Diagnostic Thresholds and Clinical Value of Ultrasound-Derived Fat Fraction in Assessing Hepatic Steatosis: Insights from a Prospective Study

doi:10.21203/rs.3.rs-5288943/v1

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Research Article

Diagnostic Thresholds and Clinical Value of Ultrasound-Derived Fat Fraction in Assessing Hepatic Steatosis: Insights from a Prospective Study

https://doi.org/10.21203/rs.3.rs-5288943/v1

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Background

A reliable assessment of hepatic steatosis is imperative for the effective management of metabolic dysfunction-associated steatotic liver disease (MASLD). This study assesses the effectiveness of ultrasound-derived fat fraction (UDFF) in measuring hepatic steatosis and determines diagnostic thresholds for different severity levels.

Methods

This prospective cross-sectional study involved 79 participants (mean age 42.8 ± 13.8 years) recruited from two centers. MRI proton density fat fraction (PDFF) served as the reference standard for assessing hepatic steatosis. Pearson correlation coefficients were applied to determine the relationship between UDFF and MRI-PDFF, while Bland-Altman analysis evaluated the measurement consistency between UDFF and PDFF.ROC curve analysis evaluated the diagnostic performance of UDFF against visual score, Fatty Liver Index (FLI), the CAP score (CAPS), and Hepatic Steatosis Index (HSI).

Results

The UDFF showed a strong correlation with MRI-PDFF (r = 0.84, p < 0.001), with a mean bias of 2.06% and 95% limits of agreement ranging from − 7.03–11.15%. The AUC values for UDFF in diagnosing steatosis grades ≥ S1, ≥S2, and S3 were 0.95, 0.97, and 0.94, respectively, outperforming visual score, FLI, CAPS, and HSI. The optimal UDFF cutoff values for these grades were 8.5%, 16.5%, and 22%.

Conclusion

UDFF shows high consistency in diagnostic performance with PDFF and steatosis grades, although UDFF values tend to be slightly higher than those of PDFF.

Ultrasound-derived fat fraction

MRI proton density fat fraction

Hepatic steatosis

Metabolic-associated steatotic liver disease

Non-invasive diagnostic tools

Hepatic steatosis, a hallmark of metabolic-associated steatotic liver disease (MASLD), is marked by abnormal fat accumulation in liver cells (1). With the rising prevalence of obesity and diabetes, the incidence of hepatic steatosis is continuously increasing worldwide, becoming a significant public health issue (2). Timely and precise diagnosis is essential for managing hepatic steatosis and preventing its progression to MASH, liver fibrosis, or cirrhosis.

Although liver biopsy is the gold standard for diagnosing hepatic steatosis, its high cost, invasiveness, and risks have prompted the creation of non-invasive diagnostic alternatives (4–6). MRI proton density fat fraction (MRI-PDFF) serves as a reference standard for quantitatively assessing liver fat content, providing precise measurements by analyzing the proportion of fat signals within MRI voxels (7, 8). However, despite the high accuracy of MRI-PDFF, its high costs, time consumption, and accessibility issues in certain clinical settings limit its widespread application (9).

Ultrasound, due to its low cost, non-invasive nature, and broad availability, plays a vital role in the assessment of hepatic steatosis. Traditional B-mode ultrasound assesses hepatic steatosis by examining liver tissue echogenicity, but its sensitivity for mild steatosis is limited, particularly in patients with higher body mass index (10, 11). To overcome these limitations, various quantitative ultrasound techniques have been developed, aiming to more accurately measure liver fat content by analyzing parameters such as the attenuation coefficient and backscatter coefficient (11, 12). The ultrasound-derived fat fraction (UDFF) algorithm quantitatively estimates liver fat content by integrating attenuation coefficient and backscatter coefficient, expressing it as a percentage similar to MRI-PDFF (13, 14).

Although previous studies have reported on the clinical application of quantitative ultrasound, inconsistent definitions of the steatosis classification thresholds across different studies have prevented the establishment of unified diagnostic standards. Furthermore, standardized examination protocols require further exploration, which also limits the broader clinical application of UDFF(15, 16).

This study employs a dual-center, prospective design to explore the clinical application of UDFF and assess its diagnostic performance in detecting varying degrees of hepatic steatosis. Additionally, the study identifies the optimal thresholds for UDFF, providing a basis for its future widespread application in clinical settings.

Study Design and Participants:

This dual-center, prospective, cross-sectional observational clinical diagnostic research was conducted at two tertiary general hospitals in China(Wuhu Second People’s Hospital and Bengbu Third People’s Hospital). Written informed consent was obtained from all participants, and approval from the institutional review committee of Wuhu Second People's Hospital was obtained (approval number KY-2024-102). August 2024, we prospectively enrolled adults aged 18 and above with suspected metabolic-associated steatotic liver disease (MASLD). The MASLD criteria were based on the latest definitions: hepatic steatosis confirmed by imaging or biopsy, and participants meeting any cardiometabolic criteria (Table 1). Exclusion criteria included (a) other chronic liver diseases including autoimmune hepatitis, viral hepatitis, drug-induced liver injury, Wilson's disease, ɑ1-antitrypsin deficiency, and hemochromatosis; (b) high alcohol consumption (≥ 210 g/week for men and ≥ 140 g/week for women); and (c) contraindications for MRI examination. Participants completed both ultrasound (US) and MRI-PDFF exams either on the same day or within a week.

Table 1

The adult criteria of MASLD.
Metabolic risk factor	Adult criteria
Overweight or Obesity	Body mass index ≥ 23 kg/m² OR waist circumference > 94 cm (M) 80 cm (F) OR ethnicity adjusted equivalent
Dysglycaemia or type 2 diabetes	Fasting serum glucose ≥ 5.6 mmol/L (100 mg/dl) OR 2-hour post-load glucose levels ≥ 7.8 mmol/L (140mg/dl) OR HbA1c ≥ 5.7% (39 mmol/L) OR type 2 diabetes OR treatment for type 2 diabetes
Plasma triglycerides	≥ 1.70 mmol/L (150 mg/dl) OR lipid lowering treatment
HDL-cholesterol	≤ 1.0 mmol/L (40 mg/dl) (M) and ≤ 1.3 mmol/L (50 mg/dl) (F) OR lipid-lowering treatment
Blood pressure	≥ 130/85 mmHg OR specific antihypertensive drug treatment
MASLD, metabolic dysfunction-associated steatotic liver disease; HbA1c, Hemoglobin A1c; HDL, high-density lipoprotein.

Ultrasound Examination Including UDFF Measurement:

Ultrasound examinations were performed using the Siemens ACUSON Sequoia ultrasound diagnostic system (Siemens Healthineers, Erlangen, Germany), equipped with a 5C1 abdominal probe and a DAX probe. Participants fasted for a minimum of 8 hours before the examination. Participants lay supine with their right arm abducted while experienced sonographers (YMW, JC, each with over 10 years of abdominal ultrasound expertise) performed the ultrasound examinations. First, abdominal ultrasound was conducted with the 5C1 probe. Hepatic steatosis was evaluated using the Hamaguchi score system, which considers liver parenchyma brightness, liver-kidney echogenicity contrast, ultrasound attenuation depth, and vascular blurriness. Based on the visual score, steatosis severity is classified from 0 to 3: 0 indicates no steatosis, 1 indicates mild steatosis, 2 indicates moderate steatosis, and 3 indicates severe steatosis. UDFF measurements were conducted using the DAX probe, placed in the right intercostal space while the patient held their breath during quiet respiration. A square region of interest (ROI) measuring 3 cm on each side was placed within the liver right lobe parenchyma, avoiding major ductal structures, with the upper horizontal line of the ROI aligned with the liver capsule. Five UDFF measurements were taken, with the median value used for analysis.

MRI-PDFF Examination:

MRI examinations were conducted using 3.0-T MRI scanners from Siemens Healthineers (Erlangen, Germany) and GE Healthcare (Waukesha, WI).MRI-PDFF was measured in the right liver lobe using a multi-echo gradient echo sequence.Each participant underwent three PDFF data acquisitions, and the overall median PDFF value was calculated.The diagnostic criteria for MRI-PDFF were as follows (17): S0 (PDFF < 5%), S1 (PDFF = 5%-15%), S2 (PDFF = 15%-25%), and S3 (PDFF ≥ 25%).

Demographic and Laboratory Data:

Demographic information, including gender, age, BMI, and waist circumference, was gathered. Laboratory tests were performed, including liver function tests, serum lipid levels, and blood glucose levels. Non-invasive tests for hepatic steatosis (NITs) were determined using established formulas, including Fatty Liver Index (FLI) (18), the CAP-score (CAPS) (19), and Hepatic Steatosis Index (HSI) (20).

Statistical analysis:

Statistical analysis was performed using SPSS (v27, IBM) and GraphPad Prism (v9.5.0, GraphPad Software). Group comparisons were conducted using one-way ANOVA with Tukey's post hoc test, based on hepatic steatosis severity. The relationship between MRI-PDFF and UDFF was evaluated using Pearson correlation coefficients, while linear regression analysis evaluated the slope, intercept, and R². Bland-Altman analysis evaluated the agreement between MRI-PDFF and UDFF measurements by determining the 95% limits of agreement (LOAs). The diagnostic performance of the non-invasive methods was evaluated by plotting ROC curves and calculating the AUC. The critical value for UDFF was established using the Youden index, ensuring a minimum of 90% sensitivity and 90% specificity. A p-value under 0.05 was considered statistically significant.

Participant Characteristics:

Among 84 study subjects, 3 were excluded due to other causes of liver disease and 2 due to MRI failures, resulting in a final cohort of 79 participants suspected of metabolic-associated steatotic liver disease (MASLD). Participants averaged 42.8 years in age (SD = 13.8) and had a mean BMI of 26.1 kg/m² (SD = 3.9). The median UDFF for all participants was 9%, with 36 (45.6%) classified as S0, 29 (36.7%) as S1, 8 (10.1%) as S2, and 6 (7.6%) as S3. The demographic and baseline characteristics of participants are summarized in Table 2, and UDFF examination results are shown in Fig. 1A.

Table 2

The demographic and baseline characteristics of participants.
Characteristic	Values
Demographic features
Sex (male, %)	44 (55.7%)
Age(years)	42.8 ± 13.8
BMI(kg/m2)	26.1 ± 3.9
Waist circumference(cm)	90.2 ± 12.5
Hypertension (n, %)	5 (6.3%)
Type 2 diabetes (n, %)	5 (6.3%)
Laboratory examination
TG (mmol/L)	1.5 [0.9, 2.3]
TC (mmol/L)	5.0 ± 0.9
HDL (mmol/L)	1.2 ± 0.3
LDL (mmol/L)	3.0 ± 0.8
Glucose (mmol/L)	5.4 ± 1.2
HbA1c (%)	6.6 ± 0.9
ALB (g/L)	45.5 ± 7.0
AST (U/L)	22.0 [18.0, 30.1]
ALT (U/L)	21.0 [13.2, 46.7]
γ-GGT (U/L)	29.0 [14.0, 49.0]
ALP (U/L)	74.0 [59.0, 85.0]
Skin to liver capsule distance(mm)	21.0 ± 4.4
UDFF	9.0 [5.0, 17.0]
PDFF	6.1 [3.4, 13.0]
FLI	41.4 [13.2, 76.3]
HSI	35.5 [32.0, 40.6]
CAPS	10.6 [9.4, 11.4]
Hepatic steatosis visual score
0	19 (24.1%)
1	32 (40.5%)
2	19 (24.1%)
3	9 (11.4%)
Hepatic Steatosis Grade
S0	36 (45.6%)
S1	29 (36.7%)
S2	8 (10.1%)
S3	6 (7.6%)
BMI, Body Mass Index; TG, Triglycerides; TC, Total cholesterol; HDL, High-density lipoprotein; LDL, Low-density lipoprotein; HbA1c, Hemoglobin A1c; ALB, Albumin; AST, Aspartate aminotransferase; ALT, Alanine aminotransferase; γ-GGT, γ-glutamyl transpeptidase; ALP, Alkaline phosphatase; UDFF, Ultrasound-derived fat fraction; PDFF, Proton density fat fraction; FLI, Fatty liver index; HSI, Hepatic steatosis index; CAPS, CAP-score.

Correlation Between UDFF and PDFF:

The study observed an increase in UDFF values corresponding to the severity of hepatic steatosis (Fig. 1B). The median UDFF values for each group were as follows: S0 group 5%, S1 group 13%, S2 group 20.5%, S3 group 26.5%. Significant differences were observed between groups, with the exception of S2 and S3 (p < 0.001) (Table 3). Linear regression analysis showed a slope of 0.78 (95% CI: 0.67, 0.89), an intercept of 4.15 (95% CI: 2.68, 5.61), and an R² of 0.71, with a Pearson correlation coefficient of r = 0.84 (p < 0.001) (Fig. 2A). Bland-Altman analysis indicated a mean bias of 2.06% between UDFF and MRI-PDFF measurements, with a 95% agreement limit ranging from − 7.03–11.15% (Fig. 2B). The findings demonstrate a notable correlation between UDFF and hepatic steatosis grading.

Table 3

Distribution of UDFF according to Hepatic Steatosis Grade.
parameter	Hepatic Steatosis Grade				P Value	Post Hoc P Value
parameter	S0	S1	S2	S3	P Value	S0vsS1	S1vsS2	S2vsS3
UDFF	5.0 [4.0, 7.3]	13.0 [9.0, 17.0]	20.5 [19.8, 27.5]	26.5 [23.8, 28.5]	< 0.001	< 0.001	< 0.001	0.606
UDFF, Ultrasound-derived fat fraction.

Clinical Value of UDFF in Assessing Hepatic Steatosis:

Table 4 displays the cutoff values, AUC, sensitivity, and specificity of UDFF for various hepatic steatosis grades. The UDFF showed an AUC of 0.95 (95% CI 0.91–0.99) for diagnosing hepatic steatosis ≥ S1, with a cutoff of 8.5%, sensitivity of 85.7%, and specificity of 88.9%. The AUC for diagnosing hepatic steatosis ≥ S2 was 0.97 (95% CI: 0.94–0.99), achieving a sensitivity of 92.9% and specificity of 87.7% at a 16.5% cutoff. For S3 grade hepatic steatosis, the AUC was 0.94 (95% CI: 0.88–0.99), with a 22% cutoff value, 83.3% sensitivity, and 93.2% specificity.

Table 4

The cutoff values of UDFF according to Youden index, at least 90% sensitivity and 90% specificity.
	AUC	Cutoff (%)	Sensitivity (%)	Specificity (%)
≥S1	0.95(0.91–0.99)
Youden index		8.5	85.7	88.9
Rule-out		7.5	97.7	75.0
Rule-in		10.5	74.4	94.4
≥S2	0.97(0.94–0.99)
Youden index		16.5	92.9	87.7
Rule-out		13.5	100	78.5
Rule-in		19.5	78.6	96.9
S3	0.94(0.88–0.99)
Youden index		22.0	83.3	93.2
Rule-out		15.5	100	74.0
Rule-in		24.5	66.7	94.5
AUC, Area Under the Curve.

Diagnostic Performance Comparison of UDFF, Visual Score, FLI, HSI, and CAPS for Hepatic Steatosis:

The AUC of UDFF for diagnosing hepatic steatosis ≥ S1 was 0.95 (95% CI: 0.91–0.99), outperforming all other indicators. The AUCs for the visual score, FLI, HSI, and CAPS were 0.87, 0.82, 0.87, and 0.82, respectively. There was a significant difference between UDFF and both FLI and CAPS (P < 0.05) in comparison with HSI and the visual score (P > 0.05). The AUC of UDFF for diagnosing hepatic steatosis ≥ S2 was 0.97 (95% CI 0.94–0.99), significantly exceeding the AUCs of the other four indicators, which were 0.77, 0.84, 0.88, and 0.86 (P < 0.05). For diagnosing hepatic steatosis S3, the UDFF demonstrated an AUC of 0.94 (95% CI: 0.88–0.99). The AUCs for the visual score, FLI, HSI, and CAPS were 0.73, 0.86, 0.89, and 0.89, respectively. The AUC of the visual score was significantly lower than that of UDFF (P < 0.05), while other indicators showed no significant differences compared to UDFF. Overall, UDFF demonstrated superior diagnostic performance compared to the visual score, FLI, HSI, and CAPS across all grades of hepatic steatosis (Table 5 and Fig. 3).

Table 5

Comparison of Diagnostic Performance Between UDFF, FLI, HSI, CAPS and Visual Score for Hepatic Steatosis.
Noninvasive methods	AUC (95%CI)	Sensitivity (%)	Specificity (%)	P Value
≥S1
UDFF	0.95(0.91–0.99)	85.7	88.9	/
FLI	0.82(0.73–0.91)	83.7	72.2	<0.05
HSI	0.87(0.78–0.96)	88.4	77.8	0.11
CAPS	0.82(0.73–0.91)	74.4	72.2	<0.05
Visual score	0.87(0.79–0.95)	60.1	94.4	0.08
≥S2
UDFF	0.97(0.94–0.99)	92.9	87.7	/
FLI	0.84(0.71–0.96)	64.3	93.9	<0.05
HSI	0.88(0.80–0.97)	92.9	70.8	<0.05
CAPS	0.86(0.75–0.98)	71.4	90.8	<0.05
Visual score	0.77(0.65–0.89)	71.4	72.3	<0.05
S3
UDFF	0.94(0.88–0.99)	83.3	93.2	/
FLI	0.86(0.72–0.99)	80.0	92.8	0.28
HSI	0.89(0.79–0.99)	90.0	84.1	0.39
CAPS	0.89(0.74–0.99)	90.0	89.9	0.47
Visual score	0.73(0.60–0.87)	70.7	70.0	<0.05
UDFF, Ultrasound-derived fat fraction; PDFF, Proton density fat fraction; FLI, Fatty liver index; HSI, Hepatic steatosis index; CAPS, CAP-score; AUC, Area Under the Curve.

This prospective study, conducted at two centers, assessed the diagnostic efficacy of ultrasound-derived fat fraction (UDFF) for evaluating hepatic steatosis. The results indicate that UDFF is an accurate and convenient non-invasive tool for evaluating varying degrees of hepatic steatosis. Compared to traditional non-invasive blood tests such as HSI, FLI, and CAPS, as well as visual scoring, UDFF demonstrated superior diagnostic accuracy. The significant correlation between UDFF and MRI-PDFF (r = 0.84, p < 0.001) validates UDFF as a dependable indicator of liver fat content, consistent with previous studies (21, 22).

UDFF exhibited higher diagnostic accuracy than serum biomarkers like FLI, HSI, and CAPS, aligning with trends from past research (23, 24). For instance, Tavaglione et al. (23) found that while serum markers can indirectly reflect liver fat content, imaging tools typically provide more direct and precise results. Compared to MRI-PDFF, the gold standard for quantitative imaging, UDFF offers greater accessibility, ease of use, and lower costs, making it ideal for resource-limited healthcare settings and enabling large-scale screening and long-term monitoring (25).

Furthermore, UDFF can be operated using existing ultrasound equipment without significant additional investment, greatly enhancing its application prospects in routine clinical practice, especially for preliminary screening and long-term monitoring. Unlike liver biopsy, UDFF offers a non-invasive and convenient assessment tool for individuals at high risk for MASLD (26).

Importantly, this study also provides optimal cutoff values for different stages of hepatic steatosis. These findings align with those of Kubale et al. (14), who reported diagnostic thresholds of 6.5% for S1, 17.4% for S2, and 22.1% for S3. While these thresholds offer valuable references for clinical practice, our study indicated that UDFF may show a slight positive bias in certain cases compared to MRI-PDFF. The mean bias for UDFF was 2.06%, with 95% limits of agreement between − 7.03% and 11.15%. This trend has been noted in previous studies as well (13, 27), suggesting that UDFF may face some systematic bias in clinical applications. Future studies should aim to enhance imaging parameters, establish uniform measurement protocols, and account for population-specific characteristics (28).

This study also has certain limitations. Although the sample size adequately supports our findings, further validation of UDFF's performance is necessary across diverse ethnic groups and MASLD patient populations. Secondly, the study did not employ liver biopsy as a reference standard. Although MRI-PDFF is widely regarded as an alternative for quantitative liver fat assessment, its correlation with histology requires further validation. Lastly, the application of UDFF in long-term clinical outcomes, such as monitoring treatment responses and disease progression, requires more longitudinal studies for support.

In conclusion, this study provides strong support for UDFF as a non-invasive, cost-effective, and accurate tool for assessing hepatic steatosis. Additional studies are needed to enhance the application of UDFF in diverse clinical settings.

MASLD, metabolic dysfunction-associated steatotic liver disease

US, ultrasound

UDFF, ultrasound-derived fat fraction

MRI-PDFF, MRI proton density fat fraction

BMI, Body Mass Index

FLI, Fatty Liver Index

HSI, Hepatic Steatosis Index

CAPS, the CAP-score

ROC, receiver operating characteristic curve

AC, attenuation coefficient

AUC, area under the curve

BSC, backscatter coefficient

TG, Triglycerides

ALB, Albumin

TC, Total cholesterol

HDL, High-density lipoprotein

AST, Aspartate aminotransferase

LDL, Low-density lipoprotein

γ-GGT, γ-glutamyl transpeptidase

HbA1c, Hemoglobin A1c

ALT, Alanine aminotransferase

ALP, Alkaline phosphatase

ROI, region of interest

NITs: Non-invasive tests

Ethics approval and consent to participate:

This study received institutional review board (IRB) approval from The Second People's Hospital, Wuhu (No. KY-2024-102) and was performed in line with the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants (or their guardians), and they also provided consent for the publication of all images, clinical data, and other materials included in the manuscript.

Consent for publication:

For the publication of images in Figure 1, the authors affirm that human participants provided informed consent.

Availability of data and materials:

All data generated or analyzed in this study are included in the published article and are available upon request.

Competing interests:

No conflicts of interest exist regarding the research, authorship, or publication of this article. There was no involvement of the funding sources in study design, data collection, analysis, interpretation, manuscript writing, or publication decisions.

Funding:

Wuhu Science and Technology Bureau's Key Research and Achievement Transformation program (2023yf122) supported this study.

Acknowledgements:

Not applicable.

Author Contributions:

Conceptualization, YPZ and LJW; Methodology, MYW and YPZ; Writing-original draft, MYW; Writing-review and editing, FLF and MYW; visualization, MYW, JC; data curation, JC, JDX, KW and YZD; project administration, LJW and YPZ. Final approval of the manuscript was obtained from all authors.

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No competing interests reported.

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Diagnostic Thresholds and Clinical Value of Ultrasound-Derived Fat Fraction in Assessing Hepatic Steatosis: Insights from a Prospective Study

Status:

Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Methods

Study Design and Participants:

Ultrasound Examination Including UDFF Measurement:

MRI-PDFF Examination:

Demographic and Laboratory Data:

Statistical analysis:

Results

Participant Characteristics:

Correlation Between UDFF and PDFF:

Clinical Value of UDFF in Assessing Hepatic Steatosis:

Diagnostic Performance Comparison of UDFF, Visual Score, FLI, HSI, and CAPS for Hepatic Steatosis:

Discussion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1