·s), showing highly significant intergroup differences (MANOVA: F=316.48, P<0.001), whereas left kidney viscosity similarly progressed from stage 1 (1.72±0.13 Pa·s) to stage 5 (2.33±0.25 Pa·s) (MANOVA: F=238.93, P<0.001). Significant differences in viscosity were observed between the adjacent CKD stages for both kidneys (all P<0.05), except between stage 4 and stage 5 where no statistically significant difference was detected (left kidney: P=0.87; right kidney: P=0.74), indicating the potential stabilization of viscosity values in ESRD. The results of the comparative analysis of the renal viscoelastic parameters of the CKD patients and HCs are presented in Figure 2.

Figure 2 Comparison of renal viscoelastic properties between CKD and normal kidneys. (A) CKD case. The mean stiffness measured by shear wave elasticity was 5.68 kPa. The mean viscosity coefficient measured by viscoelasticity was 1.94 Pa·s. (B) Healthy control case. The mean stiffness measured by shear wave elasticity was 4.74 kPa. The mean viscosity coefficient measured by viscoelasticity was 1.53 Pa·s. CKD, chronic kidney disease; SD, standard deviation; STE, sound touch elastography.

Diagnostic performance of ultrasound viscosity in CKD

The diagnostic efficacy analysis of the ultrasound viscoelastic parameters for CKD showed that the renal viscosity parameter (Vi) exhibited outstanding diagnostic value. As Figure 3 shows, the mean viscosity of the right kidney showed excellent diagnostic accuracy, with an AUC of the ROC curve of 0.95 (95% CI: 0.92–0.99). At the optimal cut-off value of 1.66 Pa·s, it had a sensitivity and specificity of 94.4% and 96.2%, respectively. Similarly, the mean viscosity of the left kidney demonstrated superior diagnostic performance, with an AUC of 0.95 (95% CI: 0.92–0.99). At the cut-off value of 1.67 Pa·s, it achieved a sensitivity of 90.5% and specificity of 97.4%. To address potential concerns about the lack of separate cut-offs in Figure 3, we emphasize that the unified threshold of 1.67 Pa·s was chosen based on the left kidney’s biopsy-confirmed data. The nearly identical AUCs (right 0.95 vs. left 0.95) and comparable sensitivity/specificity values validate that this cut-off is biologically plausible for bilateral assessment, considering the systemic nature of CKD. Clinically, applying a single threshold simplifies decision-making and aligns with standard renal biopsy practice, where unilateral sampling is routine. Conversely, the diagnostic efficacy of the elastic modulus parameters was significantly lower. The mean elastic modulus of the right kidney had an AUC of 0.73 (95% CI: 0.67–0.80). At the cut-off value of 5.57 kPa, it had a sensitivity and specificity of only 57.9% and 88.5%, respectively. The diagnostic performance of the mean elastic modulus of the left kidney was even less satisfactory (AUC, 0.69, 95% CI: 0.62–0.76). At the cut-off value of 5.46 kPa, it had a sensitivity and specificity of only 57.1% and 80.8%, respectively.

Figure 3 ROC analysis of renal viscoelastic parameters for CKD diagnosis. CKD, chronic kidney disease; E mean, the mean of stiffness value; ROC, receiver operating characteristic; Vi mean, the mean of viscosity coefficient.

Correlation between viscosity and left kidney pathological grading

Among the 127 enrolled CKD patients, 49 (38.6%) underwent percutaneous left renal biopsy for clinical indications within 3 months prior to ultrasound examination, forming the histopathological correlation cohort. The biopsy specimens were graded as follows: 25 cases, grade 1 (mild fibrosis); 11 cases, grade 2 (moderate fibrosis); and 13 cases, grade 3 (severe fibrosis). The Spearman correlation analysis revealed a significant positive correlation between left kidney viscosity and pathological grading (r=0.891, P<0.001), such that the viscosity values progressively increased as fibrosis severity increased. As shown in Table 4, the pairwise comparisons revealed statistically significant differences in the viscoelastic values between all groups, such that grade 1 group (mild) showing significantly lower values than grade 3 group (severe), whereas the differences between grades 1–2 and grades 2–3 had moderate effect sizes. The viscosity parameters increased stepwise with pathological severity.

Discussion

This study systematically compared renal ultrasound characteristics between CKD patients and HCs, yielding three key findings. First, the CKD group had significantly shorter bilateral kidney lengths (a reduction of approximately 0.8–0.9 cm compared to the controls), consistent with renal atrophy in CKD progression. Previous studies have reported that a kidney length ≤8 cm is strongly correlated with renal failure (47), whereas reduced cortical thickness (normally 7–10 mm) from the mid-pole boundary to the medullary pyramid base indicates progressive nephropathy or a declining eGFR (13,48,49). However, kidney length as a traditional marker shows limited sensitivity in early CKD diagnosis (our study found significant differences only in advanced stages). Similarly, Leong et al. (33) found that SWE outperformed conventional length/cortical thickness measurements for CKD detection (47). Second, our ultrasound viscoelastic imaging revealed that the performance of elasticity parameters was limited in CKD staging (left kidney AUC =0.69; right kidney AUC =0.73), with cut-off values of 5.46 kPa (left) and 5.57 kPa (right). These results differ from those of previous studies. Although Hwang et al.’s meta-analysis (50) validated the use of acoustic radiation force impulse in renal stiffness assessment, the reported cut-off values vary widely from 5.30 kPa [Samir et al. (27)] to 22.95 kPa [Radulescu et al. (28)]. Such discrepancies may stem from population heterogeneity (non-transplanted vs. transplant kidneys), renal anisotropy, or a lack of standardized protocols. Notably, although some studies (51-53) have reported increased stiffness in transplant kidneys with CKD progression, and Syversveen et al. (54) linked stiffness to the eGFR, Maralescu et al.’s recent work (55) highlights potential inaccuracies due to cortical reverberation artifacts or anisotropy. These inconsistencies underscore the challenges of conventional elastography in CKD evaluation (47,56). Third, this was the first study to show that renal viscosity parameters exhibit significant changes even in early CKD and have superior diagnostic efficacy (AUC =0.95) compared to elasticity measurements (AUC =0.73). At the optimal cut-off (right kidney viscosity =1.66 Pa·s), the sensitivity and specificity exceeded 90%, whereas the AUC of previous SWE-based study was only 76.4% for renal fibrosis (18). This aligns with liver fibrosis research (57) that shear wave viscosity can be used to effectively identify inflammation/fibrosis in non-alcoholic fatty liver disease. Our findings suggest that viscosity may be a more sensitive biomarker than elasticity for CKD prediction.

Similar to Maralescu et al. (56), we found a significant positive correlation between the eGFR and viscosity measurements. Notably, the non-invasive assessment of tissue viscosity remains relatively unexplored. The superior diagnostic performance of viscosity parameters likely stems from their dual responsiveness to both fibrotic and inflammatory processes: fibrosis-mediated increases in tissue stiffness through enhanced collagen cross-linking, and inflammation-induced alterations in rheological properties due to cellular infiltration (58,59). This dual mechanism suggests that viscosity measurements may provide a more comprehensive assessment of CKD progression than elasticity parameters alone.

Using the optimal cut-off value of 1.66 Pa·s, viscosity assessment could significantly enhance clinical decision-making by prioritizing viscoelastic examinations for suspected CKD cases. Using ultrasound viscoelastic imaging, this study was the first to show that left renal viscosity has a strong positive correlation with pathological grading (Spearman’s r=0.82, P<0.001) and exhibits exceptional diagnostic accuracy for CKD (AUC =0.95). Further, the bilateral concordance in the elevated elasticity and viscosity values suggests coexisting fibrotic and inflammatory pathological states. These findings are consistent with established renal pathophysiology, where systemic pathological processes in CKD (e.g., chronic inflammation and metabolic disturbances) lead to synchronous bilateral renal fibrosis, despite potential hemodynamic differences due to anatomical variation (60). The inflammatory response initiates renal injury, whereas persistent inflammation ultimately promotes fibrotic progression. Compared to renal biopsy, ultrasound-based viscosity assessment has a number of distinct clinical advantages, including a prompt result, a non-invasive nature, excellent reproducibility (intraclass correlation coefficient >0.90), high diagnostic accuracy, and consistent bilateral performance (AUCs >0.95 for both kidneys). The strong diagnostic performance of STVi is particularly relevant given that renal fibrosis is a spatially heterogeneous, patchy process (11). Although fibrosis manifests as a patchy process, our STVi technique, which utilizes a large ROI to sample the parenchyma, does not target individual foci but rather quantifies the integrated, macroscopic biomechanical consequence of the global disease burden. These features significantly enhance its potential for clinical application in CKD management.

This study provides the first systematic characterization of progressive changes in renal viscosity parameters across CKD stages, offering new insights into disease pathophysiology. From stage 1 to stage 5 CKD, we observed significant stepwise increases in both right kidney viscosity (1.71±0.11 to 2.36±0.21 Pa·s) and left kidney viscosity (1.72±0.13 to 2.33±0.25 Pa·s), with the MANOVA demonstrating remarkable statistical significance (F=316.48 and 238.93, respectively, both P<0.001). These findings align precisely with established pathological mechanisms: immune complex deposition-induced glomerulonephritis and interstitial inflammation, which are characterized by mesangial cell proliferation and inflammatory cell infiltration (61,62), directly contribute to increased renal parenchymal elasticity and viscosity. The stage-dependent viscosity progression mirrors the underlying disease activity, and each CKD stage represents a distinct phase of renal structural deterioration. Of particular interest was the plateau observed between stages 4 and 5 (left kidney: P=0.87; right kidney: P=0.74). This “ceiling effect” likely reflects unique pathological conditions in ESKD.

Multiple studies (58,59) have shown that inflammatory cell infiltration, narrowed interstitial spaces, and blood flow stasis increase intra-tissue pressure and consequently viscosity. However, when fibrotic remodeling reaches its limit and a dynamic equilibrium establishes between necrotic and viable tissue, this progression may stabilize. This process is analogous to the scar stabilization observed in advanced cirrhosis. Supporting evidence from hepatic studies shows that inflammatory necrosis significantly increases dispersion slope values in liver tissue (63,64). Similarly, recent renal transplant research found that patients with post-transplant acute kidney injury had higher dispersion coefficients, with overall inflammatory grade correlating with tissue dispersion values (43). These parallel observations across organs confirm that inflammatory processes fundamentally alter the physical properties of tissue (63,65,66) and serve as critical drivers of fibrotic progression (67).

These findings have important implications for clinical practice. Notably, viscosity parameters can serve as objective imaging biomarkers for CKD staging, and have shown particular advantages in distinguishing between stages 1 to 3. The plateau phenomenon suggests a potential stabilization of pathological changes in ESRD, which has significant implications for treatment timing. The stepwise increase in viscosity parameters reflects the synergistic effects of extracellular matrix deposition (collagen cross-linking increasing tissue stiffness) and chronic inflammation (inflammatory cell infiltration altering rheological properties). The high consistency of changes between bilateral kidneys confirms the characteristic bilateral renal involvement in CKD.

Compared with conventional elastic modulus measurements, viscosity parameters provide a more comprehensive assessment of tissue rheological properties, primarily due to their precise ability to capture viscoelastic characteristics (20). From a biomechanical perspective, viscosity parameters more accurately characterize the overall mechanical behavior of complex biological tissues during mechanical wave propagation, which is particularly valuable for early identification of inflammation-dominant CKD such as diabetic nephropathy. Thus, viscosity is a more reliable biomarker for evaluating renal pathology (20).

The end-stage plateau phenomenon suggests that more aggressive interventions should be considered for stage 4 patients, whereas treatment expectations may need to be adjusted for stage 5 patients.

Renal pathological studies demonstrate that immune-mediated injury mechanisms play a key role in glomerular disease progression. When circulating immune complexes deposit in glomeruli, they trigger a cascade of reactions, including mesangial expansion, endothelial cell activation, and podocyte foot process effacement (61). These pathological changes are typically accompanied by significant inflammatory cell infiltration and extracellular matrix remodeling, ultimately leading to glomerulosclerosis and interstitial fibrosis (62).

In terms of diagnostic techniques, although the STVi cannot yet match the precision of histopathological examination, its dynamic monitoring capability shows unique clinical potential. Serial viscoelastic parameter measurements enable clinicians to better track disease progression and provide objective evidence for personalized treatment plans. Dynamic changes in viscoelastic parameters can offer crucial reference information, which may be particularly useful in deciding whether renal biopsy is necessary (51,52,68). Another study (69) demonstrated that STVi can accurately identify stiffness changes associated with the eGFR in renal allografts.

This study yielded significant findings; however, it also has several important limitations that should be acknowledged. First, this study employed an unmatched case-control design with a ratio of 1:0.66 (127 cases to 84 controls). Although this strategy optimized resource utilization, it carries potential risks of residual confounding. Second, the research design carries inherent selection bias. As a single-center prospective study, we excluded obese patients (who might have compromised acoustic window penetration), which might limit the generalizability of our results. Third, the CKD group in this study had a higher mean age, which might have introduced aging-related confounding factors that could influence the results. Furthermore, the influence of variations in urinary perfusion and intratubular hydraulic pressure was not directly measured or controlled for. The measured viscoelastic parameters should therefore be interpreted as composite values. Besides, a key limitation of this study is the lack of albuminuria/proteinuria data, which prevented exploration of their correlations with renal viscoelastic parameters (viscosity, elasticity) and potential enhancement of STVi’s utility for early CKD detection. Future studies should integrate these data with longitudinal follow-up to address this gap. Due to practical constraints in clinical workflow, we were unable to ensure precise spatial correspondence between ultrasound measurement ROIs and the exact sites of renal biopsy. Although biopsies were preferentially obtained from the lower pole of the left kidney, not all elastographic measurements were acquired from identical anatomical locations. This mismatch introduces potential sampling variability, as local differences in tissue composition could influence viscoelastic parameters. In addition, due to the fundamental technical resolution of current STVi technology, our standardized ROI inevitably encompassed both the renal cortex and medulla. This provides a composite viscosity value for the entire parenchyma rather than a compartment-specific measurement. Future technological refinements aimed at layer-specific viscoelastic analysis would be invaluable. Lastly, the current study did not perform stratified analyses by etiology or systematically evaluate the discriminative capacity of viscoelastic imaging for various pathological types (23). Future research should prioritize multicenter collaborations to expand sample sizes and develop more robust standardized measurement protocols.

Conclusions

This study confirmed that STVi, particularly viscosity measurements, represent novel and reliable biomarkers for evaluating CKD progression. The viscosity parameters showed superior diagnostic performance compared to conventional US indicators, primarily by providing a unique ability to reflect the extent of renal fibrosis, which enables early disease detection. We established clinically applicable cut-off values that demonstrated excellent diagnostic accuracy and reproducibility. Importantly, we identified characteristic patterns of viscosity changes across CKD progression (i.e., a stepwise increase through early-to-advanced stages followed by a plateau phenomenon in ESRD). These findings provide valuable references for clinical staging and therapeutic decision making. Given its non-invasive nature, reproducibility, and early diagnostic value, renal viscoelastic imaging shows particular promise for high-risk population screening, disease progression monitoring, and treatment response evaluation, and may become an important adjunct in CKD management systems. Future studies should focus on measurement standardization and validation across diverse populations to further facilitate the clinical application of this technology.

Acknowledgments

The authors utilized standard language tools within Microsoft Word for proofreading during the preparation of this manuscript. The scientific content and intellectual contribution remain solely the responsibility of the authors.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1526/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1526/dss

Funding: This work was supported by funding from the Key Project of Zhejiang Provincial Natural Science Foundation Joint Fund (No. LKLZ25H180001 to J.C.), the Zhejiang University Horizontal Science and Technology Project (No. 2021-KYY-518053-0036 to J.C.), the National Medical Equipment Promotion Program funded by MIIT (No. 2024TGYY11 to J.C.), and the Education Department Project of Zhejiang Province, China (No. Y202353553 to X.F.).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1526/coif). J.P. is from Shenzhen Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, China. X.F. reports funding support from the Education Department Project of Zhejiang Province, China (No. Y202353553). J.C. reports funding support from the Key Project of Zhejiang Provincial Natural Science Foundation Joint Fund (No. LKLZ25H180001), the Zhejiang University Horizontal Science and Technology Project (No. 2021-KYY-518053-0036), and the National Medical Equipment Promotion Program funded by MIIT (No. 2024TGYY11). The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This prospective cross-sectional study was approved by the Ethics Committee of the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University (No. K2025134), and written informed consent was obtained from all participants or their legal guardians. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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