Direct comparison of ultrasound-guided attenuation parameter and controlled attenuation parameter for steatosis using MRI-based proton density fat fraction as a reference

Kento Imajo; Hidenori Toyoda; Satoshi Yasuda; Hidekatsu Kuroda; Masato Yoneda; Atsushi Nakajima; Takashi Kumada

doi:10.14366/usg.25127

Imajo, Toyoda, Yasuda, Kuroda, Yoneda, Nakajima, and Kumada: Direct comparison of ultrasound-guided attenuation parameter and controlled attenuation parameter for steatosis using MRI-based proton density fat fraction as a reference

Original Article

Ultrasonography 2026; 45(1): 9-17. https://doi.org/10.14366/usg.25127

Direct comparison of ultrasound-guided attenuation parameter and controlled attenuation parameter for steatosis using MRI-based proton density fat fraction as a reference

Kento Imajo^1,^2,³

, Hidenori Toyoda⁴

, Satoshi Yasuda⁴

, Hidekatsu Kuroda⁵

, Masato Yoneda¹

, Atsushi Nakajima¹

, Takashi Kumada⁶

¹Department of Gastroenterology, Yokohama City University Graduate School of Medicine, Yokohama, Japan

²Department of Gastroenterology, Shin-Yurigaoka General Hospital, Kawasaki, Japan

³Minimally Invasive Surgical and Medical Oncology, Fukushima Medical University, Fukushima, Japan

⁴Department of Gastroenterology and Hepatology, Ogaki Municipal Hospital, Ogaki, Japan

⁵Division of Hepatology, Department of Internal Medicine, Iwate Medical University, Shiwa-gun, Japan

⁶Department of Nursing, Gifu Kyoritsu University, Ogaki, Japan

Correspondence to: Takashi Kumada, MD, PhD, Department of Nursing, Gifu Kyoritsu University, 5-50 Kitagatasho, Ogaki, Gifu, 503-0019, Japan Tel. +81-584-77-3512 Fax. +81-584-77-3510 E-mail: takashi.kumada@gmail.com

Received July 1, 2025 Revised September 28, 2025 Accepted September 29, 2025 Published online September 29, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Purpose

Hepatic steatosis, which is associated with liver diseases and adverse clinical outcomes, requires accurate, noninvasive diagnostic methods because of the limitations of liver biopsy. This study aimed to evaluate the effectiveness of the ultrasound-guided attenuation parameter (UGAP), a novel technique for assessing hepatic steatosis, and to compare its diagnostic performance with that of the controlled attenuation parameter (CAP), using magnetic resonance imaging (MRI)–derived proton density fat fraction (PDFF) as the reference standard.

Methods

A total of 255 patients with chronic liver disease who underwent CAP, UGAP, and MRI-PDFF were prospectively enrolled from three liver centers in Japan. Using the area under the receiver operating characteristic curve (AUROC) analysis, cutoff values for UGAP were determined according to steatosis grades based on MRI-PDFF. To minimize overfitting, diagnostic performance was validated using five-fold cross-validation.

Results

CAP and UGAP values followed normal distributions, whereas PDFF values deviated from normality and were therefore log-transformed, yielding the variable MRI-logPDFF. CAP and UGAP demonstrated significant correlations with MRI-logPDFF, with intraclass correlation coefficients of 0.696 and 0.797, respectively. For MRI-PDFF–based grading, the AUROC (95% confidence interval) values of CAP and UGAP were 0.878 (0.813–0.923) versus 0.926 (0.867–0.960) for S0 versus S1–S3 (P=0.041), 0.820 (0.763–0.865) versus 0.908 (0.861-0.940) for S0–S1 versus S2–S3 (P<0.001), and 0.863 (0.811–0.902) versus 0.897 (0.852-0.930) for S0–S2 versus S3 (P=0.128), respectively. The validation analysis produced results consistent with those of the primary cohort.

Conclusion

UGAP showed greater diagnostic accuracy than CAP for hepatic steatosis, notably in detecting grades ≥S1 and ≥S2.

Keywords: Ultrasound-guided attenuation parameter; Controlled attenuation parameter; Proton density fat fraction; Fatty liver; Discordance

Key points

Ultrasound-guided attenuation parameter (UGAP) showed significantly better diagnostic performance than controlled attenuation parameter (CAP) for detecting mild and moderate hepatic steatosis, using magnetic resonance imaging (MRI)–derived proton density fat fraction as the reference. UGAP demonstrated fewer discrepancies and less influence from clinical factors compared to CAP, supporting its robustness in clinical practice. As a reliable and noninvasive method, UGAP may serve as a practical alternative to MRI for routine steatosis assessment in chronic liver disease.

Graphical abstract

Introduction

Hepatic steatosis is associated with a wide range of conditions, including obesity, metabolic syndrome, genotype 3 hepatitis C virus (HCV) infection, excessive alcohol consumption, and the use of steatogenic drugs such as corticosteroids and amiodarone [1–3]. Steatosis contributes to accelerated progression of liver fibrosis and a reduced treatment response in several liver diseases, including HCV infection [4]. Consequently, the accurate detection of steatosis is critical for clinical decision-making and prognosis evaluation.

Liver biopsy remains the reference standard for determining the degree of steatosis in patients with chronic liver disease [5]. However, because of its invasiveness, high cost, and risk of complications, biopsy is unsuitable for long-term, repeated monitoring [6]. Therefore, accurate, reproducible, and noninvasive diagnostic alternatives are needed to identify and quantify hepatic steatosis. Among available modalities, imaging techniques represent the most practical and effective noninvasive tools. Conventional B-mode ultrasonography, the first imaging technique adopted in clinical practice, demonstrated a sensitivity of 60%–94% and a specificity of 88%–95% for detecting steatosis [7]. However, its diagnostic accuracy declines substantially in cases of mild steatosis [8]. Furthermore, the evaluation of steatosis severity using this method is subjective and largely dependent on the examiner’s expertise.

Ultrasound-based attenuation parameters have been investigated in several studies assessing hepatic steatosis [9–11], including the controlled attenuation parameter (CAP) obtained through vibration-controlled transient elastography (VCTE; FibroScan, Echosens). CAP, however, is not an imaging technique—it requires a dedicated probe and operates using A-mode acquisition. In contrast, the ultrasound-guided attenuation parameter (UGAP) allows quantification of the attenuation coefficient (dB/cm/MHz) within the B-mode ultrasound framework. UGAP has demonstrated high diagnostic accuracy for evaluating hepatic steatosis, supporting its potential for quantitative measurement [12–17]. Nevertheless, whether UGAP provides superior diagnostic performance to CAP for steatosis grading remains unclear. The present study directly compared UGAP and CAP to determine their respective abilities to diagnose hepatic steatosis in patients with chronic liver disease.

Materials and Methods

Compliance with Ethical Standards

The study protocol was approved by the Ethics Review Committee in Ogaki Municipal Hospital (approval number: 20190822-6), and all patients provided written informed consent. This study was conducted in accordance with the ethical principles of the Declaration of Helsinki 2013.

Study Population

This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki, as revised in 2013.

This prospective study enrolled 255 patients who underwent CAP, UGAP, and magnetic resonance imaging–based proton density fat fraction (MRI-PDFF) examinations at three liver centers (Yokohama City University Hospital, Iwate Medical University Hospital, and Ogaki Municipal Hospital) between February 2020 and December 2022. The study protocol is shown in Supplementary Fig. 1. The inclusion criteria were as follows: age >18 years and simultaneous CAP and UGAP examinations. The main exclusion criteria were incomplete clinical or imaging data and the presence of decompensated cirrhosis with ascites. Patient demographics, clinical history, and baseline characteristics were collected. All imaging assessments were completed within 1 month of the MRI-PDFF scan.

MRI-PDFF and magnetic resonance elastography

The PDFF was quantified using a multiecho Dixon-based IDEAL-IQ sequence, and magnetic resonance elastography (MRE) was performed to measure liver stiffness in all enrolled patients. Specific details of the imaging protocol and acquisition parameters are provided in the Supplementary Information. Steatosis grade was determined according to previously published criteria as follows: grade 0, MRI-PDFF <5.2%; grade 1, 5.2% to <11.3%; grade 2, 11.3% to <17.1%; and grade 3, MRI-PDFF ≥17.1% [18]. Because MRI-PDFF values did not follow a normal distribution, a logarithmic transformation was applied to normalize the data (MRI-logPDFF) (Supplementary Fig. 2).

CAP and UGAP

CAP measurements were performed using the FibroScan system (Echosens, Paris, France) equipped with a standard M or XL probe, as recommended by the device’s automatic probe selection tool. UGAP was evaluated using a LOGIQ E10 ultrasound system (GE Healthcare, Wauwatosa, WI, USA). Detailed measurement protocols for both CAP and UGAP are provided in the Supplementary Information. All CAP and UGAP examinations were performed within 3 months before or after the MRI-PDFF measurement. The success rate was defined as the proportion of participants with valid measurements among all individuals tested, according to predefined reliability criteria. For UGAP, a valid measurement was defined as one with a signal-to-noise ratio above the manufacturer’s recommended threshold and an interquartile range to median ratio (IQR/median) below 30%. For CAP, validity required at least 10 successful acquisitions, an IQR/median of <30%, and an overall success rate (ratio of valid to total attempts) of ≥60%, consistent with established FibroScan quality standards.

Statistical Analysis

Continuous variables are presented as medians with IQR or as means±standard deviations. Pearson’s correlation analysis was used to examine the relationships between MRI-logPDFF and CAP or UGAP values, with correlation strength categorized as minimal (|r|<0.2), weak (|r|=0.2–0.4), moderate (|r|=0.4–0.7), or strong (|r|≥0.7) [19]. Normality was assessed using normal probability plots. The 95% limits of agreement were calculated, and diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Univariate comparisons were performed using the Student’s t-test or one-way analysis of variance with the Scheffé multiple comparison correction. Because some variables did not satisfy the normality assumption, the Kruskal-Wallis test was applied for comparisons across more than two independent groups. To prevent overfitting, five-fold cross-validation was employed. The dataset was randomly divided into five equal subsets; in each iteration, one subset served as the validation set, and the remaining four were used for training. This procedure was repeated 200 times, and the average validation performance metrics were reported [20]. All statistical analyses were conducted using JMP Pro version 15 (SAS Institute Inc., Cary, NC, USA). All authors had full access to the data and participated in the preparation and approval of the final manuscript.

Results

Study Population

A total of 327 consecutive patients with chronic liver disease were screened for study eligibility. Of these, 72 patients were excluded due to withdrawal of consent or MRI-related technical limitations such as metallic implants or claustrophobia. Consequently, the final cohort comprised 255 patients (Supplementary Fig. 3). The success rates were 99.2% for CAP and 100% for UGAP. The baseline demographic and laboratory characteristics of the enrolled patients are summarized in Table 1. The median MRI-PDFF was 10.1% (IQR, 5.3 to 16.8). The corresponding median values for CAP and UGAP were 298.7 dB/m (IQR, 256.8 to 331.8) and 0.74 dB/cm/MHz (IQR, 0.65 to 0.81), respectively.

Association between Clinical Parameters and CAP or UGAP

An analysis was performed to examine the relationships between CAP or UGAP and various clinical parameters, including MRI-based measurements. In univariate analysis, both CAP and UGAP were significantly correlated with age, body mass index (BMI), skin capsule distance (SCD), platelet count, aspartate aminotransferase, alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (γ-GTP), glycated hemoglobin, and MRI-logPDFF (Table 2).

Both CAP and UGAP demonstrated moderate to strong positive correlations with MRI-logPDFF (r=0.696 and r=0.798, respectively). Multivariate linear regression analysis identified independent associations of CAP with SCD (r=0.528, P<0.001), γ-GTP (r=0.136, P=0.032), and MRI-logPDFF (r=0.696, P<0.001). In contrast, UGAP was independently associated only with MRI-logPDFF (r=0.797, P<0.001).

CAP- and UGAP-Based Grading of Steatosis Using MRI-PDFF as the Reference

Based on MRI-PDFF values, patients were categorized into four groups (steatosis grades 0–3) according to the severity of hepatic steatosis. The mean CAP values for grades S0, S1, S2, and S3 were 232.4, 290.4, 308.5, and 340.3 dB/m, respectively (P<0.001). CAP demonstrated a trend of increasing values with higher steatosis grades; however, the difference between grades 1 and 2 did not reach statistical significance (P=0.086) (Fig. 1).

The mean UGAP values for grades S0, S1, S2, and S3 were 0.602, 0.705, 0.775, and 0.833 dB/cm/MHz, respectively (P<0.001). Pairwise comparisons revealed statistically significant differences between all grades (all P<0.001) (Fig. 1).

Comparison of the Diagnostic Performance of CAP and UGAP

For the detection of any hepatic steatosis (grade ≥1), the AUROC values for CAP and UGAP were 0.878 and 0.926, respectively (P=0.041) (Table 3, Fig. 2), with optimal cutoff values of 279 dB/m and 0.68 dB/cm/MHz. For moderate steatosis (grade ≥2), the AUROC values were 0.820 for CAP and 0.908 for UGAP (P<0.001) (Table 3, Fig. 2), with optimal cutoffs of 295 dB/m and 0.72 dB/cm/MHz. For severe steatosis (grade 3), the AUROC values were 0.863 and 0.897, respectively (P=0.128) (Table 3, Fig. 2), with optimal cutoffs of 311 dB/m and 0.77 dB/cm/MHz. UGAP outperformed CAP for diagnosing any steatosis (≥S1) and moderate steatosis (≥S2), while no significant difference in diagnostic accuracy was observed for severe steatosis (S3). Repeated stratified five-fold cross-validation produced results consistent with those of the primary analysis (Supplementary Table 1). Moreover, among the subgroup of obese individuals (BMI ≥25 kg/m², n=174), UGAP demonstrated significantly superior diagnostic performance compared with CAP (Supplementary Table 2).

Discordance between CAP and/or UGAP and MRI-PDFF

Cases showing discordance of at least two steatosis grades between MRI-PDFF and CAP- or UGAP-based predictions are illustrated in Fig. 3. Ten patients exhibited CAP-based grades lower than those determined by MRI-PDFF, whereas 33 patients had CAP-based grades higher than MRI-PDFF. In comparison, only four cases had UGAP-based grades lower than MRI-PDFF, and 12 had UGAP-based grades higher. Clinical variables associated with these discrepancies were assessed (Supplementary Table 3). CAP overestimation was associated with lower platelet counts, lower ALT levels, and higher MRE values, whereas CAP underestimation correlated with higher platelet counts. By contrast, no significant clinical parameters were associated with UGAP overestimation or underestimation (Supplementary Table 3).

Patients whose UGAP values exceeded CAP values did not differ significantly in baseline characteristics from those in the concordant group (Supplementary Table 4). However, a non-significant trend was observed toward higher platelet counts in the group with higher UGAP (23.0±8.17 vs. 19.9±7.05, P=0.075). Conversely, patients with lower UGAP than CAP values also showed no statistically significant differences across parameters, though there was a trend toward higher SCD (22.9±4.61 vs. 21.4±5.20, P=0.161) and lower ALT levels (37.4±22.9 vs. 53.8±47.9, P=0.157) relative to the concordant group.

Discussion

This study conducted a direct comparison between CAP and UGAP for grading hepatic steatosis in patients with chronic liver disease, using MRI-PDFF as the reference standard. Our findings showed no significant difference between CAP and UGAP for grading S3 steatosis; however, UGAP demonstrated superior performance in diagnosing S≥1 and S≥2 steatosis compared with CAP. Moreover, there were no technical failures or unreliable UGAP measurements in this study, suggesting a potential advantage of UGAP for reliable steatosis evaluation.

Accurate assessment of hepatic steatosis is essential for both clinical management of patients with chronic liver disease and for conducting epidemiological or therapeutic studies. The increasing prevalence of obesity, metabolic syndrome, and insulin resistance has reshaped the overall landscape of chronic liver disease. Approximately one-third of Japanese adults—similar to proportions in many Western countries—are affected by metabolic dysfunction-associated steatotic liver disease (MASLD) [21,22]. Despite its high prevalence, the evaluation of steatosis has long relied on conventional B-mode ultrasonography, which provides only qualitative diagnostic information. Although liver biopsy remains the reference standard for evaluating steatosis and fibrosis, its invasive nature, associated pain, and high cost limit its widespread use; moreover, the spatial heterogeneity of steatosis introduces a risk of sampling error and inaccurate assessment. According to the American Association for the Study of Liver Diseases (AASLD) guidance, liver biopsy should be reserved for cases in which advanced metabolic dysfunction-associated steatohepatitis is suspected or difficult to diagnose [23]. Recent research has highlighted the usefulness of MRI-PDFF as a noninvasive diagnostic modality for steatosis [22]. MRI-PDFF has been shown to outperform histologic assessment in quantifying steatotic changes in longitudinal studies and is now widely recognized as the gold standard for steatosis detection [24–28]. In prior investigations, MRI-PDFF was also found to be superior to VCTE-derived CAP in diagnosing steatosis grade among patients with MASLD who underwent liver biopsy [18]. MRI-PDFF represents a precise, reproducible, and reliable noninvasive biomarker for steatosis quantification. Nevertheless, despite its excellent accuracy, MRI-PDFF is not practical for large-scale or routine clinical use, owing to its high cost and limited accessibility. Therefore, a more feasible method for grading steatosis is required. An optimal noninvasive tool for steatosis evaluation should be widely available, safe, highly sensitive, quantitatively precise, reproducible, and cost-effective. Previous studies have reported excellent feasibility and diagnostic accuracy of UGAP for steatosis grading, with success rates ranging from 98.8% to 100% [12,15]. In the present study, UGAP again demonstrated a 100% success rate, independent of BMI or SCD. In a large cohort of 1,010 patients with chronic liver disease, including those with MASLD, UGAP achieved excellent diagnostic performance for detecting all grades of steatosis, with AUROC values between 0.894 and 0.912 [17]. These findings support that UGAP provides high diagnostic accuracy for steatosis grading, irrespective of liver disease etiology.

CAP has been widely used since its introduction in 2010, and numerous studies have evaluated its clinical utility [28]. However, CAP suffers from substantial overlap between adjacent steatosis grades, limiting its discriminative capacity [22]. Indeed, reported cutoff values for CAP vary markedly among studies, constraining its use for longitudinal follow-up or for monitoring therapeutic response [29]. In contrast, comparative studies of liver fat quantification based on attenuation imaging and integrated attenuation have shown that these B-mode–based techniques outperform CAP in diagnostic accuracy [30,31]. To date, only one study has directly compared the diagnostic performance of CAP and UGAP [32]. Although that study reported no significant difference in diagnostic accuracy, its conclusions were likely limited by a small sample size, reducing statistical power to detect subtle differences. The present study demonstrates, for the first time, that UGAP is superior to CAP in quantifying hepatic steatosis. This superiority may arise from several inherent limitations of CAP, including the absence of two-dimensional image guidance for morphological assessment and its sensitivity to external factors such as probe type and SCD [33]. By contrast, UGAP allows real-time, B-mode–guided imaging during measurement, which likely enhances the precision of fat quantification. Moreover, UGAP appears to exhibit greater sensitivity for detecting mild steatosis than CAP, a finding of particular clinical importance since conventional ultrasonography often fails to identify early steatosis [34]. The ability of UGAP to detect even mild fat accumulation highlights its potential as a sensitive screening tool. Another practical advantage of UGAP is that it does not require dedicated transducers or specialized hardware, facilitating easy integration into standard ultrasound systems. Given the growing global burden of MASLD, this feature underscores UGAP’s potential utility not only in specialized hepatology settings but also in large-scale, population-based screening and preventive care programs.

High BMI and SCD are significantly associated with elevated CAP and UGAP, and diagnostic accuracy tends to be lower among patients with BMI ≥30 kg/m² [17]. However, in the present study, multivariate analysis revealed no association between discrepancies in steatosis grading and either BMI or SCD. This may be attributable to the relatively small number of discrepant cases. Nonetheless, fewer discrepancies with MRI-PDFF were observed for UGAP than for CAP, suggesting potential overestimation by CAP, a finding supported by these results. Analysis of factors contributing to these discrepancies revealed that lower platelet count, reduced ALT levels, and higher MRE values—indicative of advanced fibrosis—were associated with CAP discordance. In contrast, unlike previous reports [35], no such correlations were identified for UGAP in this study. These findings imply that CAP may overestimate steatosis more frequently than UGAP and may yield higher values than MRI-PDFF. In the comparative discordance analysis between CAP and UGAP, patients with higher UGAP values than CAP showed a non-significant trend toward higher platelet counts, while those with lower UGAP values tended to have higher SCD and lower ALT levels. Although these differences did not reach statistical significance, they suggest that lesser liver disease severity and greater SCD could influence ultrasound attenuation and contribute to discrepancies between UGAP and CAP measurements.

This study has several limitations. First, the diagnosis and grading of hepatic steatosis were entirely based on MRI-PDFF without histopathological confirmation. However, according to the AASLD guidelines, liver biopsy is recommended only for patients with nonalcoholic fatty liver disease who are at increased risk of steatohepatitis or advanced fibrosis [36]. Therefore, performing liver biopsy solely for the purpose of steatosis evaluation raises ethical concerns. Second, CAP or UGAP and MRI-PDFF examinations were conducted within a 3-month interval. Although minor fluctuations in steatosis severity during this period cannot be completely excluded, such changes are unlikely, as patients’ body weights remained stable within ±5%, and no alterations were observed in alcohol consumption, physical activity, or medications related to steatosis. Third, the delineation of regions of interest for UGAP and MRI-PDFF has not yet been standardized. PDFF measurements in this study were obtained from the right hepatic lobe while avoiding vascular structures. Fourth, intra- and inter-observer variability could not be directly assessed because of the multicenter study design. Nevertheless, to minimize measurement variability, examinations with an IQR/median ratio >30% were excluded, and all operators fulfilled the minimum training criteria according to the European Federation of Societies for Ultrasound in Medicine and Biology guidelines (Supplementary Information). Fifth, as the study cohort consisted exclusively of Japanese patients with chronic liver disease, the generalizability of these findings to other ethnicities or to the general population may be limited. However, UGAP demonstrated superior diagnostic performance compared with CAP even in the subgroup of obese patients, a population more comparable to Western cohorts. These results suggest that the advantage of UGAP is not confined to Japanese cohorts but may extend across diverse populations. Given that Japanese adults typically have smaller body sizes, comparable to those of Western pediatric populations, the demonstrated efficacy of UGAP in Western children may also be applicable to Japanese adults with similar physiques. Finally, this study applied MRI-PDFF thresholds established in MASLD populations to grade steatosis in an overall cohort that included patients with non-MASLD etiologies and mild steatosis, which may introduce classification bias.

In conclusion, this multicenter prospective study demonstrated that UGAP correlates strongly with MRI-PDFF and provides high diagnostic accuracy for all grades of hepatic steatosis. Furthermore, UGAP outperformed CAP as a noninvasive diagnostic tool for hepatic steatosis, particularly for grades ≥S1 and ≥S2 (see Graphic Abstract in Supplementary Information). Discrepancies relative to MRI-PDFF were more frequent with CAP than with UGAP, suggesting that CAP may be more prone to overestimation. Further large-scale, international prospective studies are warranted to confirm these preliminary findings and validate the clinical applicability of UGAP for quantitative steatosis assessment.

Author Contributions

Conceptualization: Imajo K, Kumada T. Data acquisition: Imajo K, Toyoda H, Yasuda S, Kuroda H, Yoneda M, Kumada T. Data analysis or interpretation: Imajo K, Kumada T. Drafting of the manuscript: Imajo K, Toyoda H. Critical revision of the manuscript: Toyoda H, Nakajima A, Kumada T. Approval of the final version of the manuscript: all authors.

Conflict of Interest

No potential conflict of interest relevant to this article was reported.

Supplementary Material

Supplementary Table 1.

Diagnostic accuracy of CAP and UGAP for grading steatosis in testing set (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Table-1.pdf

Supplementary Table 2.

Diagnostic ability and optimal cut-off values of CAP and UGAP in obese patients with BMI>25 (n=174) for grading hepatic steatosis using MRI-PDFF as reference (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Table-2.pdf

Supplementary Table 3.

Factors associated with discordance between CAP or UGAP and MRI-PDFF (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Table-3.pdf

Supplementary Table 4.

Factors associated with discordance between CAP and UGAP (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Table-4.pdf

Supplementary Fig. 1.

Result of controlled attenuation parameter (CAP) (A) and region of interest (B) and attenuation map of ultrasound-guided attenuation parameter (UGAP) measurements (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Fig-1.pdf

Supplementary Fig. 2.

Normal probability plot (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Fig-2.pdf

Supplementary Fig. 3.

Study protocol (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Fig-3.pdf

Supplementary Information.

Materials/patients, methods, and results (https://doi.org/10.14366/usg.25127).

usg-25127-Supplementary-Information.pdf

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Fig. 1.

Controlled attenuation parameter (CAP, dB/m) and ultrasound-guided attenuation parameter (UGAP, dB/cm/MHz) versus magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) steatosis grades.

CAP (A) and UGAP (B) values were plotted for steatosis grades classified by MRI-PDFF. Kruskal-Wallis rank sum test; P<0.001. CAP showed a tendency toward higher values with increasing steatosis grade; however, no statistically significant difference was observed between grades 1 and 2 (P=0.086).

Fig. 2.

Area under the receiver operating characteristic curve (AUROC) values of controlled attenuation parameter (CAP) and ultrasound-guided attenuation parameter (UGAP) for diagnosing steatosis grades.

The AUROC values of CAP and UGAP for diagnosing steatosis grades ≥1 (A), >2 (B), and 3 (C) were 0.878 (95% confidence interval [CI], 0.813 to 0.923) and 0.926 (95% CI, 0.867 to 0.960), 0.820 (95% CI, 0.763 to 0.865) and 0.908 (95% CI, 0.861 to 0.940), and 0.863 (95% CI, 0.811 to 0.902) and 0.897 (95% CI, 0.853 to 0.930), respectively.

Fig. 3.

Number of cases with discordance between magnetic resonance imaging–derived proton density fat fraction (MRI-PDFF) grading and controlled attenuation parameter (CAP) or ultrasound-guided attenuation parameter (UGAP) grading.

Both CAP (A) and UGAP (B) showed a greater proportion of overestimation than underestimation compared to MRI-PDFF; however, the extent of overestimation and underestimation was lower with UGAP than with CAP.

Table 1.

Clinical and serological characteristics of patients with chronic liver disease who underwent imaging using CAP, UGAP, and MRI-PDFF

	Value (n=255)
Chronic liver disease:	196/30/12/7/6/2/2
MASLD/ALD/HBV/HCV/AIH/PBC/Others	196/30/12/7/6/2/2
Age (year)	63.0 (52.0–72.0)
Sex (male:female)	151:104
Body mass index (kg/m²)	27.1 (24.2–30.7)
Skin capsule distance (mm)	20.7 (17.7–25.0)
Platelets (×10⁴/μL)	20.2 (15.1–24.7)
AST (IU/L)	35.0 (24.0–50.3)
ALT (IU/L)	37.0 (23.0–68.5)
GGT (IU/L)	47.0 (30.0–81.0)
HbA1c (%)	6.1 (5.8–7.0)
MRE (kPa)	3.45 (2.56–4.80)
CAP (dB/m) [M/XL probe]	298.7 (256.8–331.8) [n=207/48]
MRI-PDFF (%)	10.1 (5.3–16.8)
UGAP (dB/cm/MHz)	0.74 (0.65–0.81)

Values are median (interquartile range) or number (%).

CAP, controlled attenuation parameter; UGAP, ultrasound-guided attenuation parameter; MRI-PDFF, magnetic resonance imaging–derived proton density fat fraction; MASLD, metabolic dysfunction–associated steatotic liver disease; ALD, alcohol-associated liver disease; HBV, hepatitis B virus; HCV, hepatitis C virus; AIH, autoimmune hepatitis; PBC, primary biliary cholangitis; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-glutamyl transferase; HbA1c, hemoglobin A1c; MRE, magnetic resonance elastography.

Table 2.

Associations between CAP/UGAP and clinical characteristics (n=255)

Variable	CAP			UGAP
	r	P-value		r	P-value
	Correlation coefficient	Univariate analysis	Multivariate analysis	Correlation coefficient	Univariate analysis	Multivariate analysis
Age (year)	–0.239	<0.001*	0.690	–0.277	<0.001*	0.754
Sex (male or female)	0.105	0.096	-	0.110	0.078
BMI (kg/m²)	0.480	<0.001*	0.706	0.385	<0.001*	0.907
SCD (mm)	0.528	<0.001*	<0.001*	0.387	<0.001*	0.227
Platelets (×10⁴/μL)	0.177	0.005*	0.610	0.208	<0.001*	0.384
AST (IU/L)	0.251	<0.001*	0.186	0.319	<0.001*	0.577
ALT (IU/L)	0.332	<0.001*	0.718	0.386	<0.001*	0.871
γ-GTP (IU/L)	0.136	0.032*	0.032*	0.154	0.015*	0.073
HbA1c (%)	0.153	0.002*	0.496	0.214	<0.001*	0.137
MRE (kPa)	–0.025	0.703	-	–0.051	0.431	-
MRI-LogPDFF	0.696	<0.001*	<0.001*	0.797	<0.001*	<0.001*

CAP, controlled attenuation parameter; UGAP, ultrasound-guided attenuation parameter; BMI, body mass index; SCD, skin capsule distance; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyl transferase; HbA1c, hemoglobin A1c; MRE, magnetic resonance elastography; MRI-LogPDFF, magnetic resonance imaging–log-transformed proton density fat fraction.

*Significant at P<0.05.

Table 3.

Diagnostic ability and optimal cut-off values of UGAP for grading hepatic steatosis using MRI-PDFF as reference

Steatosis grade	Steatosis grade	AUROC (95% CI)	Cut-off values	Sensitivity (95% CI)	Specificity(95% CI)	PPV (95% CI)	NPV (95% CI)
Grade ≥S1	CAP (dB/m)	0.878 (0.813–0.923)	279	83.6 (78.4–88.8)	84.2 (74.7–93.7)	94.8 (91.4–98.1)	60.0 (49.3–70.7)
	UGAP (dB/cm/MHz)	0.926 (0.867–0.960)	0.68	85.1 (80.1–90.1)	89.5 (81.5–97.4)	96.5 (93.8–99.3)	63.8 (53.2–74.3)
	P-value	0.041*		0.781	0.581	0.599	0.745
Grade ≥S2	CAP (dB/m)	0.820 (0.763–0.865)	295	83.2 (76.3–90.1)	69.8 (62.2–77.4)	69.1 (61.4–76.9)	83.6 (76.9–90.4)
	UGAP (dB/cm/MHz)	0.908 (0.861–0.940)	0.72	95.6 (91.8–99.4)	76.3 (69.2–83.3)	76.6 (69.6–83.6)	95.5 (91.6–99.4)
	P-value	<0.001*		0.004*	0.280	0.178	0.004*
Grade S3	CAP (dB/m)	0.863 (0.811–0.902)	311	90.3 (83.0–97.7)	72.6 (66.3–79.0)	51.9 (42.4–61.3)	95.8 (92.6–99.1)
	UGAP (dB/cm/MHz)	0.897 (0.853–0.930)	0.77	88.7 (80.8–96.6)	77.9 (72.0–83.8)	56.7 (46.8–66.6)	95.5 (92.2–98.8)
	P-value	0.128		>0.99	0.790	0.575	>0.99

UGAP, ultrasound-guided attenuation parameter; MRI-PDFF, magnetic resonance imaging–derived proton density fat fraction; AUROC, area under the receiver operating characteristic curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; CAP, controlled attenuation parameter.

*Significant at P<0.05.