Abstract
Background and objectives
Ultrasound-derived fat fraction (UDFF) is a novel, non-invasive, rapid, and cost-effective technology that assesses liver fat content in various hepatic diseases. Its use in evaluating hepatic steatosis in Wilson’s disease (WD) remains largely unexplored. This study aimed to verify the clinical utility and measurement consistency of UDFF in assessing hepatic steatosis in WD, investigate the relationship between BMI and the severity of hepatic steatosis in WD patients, and determine if UDFF is an effective indicator for this condition.
Methods
This retrospective study involved 89 patients diagnosed with WD. The demographic characteristics, body mass index (BMI), conventional ultrasound examination, liver shear wave elastography, and ultrasound-derived fat fraction (UDFF) detection data were collected and statistically analyzed. The degree of hepatic steatosis was evaluated using the visual scoring method known as the Hamaguchi score. The Bland-Altman plot was used to analyze the intra-observer and inter-observer consistency of UDFF measurements. The Spearman correlation analysis was conducted to explore the correlations among BMI, UDFF, and the Hamaguchi score. Additionally, confounding factors were included to analyze whether UDFF was an independent influencing factor for WD hepatic steatosis. The receiver operating characteristic (ROC) curve was utilized to determine the cutoff value of UDFF for diagnosing WD hepatic steatosis and its diagnostic efficacy.
Results
The Bland-Altman analysis showed bias values of 5.7% and 1.1% for intra-observer variability of a junior and a senior sonologist, respectively, and 14.9% for inter-observer variability. Univariate analysis showed no significant correlation between BMI and the Hamaguchi score (r = 0.08, P = 0.478). However, there was a positive correlation between UDFF and the Hamaguchi score (r = 0.71, P < 0.001). Multivariate analysis indicated a significant correlation between UDFF and WD hepatic steatosis, with a regression coefficient of 1.243, OR of 3.465, and 95% CI of 1.617–10.51 (P = 0.008). ROC curve analysis demonstrated that the optimal cutoff value of UDFF for diagnosing WD hepatic steatosis was 4.5%, with an AUROC of 0.80 (95% CI: 71 − 90%), sensitivity of 90%, and specificity of 80%.
Conclusion
The clinical operation of UDFF exhibits high repeatability. In patients with WD, there may be a paradoxical phenomenon where those with low or normal BMI co-exist with hepatic steatosis. UDFF can serve as a valuable tool for the quantitative assessment of WD hepatic steatosis. Our study broadens the clinical applications of UDFF.
Keywords: Wilson’s disease, Ultrasound-derived fat fraction, Hepatic steatosis, Liver parenchyma brightness, Hamaguchi’s score
Introduction
Wilson’s disease (WD) is a genetic disorder caused by mutations in the ATP7B gene [1–3], leading to excessive copper accumulation in organs such as the liver, brain, and kidneys. Hepatic steatosis is often one of the manifestations of early liver damage in WD [4, 5], which can progress to liver fibrosis, cirrhosis, or even liver failure, and may coexist with fibrosis. Early intervention has the potential to partially reverse hepatic steatosis and improve liver function.
Ultrasound, as a low-cost, non-invasive, and radiation-free imaging modality, is the first-line examination method for liver assessment in WD. Unlike liver biopsy, ultrasound can be repeatedly performed to monitor the degree of hepatic steatosis dynamically. However, in the early stages of hepatic steatosis, conventional B-mode ultrasound may have limited sensitivity due to subtle image changes. Ultrasound-derived fat fraction (UDFF) enables non-invasive quantification of liver fat content during routine abdominal ultrasound examinations.
Although previous studies have already demonstrated that UDFF exhibits high sensitivity and specificity in the detection of non-alcoholic fatty liver disease and is highly consistent with magnetic resonance imaging-proton density fat fraction (MRI-PDFF) [6–9], because the pathological mechanisms of WD are different from non-alcoholic fatty liver disease (NAFLD), these differences might lead to the situation where the accuracy and consistency of UDFF measurements in WD hepatic steatosis are different from those in the latter. Moreover, various factors such as fibrosis and metabolic status may influence the measurement of UDFF. Currently, there is still a lack of research reports on the application of this technique in the assessment of WD-related hepatic steatosis.
This study was designed to evaluate the operational repeatability of employing UDFF to gauge the hepatic fat content in patients with WD, both among and within groups of sonologists with varying years of experience. Specifically, it analyzed the correlations between UDFF, the characteristics of WD patients like BMI and the Hamaguchi score, and probed into the optimal cut-off value of UDFF for diagnosing hepatic steatosis in WD. The overarching aim of this study was to appraise the practicability and application value of UDFF, a novel ultrasonic detection technique, in the assessment of hepatic injury in WD.
Research methods
Study subjects
This retrospective study was conducted in accordance with the ethical guidelines of the Declaration of Helsinki and was approved by the hospital’s ethics review committee. Based on the inclusion criteria, an initial cohort of 115 patients diagnosed with WD who underwent UDFF examination between October 2023 and September 2024 was enrolled. After applying the exclusion criteria, a total of 89 patients were ultimately included in the study.
Inclusion criteria: (1) Patients diagnosed with WD according to WD diagnostic guidelines [10, 11]; (2) No concomitant viral hepatitis or autoimmune hepatitis; (3) No history of excessive alcohol consumption, defined as a weekly alcohol intake not exceeding 140 g for women and 210 g for men; (4) No rheumatic diseases that could lead to liver fibrosis.
Exclusion criteria: Patients were excluded if they met any of the following criteria: (1) Incomplete diagnostic information from UDFF, shear wave elastography, or conventional ultrasound; (2) Poor image quality of UDFF and shear wave elastography due to substantial ascites, limb tremor, or inability to hold breath, as limb tremor and inability to hold breath can lead to unstable signals during ultrasound examination, potentially affecting the reliability of measurements; (3) Unclear liver-kidney echo contrast or a history of splenectomy.
Observational indicators
Demographic data
On the day of the ultrasound measurement, the following patient information was recorded: sex, age, disease duration, medical history, height, and weight. Body mass index (BMI), defined as weight in kilograms divided by the square of height in meters, was categorized as follows: BMI < 24 kg/m² as normal, 24 kg/m² ≤ BMI < 28 kg/m² as overweight, and BMI ≥ 28 kg/m² as obese [12–14].
Routine ultrasound examination and UDFF (Ultrasound-Derived fat Fraction) + Auto pSWE (Auto Point Shear Wave) examination
The examination used the ACUSON Sequoia ultrasound system VA30 SW (Siemens Healthineers, Erlangen, Germany), equipped with a 5C1 convex probe (1.0-5.7 MHz) and a specialized deep-penetration DAX probe. Each of two trained sonologists (Sonologists A and B) performed the UDFF + Auto pSWE measurements independently on the same day, without knowing the other’s results. Sonologists A and B have over 5 and 20 years of abdominal ultrasound diagnostic experience, respectively.
After an 8-hour fasting period, a routine abdominal B-mode ultrasound examination was carried out on the patients. The liver parenchyma brightness, the attenuation of echoes behind the liver, the clarity of the diaphragm, the contrast of echoes between the liver, kidneys, and spleen, the clarity of intrahepatic vessel visualization, as well as the hemodynamic characteristics including the portal venous velocity (PVV) and portal venous diameter (PVD) were recorded. For each patient, at least four gray-scale images were obtained for the subsequent assessment of the degree of hepatic steatosis. These included comparative images of the liver and right kidney (Fig. 1A), the right branch of the portal vein (Fig. 1B), comparative images of the liver and spleen (Fig. 1C), and hepatic vein images (Fig. 1D).
Fig. 1.
Conventional ultrasound images of Wilson’s disease. Note: A: Echo contrast between the liver and the kidney; B: Right branch of the portal vein; C: Echo contrast between the liver and the spleen; D: Hepatic vein
UDFF + Auto pSWE procedure
Patients were positioned supine with their right arm raised to widen the intercostal space while maintaining steady breathing. The operator used a DAX Abdomen probe to target segments S5 or S8 of the liver. The probe was positioned perpendicular to the skin surface, and the VT button was pressed on the control panel. The operator sequentially selected the pSWE, Auto pSWE, and UDFF options on the touchscreen. The region of interest (ROI) was set 1.5–2 cm below the liver capsule, ensuring the sampling line’s “+” marker was parallel to the capsule. Patients were instructed to hold their breath after identifying an appropriate imaging plane (minimizing vascular interference and ensuring clear hepatic parenchyma). When the ultrasound image on the monitor was stable, the “update” button was pressed to freeze the image. The Auto pSWE method automatically provided one UDFF value along with up to 15 Vs (m/s) and E (kPa) values (Fig. 2A and B). A detection was considered valid if the Vs interquartile range-to-median ratio (IQR/Median) was ≤ 0.15 and the E (kPa) IQR/Median was ≤ 0.30. The median value of valid measurements was taken as the result for each Vs (m/s) and E (kPa) measurement. This process was repeated at least five times. The final UDFF and E (kPa) values, with a data distribution satisfying IQR/Median ≤ 0.30, were used as a reference for the quality control standard of this technique.
Fig. 2.
UDFF (Ultrasound-Derived Fat Fraction) + Auto pSWE (Auto Point Shear Wave) Examination. A region of interest (parallel to the liver capsule) was placed on Segment V of the liver, 1.5 cm away from the liver capsule, avoiding large intrahepatic vascular structures. The measurement results are shown in the upper-left corner of the figure: UDFF value, depth, Vs (m/s), and E (kPa) values
Visual grading of hepatic steatosis
All ultrasound images were acquired in accordance with standardized imaging planes to mitigate scoring bias arising from technical variability. Three senior ultrasound physicians independently evaluated the abdominal ultrasound images of all patients under blinded conditions. The assessment was based on Hamaguchi’s score, which assesses liver steatosis by examining the brightness of liver parenchyma echoes, the contrast between liver-kidney or liver-spleen echoes, deep attenuation, and the degree of vessel blurring [15, 16]. A consensus score was reached to determine the level of hepatic steatosis. Hamaguchi’s score ranges from 0 to 6, where a score of ≥ 2 indicates hepatic steatosis and a ≥ 4 indicates moderate/severe steatosis [17–19]. Higher scores represent a greater severity of hepatic steatosis.
(1) Liver parenchyma brightness and Liver-Kidney (or Liver-Spleen) Echo Contrast, Score 0: No bright liver, negative liver-kidney (or liver-spleen) contrast. Score 1: Either bright liver or positive liver-kidney (or liver-spleen) contrast. Score 2: Mildly bright liver with positive liver-kidney (or liver-spleen) contrast. Score 3: Severely bright liver with positive liver-kidney (or liver-spleen) contrast. (2) Deep Attenuation, Score 0: No deep attenuation. Score 1: Blurred diaphragm, but the observer can distinguish the diaphragm. Score 2: The diaphragm is indiscernible to the observer. (3) Vessel Blurring, Score 0: No vessel blurring. Score 1: Intrahepatic vessels have unclear boundaries and narrowed lumens.
Data analysis and statistical methods
Statistical analyses were conducted using SPSS 26.0 and R (version 4.1.3). Continuous variables with a normal distribution were presented as mean ± standard deviation (x‾±s), while non-normally distributed variables were expressed as median (interquartile range). Categorical data were reported as frequencies or percentages. Comparisons between two groups for normally distributed data were made using an independent samples T-test. For non-normally distributed data, the non-parametric Mann-Whitney U test was used. Pearson’s chi-square test was applied to compare categorical variables between groups. Bland-Altman plots were used to assess the consistency of UDFF measurements between different observers or at different times by the same observer. Spearman’s correlation coefficient was used in univariate analysis to examine the relationship between BMI and Hamaguchi score. A multivariate logistic regression analysis, performed with the glm package in R, was used to analyze factors influencing hepatic steatosis. Factors included in the multivariate analysis were selected based on clinical experience and previous literature [7, 17–21], including age, gender, disease duration, BMI, portal vein diameter, portal vein velocity, and liver stiffness measurement (LSM). The diagnostic efficacy of UDFF was determined using ROC curve analysis, which also identified the optimal cutoff value for diagnosing hepatic steatosis in WD. The significance level was set at p = 0.05.
Results
Demographic characteristics of the study population
A total of 115 patients with WD were initially included in this retrospective study based on the inclusion criteria. After applying the exclusion criteria, 26 patients were excluded: 13 due to uncontrolled limb tremors or inability to hold their breath, which affected the quality of UDFF and LSM; 9 due to excessive ascites that prevented successful UDFF and shear wave elastography; and 4 patients due to incomplete diagnostic information on routine ultrasound images. The final study population consisted of 89 WD patients, with 53 males and 36 females. The median age was 26 years, the median disease duration was 21.2 years, the median BMI was 20.75 kg/m², and the median Hamaguchi score was 3 (Table 1).
Table 1.
Demographic characteristics of the study population
| Characteristic | N = 89 |
|---|---|
| Age (years) | 26.00 [18.00;35.00] |
| Gender (n) | |
| Female | 36 (40.45%) |
| Male | 53 (59.55%) |
| Disease Duration (years) | 21.20 [13.30;30.80] |
| BMI (kg/m²) | 20.75 [17.97;24.54] |
| UDFF (%) | 4.00 [3.00;6.00] |
| Portal Vein Diameter (mm) | 11.00 [10.00;12.00] |
| Portal Vein Velocity (m/s) | 21.10 [18.40;24.40] |
| LSM (kPa) | 6.40 [4.30;8.80] |
| Shear Wave Speed (m/s) | 1.48 [1.20;1.73] |
| Hamaguchi’s score | 3.00 [2.00;4.00] |
Note: Gender is presented as counts (percentages), while other characteristics are expressed as medians (lower quartile, upper quartile)
Consistency of UDFF measurements by sonographers of different experience levels and at different times
The Bland-Altman plot for Sonographer A, who has 5 years of experience, shows a bias of 5.7% in UDFF measurements taken at 30-minute intervals (Fig. 3). Similarly, the Bland-Altman plot for Sonographer B, who has over 20 years of experience, shows a bias of 1.1% in measurements taken at 30-minute intervals (Fig. 4). The Bland-Altman plot comparing the UDFF measurements between Sonographer A and Sonographer B shows a bias of 14.9% (Fig. 5). All biases are close to 0, indicating minimal systematic error between these methods. Most data points fall between the two red dashed lines, suggesting that the two measurement methods are generally consistent. This indicates that the deviations of the UDFF measured within and between the two doctors were relatively small.
Fig. 3.
Bland-Altman consistency plot for sonographer A (Intra-observer consistency)
Fig. 4.
Bland-Altman consistency plot for sonographer b (Intra-observer consistency)
Fig. 5.
Bland-Altman consistency plot between sonographer A and sonographer B (Inter-observer consistency)
Univariate analysis of the correlation between BMI, UDFF, and Hamaguchi’s score in WD patients
Figure 6 shows no significant correlation between BMI and Hamaguchi score (r = 0.08, P = 0.478). Figure 7 indicates a significant positive correlation between UDFF and Hamaguchi score (r = 0.71, P < 0.001), suggesting a statistically significant relationship. Figure 8 shows no significant correlation between BMI and UDFF score (r = 0.15, P = 0.1539).
Fig. 6.
Correlation between BMI and Hamaguchi score
Fig. 7.
Correlation between UDFF and Hamaguchi score
Fig. 8.
Correlation between BMI and UDFF
Multivariate analysis of factors influencing WD patients with hepatic steatosis
The previous univariate analysis revealed a correlation between UDFF and the Hamaguchi score. Based on prior literature, a multivariate analysis was performed to account for potential confounding factors, including age, gender, disease duration, BMI, portal vein diameter, portal vein velocity and LSM. The results showed that age, gender, BMI, portal vein velocity, and LSM were not significant factors influencing the degree of hepatic steatosis. The P-value for portal vein diameter was slightly higher than the significance threshold of 0.05. UDFF was identified as an independent influencing factor for WD patients with hepatic steatosis. A significant correlation was observed between UDFF and the Hamaguchi score, with a regression coefficient of 1.243. This indicates that each one-unit increase in UDFF is associated with approximately a 3.5-fold increase in the likelihood of hepatic steatosis (Table 2).
Table 2.
Multivariate analysis of factors influencing WD patients with hepatic steatosis
| Characteristics | B | SE | OR | CI | Z | P |
|---|---|---|---|---|---|---|
| (Intercept) | -3.584 | 6.59217 | 0.028 | 0.027 (7.673–39584) | -0.544 | 0.587 |
| Age | -0.703 | 1.0335 | 0.495 | 0.494 (0.024–1.085) | -0.681 | 0.496 |
| Gender | -1.337 | 0.8608 | 0.263 | 0.262 (0.042–1.321) | -1.553 | 0.12 |
| Disease Duration (years) | 0.698 | 1.03298 | 2.009 | 2.008 (0.912–41.16) | 0.675 | 0.5 |
| BMI (kg/m²) | -0.023 | 0.08333 | 0.977 | 0.976 (0.830–1.170) | -0.28 | 0.779 |
| Portal Vein Diameter (mm) | 0.206 | 0.10616 | 1.229 | 1.228 (1.022–1.567) | 1.94 | 0.052 |
| Portal Vein Velocity (m/s) | -0.087 | 0.24847 | 0.916 | 0.916 (0.554–1.518) | -0.352 | 0.725 |
| LSM (kPa) | 0.177 | 0.18906 | 1.193 | 1.193 (0.875–1.840) | 0.935 | 0.35 |
| UDFF (%) | 1.243 | 0.47042 | 3.465 | 3.464 (1.617–10.51) | 2.642 | 0.008 |
ROC curve analysis determined that the optimal UDFF cutoff value for diagnosing WD patients with hepatic steatosis was 4.5%. The area under the ROC curve (AUROC) was 0.80 (95% CI: 71-90%), with a sensitivity of 90% and specificity of 80% (Fig. 9). The maximum Youden index was 0.70.
Fig. 9.
ROC curve analysis of UDFF for diagnosing WD patients with hepatic steatosis
Discussion
UDFF is a non-invasive, expeditious, and relatively low-cost technique that has been employed in the evaluation of a variety of liver diseases. Nevertheless, research on its application in WD is extremely scarce. This study investigated the application of UDFF in the assessment of hepatic steatosis among WD patients, thus offering new perspectives and references for research in this domain. The results of the study demonstrated that UDFF technology exhibited high intra-observer and inter-observer consistencies among WD patients, primarily owing to the strict quality control procedures of this technique. According to clinical experience and previous studies, it has been pointed out that the UDFF may be affected by confounding factors such as the degree of liver fibrosis, obesity, and metabolic abnormalities during the assessment of NAFLD [7, 17–21]. Therefore, when enrolling subjects in this study, viral liver diseases, autoimmune liver diseases, alcoholic liver diseases, and rheumatic diseases that may lead to liver fibrosis were excluded. In addition, after univariate correlation analysis and multivariate analysis considering confounding factors such as body mass index (BMI), liver stiffness, age, gender, and disease duration, it was ultimately determined that there was no significant correlation between the BMI of patients with WD and the visual score of hepatic steatosis. This implies that BMI cannot serve as an indirect indicator reflecting the condition of hepatic steatosis. In contrast, the UDFF value showed a significant correlation with the visual score of hepatic steatosis. The results verified that UDFF has a relatively high diagnostic efficacy in quantitatively evaluating the degree of hepatic steatosis in WD patients, highlighting its application potential in this rare disease.
In evaluating the severity of hepatic steatosis in WD patients, an invasive approach such as liver biopsy is unethical. To assess the reliability of UDFF, this study used Hamaguchi’s score as a reference. Hamaguchi’s score is an alternative semi-quantitative, ultrasound-based scoring system for hepatic steatosis, with a sensitivity of up to 91.7% and a specificity of up to 100% [15]. Another study compared various non-invasive assessment methods, including the fatty liver index (FLI), hepatic steatosis index (HSI), lipid accumulation product (LAP), and Hamaguchi’s score. The findings indicated that Hamaguchi’s score had high accuracy (AUC ≥ 0.90) for detecting hepatic steatosis, with the highest specificity among these methods [19].
WD is a rare disorder, and studies investigating the relationship between hepatic steatosis and BMI in WD are scarce. A case report by Bracciamà et al. suggested that obesity may be a confounding factor for hepatic steatosis in WD patients [22]. However, in this study, no significant correlation was found between BMI and the Hamaguchi score in WD patients. This finding differs from previous research on non-alcoholic fatty liver disease (NAFLD), which has shown a close association between hepatic steatosis and BMI. In NAFLD, insulin resistance plays a central role, with obesity being a major contributor. Obesity-induced insulin resistance impairs the liver’s ability to process circulating lipids, leading to excessive lipid accumulation in hepatocytes and the development of steatosis [8, 23–25].
However, in WD, the mechanism differs. Pathophysiological studies on WD indicate that hepatic steatosis in WD is primarily due to copper-induced toxicity, causing lipid metabolism disorders, especially mitochondrial dysfunction, which disrupts fatty acid β-oxidation. This leads to lipid metabolism disturbances and abnormal accumulation of fat within liver cells, resulting in hepatic steatosis [26–28]. In WD, hepatic steatosis is more closely linked to cellular damage caused by copper toxicity. This association is not directly related to BMI. Therefore, BMI has limited value in assessing hepatic steatosis in WD. The extent of liver damage in WD patients depends more on copper deposition and its toxic effects within the liver. Consequently, even patients with normal or low BMI may exhibit significant hepatic steatosis. Therefore, for patients with hepatic steatosis of unknown origin and relatively low BMI, especially children, it is not advisable to diagnose them as having NAFLD lightly. It is necessary to further complete a series of examinations, such as relevant genes for excluding WD and copper biochemistry tests.
This study demonstrates a positive correlation between UDFF and visual grading of hepatic steatosis in WD patients. UDFF is an emerging technology for assessing the severity of hepatic steatosis, with recent research showing its value, particularly in the screening, grading, and monitoring of treatment effects in fatty liver disease. However, these studies primarily focus on NAFLD patients. Tavaglione F [18] suggested that UDFF is an effective method for assessing hepatic steatosis in high-risk individuals. Huang YL [20] also indicated that UDFF is a feasible, non-invasive imaging tool, with UDFF values increasing with the severity of fatty liver disease. Studies by Dillman JR [7] and Zalcman M [8] comparing UDFF with MRI proton density fat fraction (PDFF) showed high consistency, supporting the accuracy and reliability of UDFF.
As a center specializing in WD diagnosis and treatment, we applied UDFF technology clinically in WD patients and found high consistency between UDFF measurements and visual grading of hepatic steatosis. This study also identified a UDFF cutoff value of 4.5% for assessing hepatic steatosis in WD, with an AUROC of 0.80 (95% CI: 71-90%), sensitivity of 90%, and specificity of 80%. Currently, clinical research on UDFF applications is limited, and studies on its cutoff values remain insufficient. Zalcman [8] proposed a UDFF cutoff of 6% for diagnosing steatosis, with an AUROC of 0.95 (95% CI: 0.89–0.99), sensitivity of 90%, and specificity of 94%. Tavaglione [18] suggested a cutoff of 6.25% for assessing NAFLD, with a sensitivity of 0.84 and a specificity of 0.97. Dillman JR [7] reported that a UDFF threshold above 5% correlates well with MRI PDFF > 5.5%, with high sensitivity (94%) but lower specificity (63%). Our study’s UDFF cutoff for diagnosing hepatic steatosis in WD is lower than these previously reported values, reflecting the unique impact of copper accumulation on steatosis in WD. It should be noted that it is impossible to clearly distinguish WD from other diseases solely based on this cutoff value of UDFF. The definitive diagnosis of WD still requires a series of relatively complex tests, such as genetic testing and copper biochemistry assays. For patients who have already been diagnosed with WD, traditional ultrasound has limited sensitivity in detecting early hepatic steatosis. The cutoff value identified in this study enables earlier detection of whether liver injury has occurred in WD patients, prompting early clinical intervention. This is the clinical significance of determining the cutoff value of UDFF. In addition, for patients who have not been diagnosed with WD, if the UDFF value exceeds this threshold and there is no high BMI, we should suspect the possibility of WD in these patients and conduct further examinations to rule out WD.
This study has several limitations. First, we compared UDFF with the Hamaguchi score rather than liver biopsy. This approach may not fully reflect the true degree of hepatic steatosis. However, performing a liver biopsy to assess the extent of hepatic steatosis in WD is not ethically justifiable. As a result, obtaining a large sample of biopsy-based controls is challenging. In future studies, we plan to conduct more prospective research to evaluate the accuracy of UDFF in diagnosing hepatic steatosis, potentially using MRI-PDFF as a reference standard. Additionally, this study was cross-sectional; a longitudinal follow-up of WD patients would be valuable to assess UDFF’s utility in monitoring disease progression or response to therapy. Second, Hamaguchi’s score as a reference standard in this study involves a liver-kidney echo contrast. Some WD patients may also have copper deposition in the kidneys, leading to renal involvement and increased kidney echo intensity, which could distort the liver-kidney contrast. To address this, we additionally compared liver and spleen echoes to validate further changes in liver echogenicity. Third, WD is a rare disease, and the sample size in this study is relatively small. Larger cohort studies are needed to verify our preliminary findings. Fourthly, the mutation types of the ATP7B gene may affect the copper metabolism efficiency and the degree of liver damage in patients with WD. In the future, it is necessary to further explore the association between the WD genotype and the UDFF.
Conclusion
UDFF shows high operational consistency in clinical practice. In WD patients, there may be a paradoxical phenomenon of low BMI with a high degree of hepatic steatosis. UDFF can be served as a valuable tool for quantitatively assessing hepatic steatosis in WD. Our study on WD further validates the potential of UDFF in the non-invasive evaluation of hepatic steatosis. Moreover, UDFF has advantages such as low examination costs, convenience, and the ability to be rechecked at a high frequency, and thus can be regarded as an effective instrument for liver health management.
Acknowledgements
Special thanks are due to our supervisor, Prof. Ma Shou Liang.
Author contributions
L Y and L B Q collected clinical data and drafted the manuscript; L Y is the First Author. J F, N J J collected clinical data. W J P and L B Q designed the study. W J P and L B Q are the corresponding authors.
Funding
Provincial key specialty construction projects in 2020. Traditional Chinese Medicine Inheritance and Innovation Project of Anhui Province (2024CCCX011).
Data availability
The data supporting the findings of this study are available from the corresponding author, upon reasonable request.
Declarations
Ethics approval and consent to participate
This retrospective study was conducted in accordance with the ethical guidelines of the Declaration of Helsinki. The requirement for individual consent was waived by the committee because of the retrospective nature of the study. The full name of the ethics committee that waived the requirement of informed consent for our study is the Ethics Committee of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine.
Consent for publication
All authors read and approved the final manuscript.
Competing interests
The authors declare no competing interests.
Footnotes
Li Yan is the first author.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Li Bao Qi, Email: renandwo@163.com.
Wang Jing Ping, Email: hf_wjp@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author, upon reasonable request.