Intravoxel incoherent motion diffusion-weighted imaging for the assessment of renal injury in cirrhotic patients

Introduction

Kidney injury is a prevalent and severe complication of decompensated cirrhosis, affecting up to 30–50% of cirrhotic patients (1). Acute kidney injury in these patients can significantly worsen prognosis, with the mortality rate escalating to as high as 44% within 30 days of onset (2). Additionally, acute kidney injury often progresses to chronic kidney disease and irreversible renal dysfunction, which further complicates cirrhosis management and increases the risk of hepatic decompensation and mortality (3,4). Early detection of kidney injury, therefore, is crucial for improving clinical outcomes through timely intervention and personalized management strategies.

Currently, serum creatinine serves as the primary clinical parameter for diagnosing acute kidney injury in patients with cirrhosis (5). However, serum creatinine has well-documented limitations in cirrhosis due to impaired creatine production, reduced muscle mass, and renal tubular dysfunction, all of which can lead to underestimation of renal injury severity (6,7). Moreover, hyperbilirubinemia, a common complication of cirrhosis, interferes with serum creatinine measurements when calorimetric methods are used, further reducing its diagnostic reliability (6). These inherent limitations underscore the need for a non-invasive, reliable, and sensitive imaging technique to evaluate renal injury, particularly in its early stages, before significant serum creatinine changes become evident.

Currently, alternative imaging modalities such as ultrasonography, arterial spin labeling, T1-mapping magnetic resonance imaging (MRI), blood oxygenation level-dependent MRI, and traditional MRI have been explored for assessing renal function. Ultrasonic point-shear wave elastography has assessed renal stiffness and duplex sonography has evaluated renal hemodynamics in cirrhotic patients (8,9). However, ultrasound results are susceptible to the subjective factors of the operators, and factors such as the patient’s respiration, positional changes, and the thickness of fat surrounding the kidney may interfere with the results (10). Arterial spin labeling, an MRI-based perfusion technique, can measure renal blood flow without contrast agents and has shown promise in evaluating renal perfusion in various conditions (11-13). However, arterial spin labeling’s sensitivity to motion artifacts and limited ability to differentiate microvascular perfusion from intrinsic tissue diffusion remain significant drawbacks, especially in cirrhotic patients prone to ascites or respiratory variability (14,15). T1-mapping MRI is utilized to assess water content and the degree of fibrosis across various renal diseases, yet it possesses a limitation in evaluating renal perfusion and microvascular alterations (16,17). The blood oxygenation level-dependent technique response exhibits high sensitivity to tissue hypoxia, enabling an effective evaluation of tissue oxygenation status. However, the blood oxygenation level-dependent technique is similarly constrained by its inability to offer quantitative assessments of renal perfusion or microvascular changes (18). Traditional MRI techniques, such as diffusion-weighted imaging (DWI), have been used to assess renal diffusion properties but fail to separate microvascular perfusion effects from tissue diffusivity (19).

In contrast, intravoxel incoherent motion (IVIM) DWI integrates perfusion and diffusion metrics by decoupling pseudo-diffusion (reflecting microvascular perfusion) and true diffusion (reflecting intrinsic water mobility), offering a comprehensive evaluation of renal microvascular and parenchymal changes (20). This makes IVIM particularly well-suited for capturing the subtle early changes in renal perfusion and diffusion often seen in cirrhotic patients, which may not yet be detectable with other imaging modalities or serum creatinine-based measures. IVIM DWI has been applied to various renal pathologies with promising results. In chronic kidney disease, Mao et al. (21) demonstrated that the perfusion fraction (f) derived from IVIM DWI correlates more strongly with renal function than estimated glomerular filtration rate, enabling earlier detection of renal dysfunction even when estimated glomerular filtration rate is normal. Similarly, Deng et al. (22) observed lower diffusion coefficient (ADC_slow) and higher f values in diabetic nephropathy patients with preserved renal function, suggesting early changes in renal microcirculation and restricted water movement, serving as imaging markers for early renal injury in diabetics. Moreover, in an acute kidney injury rat model induced by severe acute pancreatitis, IVIM-derived parameters correlated strongly with renal histopathology scores, with cortical pseudo-diffusion coefficient (ADC_fast) achieving an area under the curve of 0.950 for acute kidney injury diagnosis (23). Despite these findings, the efficacy of IVIM DWI in assessing renal injury in cirrhotic patients remains unexplored.

This study aims to evaluate the feasibility of using IVIM DWI to detect early renal perfusion and diffusion changes in cirrhotic patients. Specifically, we seek to explore the relationships between renal IVIM-derived parameters and the progressive severity of liver cirrhosis, as defined by the Child-Pugh classification. We hypothesize that IVIM DWI can offer unique insights into the pathophysiological changes associated with cirrhotic renal injury, enabling earlier detection and more accurate assessment than conventional biomarkers. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2918/rc).

Methods

Subjects

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the institutional review board of Chongqing Hospital of Traditional Chinese Medicine (No. 2021-ky-68) and informed consent was taken from all the patients. Between February 2022 and February 2023, a cohort of 64 hospitalized patients with confirmed cirrhosis was enrolled. The inclusion criteria were: (I) hematologic and radiologic evidence of advanced liver disease, defined as a platelet count <100,000/µL combined with abdominal cross-sectional imaging [computed tomography (CT)/MRI] revealing nodular liver surface, splenomegaly, or other cirrhosis-associated morphological changes; (II) clinical manifestations of portal hypertension, including ascites, esophageal/gastric varices, or hepatic encephalopathy; and (III) optional histopathologic confirmation via liver biopsy when feasible, with biopsy findings consistent with cirrhosis (24,25). The exclusion criteria were: (I) primary kidney diseases such as nephrotic syndrome and glomerular nephritis; hypertension, diabetic mellitus, or gout disease; (II) serious systemic or organic lesions; (III) use of medications such as diuretics, angiotensin-converting enzyme inhibitors, or angiotensin receptor blockers before MRI examination; (IV) patients with malignant tumors; and (V) poor imaging.

During the same study period, 34 healthy controls were enrolled, adhering to the following composite criteria: (I) absence of prior abdominal pathology (excluding gastrointestinal, hepatobiliary, or other abdominal organ disorders); (II) normal renal morphology confirmed by abdominal imaging (CT/MRI demonstrating bilaterally intact kidneys without structural anomalies); and (III) exclusion of clinically significant comorbidities (including diabetes mellitus, hypertension, cardiovascular diseases, or chronic renal conditions).

Image data acquisition

All participants underwent standardized abdominal MRI and IVIM on a 3.0-T MRI system (Signa Architect, GE Healthcare, Milwaukee, WI, USA) equipped with an adaptive receive coil. Subjects fasted for 6–8 hours prior to scanning. T1-weighted and T2-weighted imaging were performed as part of the routine clinical assessment, while IVIM imaging was specifically performed using multiple sensitivity encoding with respiratory gating and parallel acquisition. The IVIM sequence parameters included repetition time/echo time =5,000 ms/75.5 ms; field of view =36×36 cm²; matrix =130×130; slice thickness =3.6 mm; slice spacing =0.5 mm; slices =18; b-values =0, 10, 20, 50, 100, 200, 400, 600, 800, and 1,000 s/mm²; and the number of excitation =2, 2, 2, 2, 1, 1, 1, 1, 2, and 2 and diffusion sensitization applied in three orthogonal directions.

Image data analysis and processing

Post-processing of IVIM images was conducted on the Advanced Workstation platform (version 4.6, GE Healthcare) using multi-b-value apparent diffusion coefficient analysis software. Two radiologists, each with 5–6 years of specialized experience in abdominal MRI, independently reviewed IVIM images, blinded to laboratory data and clinical outcomes. Measurements were performed separately on both kidneys. Regions of interest (ROI) were manually delineated on IVIM images acquired at b-value =10 s/mm². As shown in Figure 1, three sections closest to the renal hilum were selected for both the left and right kidneys, and a manually drawn ROI, with an area of 5–9 cm², was created to encompass the entire renal cortex. Additionally, three slices from the left and right kidneys that were closest to the renal hilum. Given the small size of the renal medulla, three elliptical ROIs with an area of 0.2–0.4 cm² each were placed on each slice to minimize partial volume effects and confounding signals (26,27). Finalized ROIs were transferred to IVIM-derived quantitative parameter maps to extract mean ADC_slow, ADC_fast, and f values. The average of these measurements from both observers was computed for subsequent statistical analysis. All parameters were derived using the Bihan bi-exponential model, which decomposes IVIM signals into perfusion-related and diffusion-dominated components (20):

S(b)=S(0)[fexp(−bADCfast)+(1−f)exp(−bADCslow)][1]

Figure 1 ROIs were delineated in the IVIM images with a b-value of 10 s/mm². (A) ROI 1 and ROI 2 correspond to the freely hand-drawn ROIs (each with an area of 5–9 cm²) on the right and left kidneys, respectively, at the level of the renal hilum, both completely covering the renal cortex. (B) ROI 1–3 delineate the renal medulla region of the right kidney, while ROI 4–6 delineate the renal medulla region of the left kidney, with each set containing three manually placed elliptical ROIs (each with an area of 0.2–0.4 cm²). IVIM, intravoxel incoherent motion; ROI, region of interest.

In the Bihan bi-exponential model, b-value quantifies the diffusion-weighting gradient sensitivity. ADC_slow reflects water diffusion constrained by tissue cellularity, while ADC_fast captures perfusion-driven microdiffusion within the microcirculation. The f value, constrained to [0, 1], denotes the microvascular volume fraction contributing to diffusion signal decay.

We employed a segmented fitting approach for IVIM data processing. High b-value fitting: utilizing high b-value data (typically in the range where perfusion contributions are considered minimal, such as b≥200 s/mm²), the ADC_slow parameter is initially fitted independently. At this stage, signal decay is primarily dominated by pure diffusion effects. Low b-value fitting: after fixing the ADC_slow obtained from high b-value fitting, the remaining components of the biexponential model are fitted using low b-value data (covering the lower range of b-values, such as b<200 s/mm²) to isolate the ADC_fast and f parameters, thereby obtaining values that reflect microcirculatory perfusion. The segmented fitting approach yields more stable and robust parameter estimates under low signal-to-noise ratio conditions, reducing the likelihood of interference from different perfusion effects on pure diffusion parameters. This method has been applied in multiple preliminary studies and has been demonstrated to have significant advantages in accurately distinguishing between diffusion and perfusion components (28-30).

Cirrhotic patients were stratified into Child-Pugh classes A (5–6 points), B (7–9 points), and C (10–15 points) based on the standardized scoring system, which evaluates hepatic dysfunction severity through bilirubin, albumin, coagulation, ascites, and encephalopathy parameters (25).

Statistical analysis

All statistical analyses were conducted using SPSS for Windows (version 22.0, Chicago, IL, USA). Data normality was assessed via the Shapiro-Wilk test, followed by Levene’s test to evaluate homogeneity of variances across groups. Statistical significance was set at P<0.05 (two-tailed). The Student’s t-test was used to compare the age difference between the cirrhosis group and the control group. The Chi-squared test was employed to compare the gender composition. Using multivariate regression analysis to explore the influence of age and gender on IVIM-derived parameters. The paired t-test (for normally distributed data) or Wilcoxon signed-rank test (for non-normally distributed data) was used to compare IVIM-derived renal parameters between the right and left kidneys. The Student’s t-test (for normally distributed data) or Mann-Whitney U test (for non-normally distributed data) was applied to compare IVIM-derived renal parameters between the cirrhotic and control groups. Spearman’s rank correlation was employed to evaluate the relationship between IVIM-derived renal parameters and hepatic function severity, as stratified by Child-Pugh classification. The Kruskal-Wallis H test was conducted to compare IVIM-derived renal parameters across Child-Pugh classification in cirrhotic patients, followed by Bonferroni-corrected pairwise comparisons to identify specific group differences if the omnibus test was significant (P<0.05).

Results

Demographic and clinical features

Fourteen patients were excluded from the study due to the following reasons: four with poor imaging, four with incomplete images, and six with malignant tumors. Finally, 64 cirrhotic patients and 30 normal subjects were enrolled in the analysis. The details are shown in Figure 2.

Figure 2 Study flow diagram. DWI, diffusion-weighted imaging; IVIM, intravoxel incoherent motion; MRI, magnetic resonance imaging.

Table 1 summarizes the clinical characteristics of the subjects. The cirrhotic cohort comprised 64 patients (49 males, 15 females; mean age ± standard deviation, 54±8.9 years; range, 44–72 years). Based on the Child-Pugh classification (25), 68.75% (44/64) were classified as class A, 26.56% (17/64) as class B, and 4.69% (3/64) as class C. The predominant etiology of cirrhosis was hepatitis B virus infection (82.81%, 53/64), followed by alcohol-related liver disease (6.25%, 4/64) and autoimmune hepatitis (6.25%, 4/64), with hepatitis C virus accounting for the remaining 4.69% (3/64).

The control group comprised 30 participants (16 males, 14 females; mean age ± standard deviation, 49.9±12.3 years; range, 30–73 years). Abdominal MRI revealed no abnormalities in 22 subjects (73.3%), 6 subjects (20.0%) with hepatic cysts, and 2 subjects (6.7%) with splenic cysts.

The multivariate regression analysis revealed that age and gender had no significant impact on the IVIM parameters, with all P values greater than 0.05, as shown in Table 2.

Comparison of the IVIM-derived parameters between the right and left kidneys in the control group

As shown in Table 3 and Figure 3, there were no significant differences in the IVIM-derived parameters (ADC_slow, ADC_fast, and f) between the left and right kidneys in the control group. The average measurements of both sides of each participant’s kidney were used for the final analysis.

Figure 3 The box-and-whisker plots, including individual data points, displaying the comparison of ADC_slow (A,D), ADC_fast (B,E), and f (C,F) values between the renal cortex and medulla in both the right and left kidneys within the control group. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction.

Figure 4A-4D presents MRI findings from a representative control group subject.

Figure 4 Axial IVIM imaging and parameter maps from a 50-year-old healthy female subject. (A) IVIM image with a b-value of 10 s/mm²; (B) IVIM-derived ADC_slow map; (C) ADC_fast map; (D) f map. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction; IVIM, intravoxel incoherent motion; RI, rainbow invert.

Comparison of the IVIM-derived renal cortical and medullary parameters between the cirrhotic and control groups

Figure 5A-5C demonstrates that cirrhotic patients exhibited significantly lower renal cortical ADC_fast and f values compared with controls (P=0.033 and 0.049, respectively), while ADC_slow showed no significant difference between the cirrhotic and control groups (P=0.846).

Figure 5 The box-and-whisker plots, incorporating individual data points, illustrating the comparison of (A-C) cortical and (D-F) medullary ADC_slow, ADC_fast, and f values between the control group and the cirrhotic group, respectively. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction.

Figure 5D-5F indicates that renal medullary ADC_fast was significantly reduced in cirrhotic patients compared with controls (P=0.043), while ADC_slow and f values showed no significant difference between the cirrhotic and control groups (P=0.638 and 0.173, respectively).

The detailed information is shown in Table 4.

The correlations between IVIM-derived renal cortical and medullary parameters and Child-Pugh-based hepatic function grades in cirrhotic patients

In the cirrhotic group, renal cortical ADC_fast demonstrated a significant inverse correlation with Child-Pugh classification (R=−0.406, P=0.001), whereas ADC_slow and f values showed no correlation (R=−0.03, P=0.817; R=−0.165, P=0.191, respectively) (Figure 6A-6C). Renal medullary ADC_fast exhibited a significant inverse correlation with Child-Pugh grades (R=−0.251, P=0.045), whereas ADC_slow and f values showed no correlation (R=−0.198, P=0.117; R=0.026, P=0.838, respectively) (Figure 6D-6F).

Figure 6 Correlations between IVIM-derived renal (A-C) cortical and (D-F) medullary parameters and Child-Pugh classification. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction; IVIM, intravoxel incoherent motion.

In cirrhotic patients, renal cortical ADC_fast was significantly elevated in Child-Pugh class A patients compared with classes B and C (P=0.032 and 0.019, respectively), with no difference between classes B and C (P=0.208). In contrast, ADC_slow and f values remained non-significant across hepatic function grades (P=0.934 and 0.285, respectively) (Figure 7A-7C). Renal medullary ADC_fast was significantly elevated in Child-Pugh class A patients compared with class B (P=0.017), with no differences between class A vs. C (P=0.052) or class B vs. C (P=0.448). In contrast, ADC_slow and f values showed no significant differences across hepatic function grades (P=0.444 and 0.811, respectively) (Figure 7D-7F). The detailed information is shown in Table 5.

Figure 7 The box-and-whisker plot with individual data points of the (A,D) ADC_slow, (B,E) ADC_fast, and (C,F) f values among different severity of cirrhotic according to the Child-Pugh classification. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction.

Figure 8A-8L illustrates representative cases of cirrhotic patients stratified by Child-Pugh classification (classes A, B, and C).

Figure 8 The axial IVIM images with a b-value of 10 s/mm² (A,E,I) and IVIM-derived ADC_slow (B,F,J), ADC_fast (C,G,K), and f (D,H,L) maps from three representative cirrhotic patients. (A-D) A 53-year-old female with liver cirrhosis classified as class A according to the Child-Pugh classification. (E-H) A 52-year-old man with liver cirrhosis classified as class B. (I-L) A 54-year-old man with liver cirrhosis classified as class C. ADC_fast, pseudo-diffusion coefficient; ADC_slow, diffusion coefficient; f, perfusion fraction; IVIM, intravoxel incoherent motion; RI, rainbow invert.

Discussion

In this study, IVIM DWI was employed to non-invasively assess early changes in renal injury among cirrhotic patients. The ADC_fast and f values, derived from IVIM measurements using the bi-exponential model, were calculated to evaluate the characteristics of tissue perfusion (20). The findings revealed that cirrhotic patients exhibited lower blood perfusion in both the renal cortex and medulla compared to normal subjects. As the severity of liver cirrhosis increased according to the Child-Pugh classification, renal perfusion further declined, emphasizing the potential of IVIM parameters to reflect the progression of renal injury.

In this study, the ADC_fast and f values of the renal cortex were significantly lower in cirrhotic patients compared to the control group. This aligns with previous findings from an arterial spin labeling perfusion study, which reported decreased renal cortical blood flow in cirrhotic patients (11). However, unlike arterial spin labeling, IVIM DWI integrates both perfusion and diffusion metrics, offering a more comprehensive assessment of renal microcirculatory perfusion and tissue diffusion properties (20,31). This advantage is particularly relevant in cirrhotic patients, who often present with ascites or respiratory variability, making arterial spin labeling prone to motion artifacts (14,15). Additionally, ADC_fast value in the renal medulla was also significantly reduced in cirrhotic patients, while f value showed a decreasing trend without reaching statistical significance. The findings suggest the sensitivity of IVIM-derived parameters, particularly ADC_fast, in detecting subtle renal microvascular changes that precede clinical manifestations. Patients with cirrhosis, due to portal hypertension and a hyperdynamic circulatory state, experience exacerbated splanchnic arterial vasodilation, which subsequently leads to a reduction in effective circulating blood volume. This change reflexively activates the renin-angiotensin-aldosterone system, resulting in inadequate cardiac output (32,33). Concurrently, factors such as hepatic inflammation, intestinal flora translocation, and concurrent infections can lead to the release of a large number of inflammatory factors and the development of endotoxemia (34-36). These pathological processes interfere with the normal function of renal microcirculation, thereby inducing renal functional impairment. Consequently, in this study, we observed decreases in both ADC_fast and f values, which reflect renal microcirculatory perfusion, further confirming the adverse effects of cirrhosis on renal microcirculation and function.

ADC_slow is generally considered to reflect the slower diffusion component within tissues, which is less influenced by perfusion and more affected by the intrinsic diffusion properties of the tissue (37). In the context of renal function, changes in ADC_slow are more likely to be associated with alterations in the tissue microstructure, such as fibrosis and inflammation, rather than changes in blood flow (27,38). In our study, there was no significant difference in ADC_slow between patients with cirrhosis and healthy controls, suggesting that the observed changes in renal function may be more closely related to perfusion alterations (as reflected by ADC_fast and f) rather than changes in the tissue microstructure that would affect ADC_slow. This finding is consistent with the pathophysiological mechanisms of renal dysfunction in cirrhosis, where a reduction in effective circulatory blood volume and activation of the renin-angiotensin-aldosterone system lead to changes in renal perfusion (32,33).

Our study demonstrated that ADC_fast values of both the renal cortex and medulla decreased as hepatic function deteriorated, based on the Child-Pugh classification. This correlation suggests that worsening hepatic function exacerbates renal hypoperfusion and microcirculatory dysfunction, likely due to hemodynamic disturbances, reduced effective circulating blood volume, and activation of the renin-angiotensin-aldosterone system (32,33). Inflammatory processes, such as endotoxemia induced by liver inflammation and intestinal microbiota translocation, further contribute to renal vascular endothelial dysfunction (34-36). However, the lack of significant differences between Child-Pugh B and C classes may be attributed to the small sample size of class C patients, highlighting the need for larger cohorts to validate these findings.

The f value indicates the proportion of diffusion influenced by microcirculation (20). Our study did not demonstrate any correlation between the f value of the renal cortex or medulla and hepatic function. This may be because, in cirrhotic patients, the f value of both the renal cortex and medulla is influenced by the overall diffusion effect, thereby obscuring any potential relationship with hepatic function.

When assessing renal injury in patients with cirrhosis, IVIM demonstrates significant advantages over arterial spin labeling, T1 mapping, and blood oxygenation level-dependent techniques. With a single imaging session, IVIM can acquire multiple quantitative parameters, comprehensively revealing renal microcirculation perfusion and water molecule diffusion status, and further indicating changes in tissue microstructure and the degree of fibrosis (20,39). By incorporating respiratory gating technology, IVIM eliminates the need for patients to hold their breath, significantly enhancing the convenience and comfort of the examination, especially for patients with cirrhosis in the decompensated stage. More importantly, IVIM can precisely capture early changes in renal microcirculation and restricted water movement in diabetic patients, even before significant abnormalities in renal function appear (22). This demonstrates the high sensitivity and accuracy of IVIM in detecting microscopic changes in the kidneys. Regarding renal injury in liver cirrhosis, previous study has predominantly focused on analyzing the differences in T1 value and renal blood flow among cirrhotic patients with varying renal functions (11). Animal experiments have delved into the pathological changes of the kidney, including assessing renal damage through Hematoxylin-Eosin staining, peritubular capillary density, Hypoxia-Inducible Factor-1α expression, as well as serum creatinine and blood urea nitrogen levels. Additionally, these studies have explored the correlations between these indicators and quantitative MRI parameters, such as renal blood flow and T2* value (18,40). However, it is noteworthy that to some extent, these studies have overlooked the direct and indirect impacts of liver function impairment on the kidney. Liver dysfunction can not only directly affect renal hemodynamics but also indirectly exacerbate renal injury through systemic metabolic alterations (32-36). This study is the first to employ IVIM to conduct an in-depth analysis of the impact of Child-Pugh classification on renal function in patients with cirrhosis, providing a new perspective for research in this field.

However, in this study, we did not compare IVIM-related parameters with clinical indicators such as creatinine clearance, serum creatinine, estimated glomerular filtration rate, and blood urea nitrogen. Despite attempting to collect these data from some patients, the information was incomplete due to lack of tests for certain indicators. For the available clinical indicators, most patients had normal serum creatinine, estimated glomerular filtration rate, and blood urea nitrogen levels. This may indicate that traditional indicators have insufficient sensitivity in detecting early renal impairment. Specifically, serum creatinine increases significantly only when glomerular filtration rate drops by over 50%, and is prone to interference from factors like age, gender, and muscle mass (6,7,41). Estimated glomerular filtration rate, reliant on serum creatinine formulas, can be erroneous in individuals with abnormal muscle mass or special populations (42). Blood urea nitrogen is significantly affected by non-renal factors such as high-protein diet, dehydration, infection, and gastrointestinal bleeding, leading to false-positive or false-negative results. Therefore, traditional clinical indicators mainly reflect overall changes in renal function and are difficult to capture early local or microscopic injuries (such as microcirculatory disturbances). In contrast, IVIM offers significant advantages. Its ADC_fast and f values can reflect abnormal blood flow perfusion, distinguish between renal cortex and medulla injuries, and provide spatial information. Being non-invasive and contrast-agent-free, IVIM is suitable for repeated examinations to assess treatment effects or disease progression. Previous studies have shown that IVIM parameters undergo notable changes in early stages of chronic kidney disease and acute kidney injury. For instance, Mao et al. (21). found that the f value correlates stronger with renal function than estimated glomerular filtration rate, and IVIM can detect renal dysfunction earlier, even when estimated glomerular filtration rate is normal. In acute kidney injury, a decrease in renal cortical ADC_fast value reflects reduced renal perfusion (43).

However, there are several limitations in this study that are worth noting. Firstly, IVIM parameters have limitations in accurately reflecting tissue diffusion and perfusion, due to factors like T2 relaxation time and multiple T2 compartments in tissues (44). Additionally, the previous research has shown that IVIM parameters exhibit a mutual constraining relationship, where changes in one parameter can affect the others, complicating interpretations (45). Despite these, IVIM parameters remain valuable as composite biomarkers, providing insights into tissue microstructure and perfusion changes, especially in situations where direct measurements are challenging. Secondly, in our study, since hepatitis B was the primary cause of cirrhosis, we did not explore the interference of etiologies on cirrhosis-related kidney injury. However, we are aware of the significance of other causes such as hepatitis C, alcoholic liver disease, and autoimmune liver diseases. In future research, we will pay greater attention to cirrhosis-related kidney injury caused by diverse etiologies and strive to incorporate a wider range of etiological types. Thirdly, there was an imbalance in gender and age distribution among patients, which may affect IVIM parameters. However, multivariate regression analysis showed no significant impact of age and gender (P>0.05). These results are exploratory due to sample size limitations, and future research will aim for a larger and more balanced sample. Finally, the number of patients with Child-Pugh C cirrhosis is relatively small. Due to the severity of their condition, recruitment poses significant challenges, which to some extent limits our sample size. Future research will focus on expanding the sample size, particularly for Child-Pugh C patients, to enhance representativeness and reliability.

Conclusions

IVIM DWI offers a non-invasive method to evaluate early alterations in renal injury among cirrhotic patients. Our findings indicate that renal blood perfusion is reduced in cirrhotic patients compared to healthy individuals, and this reduction correlates with the severity of liver cirrhosis according to the Child-Pugh classification.

Acknowledgments

The authors would like to express their deepest gratitude to the technicians who performed IVIM-MRI scans on all subjects in the department of radiology, Chongqing Hospital of Traditional Chinese Medicine, Chongqing, China.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2918/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2918/dss

Funding: This work was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission (No. KJQN202415136) and the Natural Science Foundation of Chongqing, China (No. CSTB2024NSCQ-MSX0230).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2024-2918/coif). R.H. reports that this research was funded by the Scientific and Technological Research Program of Chongqing Municipal Education Commission (No. KJQN202415136). Hua Yang reports that this research was funded by the Natural Science Foundation of Chongqing, China (No. CSTB2024NSCQ-MSX0230). L.N. is an employee of GE Healthcare, MR Research China, Beijing, China. 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 study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the institutional review board of Chongqing Hospital of Traditional Chinese Medicine (No. 2021-ky-68) and informed consent was taken from all the patients.

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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