Consistency of ultrasound-derived fat fraction measurements between the right and left hepatic lobes

doi:10.3877/cma.j.issn.1672-6448.2026.06.003

Abstract

Abstract:

Objective

To explore the consistency of ultrasound-derived fat fraction (UDFF) measurements between the left and right hepatic lobes, and to evaluate its diagnostic accuracy for metabolic dysfunction-associated steatotic liver disease (MASLD), using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the reference standard.

Methods

This prospective single-center study included 101 participants who underwent both MRI-PDFF and UDFF examinations at Hangzhou First People's Hospital between February 2023 and May 2024. With MRI-PDFF as the reference standard, the intraclass correlation coefficient (ICC), Bland-Altman analysis, and receiver operating characteristic (ROC) curves were used to assess the repeatability, agreement, and diagnostic performance of UDFF.

Results

A total of 101 participants were enrolled in the final cohort (median age 34.0 years; 44 males and 57 females). The median UDFF values in the right and left lobes were 8.0% and 11.0%, respectively, with an overall median UDFF of 10.1%. UDFF measurements demonstrated excellent repeatability (ICC=0.952 for the right lobe and 0.927 for the left lobe). The agreement (ICC=0.904) and correlation (r=0.830) between right-lobe UDFF and MRI-PDFF were significantly stronger than those for the left lobe (ICC=0.836, r=0.669). Bland-Altman analysis revealed a mean bias of 2.0% for the right lobe versus 1.8% for the left lobe; however, the 95% limits of agreement (LoA) were narrower for the right lobe (20.9% vs 29.9%). Right-lobe UDFF exhibited excellent diagnostic performance for mild (AUC=0.882), moderate (AUC=0.970), and severe hepatic steatosis (AUC=0.962), with sensitivities of 78.8%, 96.2%, and 95.0%, and specificities of 93.8%, 92.0%, and 87.7%, respectively. The diagnostic performance of left-lobe UDFF was slightly inferior, with corresponding AUC values of 0.709, 0.921, and 0.942.

Conclusion

UDFF is a reliable, non-invasive tool for quantifying hepatic steatosis and provides valuable information for the clinical diagnosis and grading of MASLD. For optimal performance, measurement of the right hepatic lobe is recommended.

Key words: Metabolic dysfunction-associated steatotic liver disease, Ultrasound-derived fat fraction, Proton density fat fraction, Hepatic steatosis

Yiting Lin, Ruixiang Qi, Ting He, Liren Lu, Liqing Zhang, Lingyun Bao. Consistency of ultrasound-derived fat fraction measurements between the right and left hepatic lobes[J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2026, 23(06): 449-457.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://chaosheng.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1672-6448.2026.06.003

https://chaosheng.cma-cmc.com.cn/EN/Y2026/V23/I06/449

Figures/Tables 7

References 23

1	Wang P, Song D, Han J, et al. Comparing Three Ultrasound-Based Techniques for Diagnosing and Grading Hepatic Steatosis in Metabolic Dysfunction-Associated Steatotic Liver Disease[J]. Acad Radiol, 2025, 32(4): 1949-1957.
2	董怡, 王文平. 肝脂肪变性的超声检测技术及其应用前景[J]. 肿瘤影像学, 2023, 32(4): 317-323.
3	Kaliaev A, Chavez W, Soto J, et al. Quantitative Ultrasound Assessment of Hepatic Steatosis[J]. J Clin Exp Hepatol, 2022, 12(4): 1091-1101.
4	黄韵琳, 董怡. 非酒精性脂肪性肝病的超声无创评估技术进展[J]. 肿瘤影像学, 2023, 32(4): 386-392.
5	韩佳豪, 李嘉, 沈会明, 等. 超声衍生脂肪分数对代谢异常相关脂肪性肝病的诊断效能[J]. 中华超声影像学杂志, 2024, 33(8): 703-711.
6	张杰, 何年安. 评估超声脂肪分数对代谢相关脂肪性肝病的诊断价值[J]. 中国超声医学杂志, 2024, 40(7): 771-774.
7	Labyed Y, Milkowski A. Novel Method for Ultrasound‐Derived Fat Fraction Using an Integrated Phantom[J]. J Ultrasound in Med, 2020, 39(12): 2427-2438.
8	Dillman JR, Thapaliya S, Tkach JA, et al. Quantification of hepatic steatosis by ultrasound: prospective comparison with MRI proton density fat fraction as reference standard[J]. AJR Am J Roentgenol, 2022, 219(5): 784-791.
9	Qiao F, Xue Y, Zou C, et al. The application performance of MRI-PDFF detection values of different hepatic lobes in diagnosing liver steatosis[J]. Clin Exp Med, 2025, 25(1): 210.
10	Tang A, Desai A, Hamilton G, et al. Accuracy of MR imaging-estimated proton density fat fraction for classification of dichotomized histologic steatosis grades in nonalcoholic fatty liver disease[J]. Radiology, 2015, 274(2): 416-425.
11	Tamaki N, Ajmera V, Loomba R. Non-invasive methods for imaging hepatic steatosis and their clinical importance in NAFLD[J]. Nat Rev Endocrinol, 2022, 18(1): 55-66.
12	De Robertis R, Spoto F, Autelitano D, et al. Ultrasound-derived fat fraction for detection of hepatic steatosis and quantification of liver fat content[J]. Radiol Med, 2023, 128(10): 1174-1180.
13	Kubale R, Schneider G, Lessenich CPN, et al. Ultrasound-derived fat fraction for hepatic steatosis assessment: Prospective study of agreement with mri pdff and sources of variability in a heterogeneous population[J]. AJR Am J Roentgenol, 2024, 222(6): e2330775.
14	Bonekamp S, Tang A, Mashhood A, et al. Spatial distribution of MRI-determined hepatic proton density fat fraction in adults with nonalcoholic fatty liver disease: spatial distribution of liver fat in NAFLD[J]. J Magn Reson Imaging, 2014, 39(6): 1525-1532.
15	Hong CW, Wolfson T, Sy EZ, et al. Optimization of region‐of‐interest sampling strategies for hepatic MRI proton density fat fraction quantification[J]. J Magn Resona Imaging, 2018, 47(4): 988-994.
16	de Padua V. Alves V, Dillman JR, Trout AT. Retrospective comparison of liver chemical shift-encoded PDFF sampling strategies in children and adolescents[J]. Abdom Radiol (NY), 2022, 47(10): 3478-3484.
17	Kim KY, Song JS, Kannengiesser S, et al. Hepatic fat quantification using the proton density fat fraction (PDFF): utility of free-drawn-PDFF with a large coverage area[J]. Radiol Med, 2015, 120(12): 1083-1093.
18	Kang BK, Kim M, Song SY, et al. Feasibility of modified dixon MRI techniques for hepatic fat quantification in hepatic disorders: validation with MRS and histology[J]. Br J Radiol, 2017, 91(1089): 20170378.
19	黄韵琳, 程娟, 王颖, 等. 超声脂肪分数定量检测肝脂肪变性的可靠性研究[J]. 肿瘤影像学, 2023, 32(4): 324-327.
20	Song D, Wang P, Han J, et al. Reproducibility of ultrasound-derived fat fraction in measuring hepatic steatosis[J]. Insights Imaging, 2024, 15(1): 254.
21	Huang Y, Li J, Liu C, et al. Noninvasive quantification of hepatic steatosis using ultrasound‐derived fat fraction (CHESS2303): a prospective multicenter study[J]. MedComm (2020), 2025, 6(3): e70123.
22	Nakamura Y, Hirooka M, Koizumi Y, et al. Diagnostic accuracy of ultrasound-derived fat fraction for the detection and quantification of hepatic steatosis in patients with liver biopsy[J]. J Med Ultrason (2001), 2025, 52(1): 85-94.
23	Barr RG, Cestone A, De Silvestri A. A pre‐release algorithm with a confidence map for estimating the attenuation coefficient for liver fat quantification[J]. J Ultrasound Med, 2022, 41(8): 1939-1948.

参数	总人数（101例）	S0（16例）	S1（59例）	S2（6例）	S3（20例）	统计值	P值
年龄[岁，M（Q₁，Q₃）]	34.0（28.0，40.0）	34.5（29.8，39.5）	36.0（26.5，45.5）	32.5（32.0，34.5）	31.5（25.5，36.3）	H=4.134	0.249
性别[例（%）]						χ²=7.809	0.050
男	44（43.6）	2（12.5）	28（47.5）	3（50.0）	11（55.0）
女	57（56.4）	14（87.5）	31（52.5）	3（50.0）	9（45.0）
BMI [kg/m²，M（Q₁，Q₃）]	25.7（23.4，29.5）	22.5（20.6，24.0）	25.5（23.6，28.3）	28.4（27.0，29.9）	31.3（27.4，33.2）	H=32.151	＜0.001
UDFF [%，M（Q₁，Q₃）]
UDFF肝右叶	8.0（5.0，18.0）	4.0（3.4，5.0）	7.5（4.8，12.0）	18.5（17.6，20.1）	27.8（20.9，30.0）	H=61.045	＜0.001
UDFF肝左叶	11.0（7.0，24.0）	8.0（5.8，9.3）	10.0（6.0，16.0）	19.0（15.8，27.5）	35.0（26.8，37.5）	H=43.458	＜0.001
MRI-PDFF[%，M（Q₁，Q₃）]	10.1（7.1，17.4）	5.4（5.0，5.9）	9.3（7.8，12.5）	19.6（18.5，20.4）	30.2（27.5，34.0）	H=78.890	＜0.001

参数	总人数（101例）	S0（16例）	S1（59例）	S2（6例）	S3（20例）	统计值	P值
年龄[岁，M（Q₁，Q₃）]	34.0（28.0，40.0）	34.5（29.8，39.5）	36.0（26.5，45.5）	32.5（32.0，34.5）	31.5（25.5，36.3）	H=4.134	0.249
性别[例（%）]						χ²=7.809	0.050
男	44（43.6）	2（12.5）	28（47.5）	3（50.0）	11（55.0）
女	57（56.4）	14（87.5）	31（52.5）	3（50.0）	9（45.0）
BMI [kg/m²，M（Q₁，Q₃）]	25.7（23.4，29.5）	22.5（20.6，24.0）	25.5（23.6，28.3）	28.4（27.0，29.9）	31.3（27.4，33.2）	H=32.151	＜0.001
UDFF [%，M（Q₁，Q₃）]
UDFF肝右叶	8.0（5.0，18.0）	4.0（3.4，5.0）	7.5（4.8，12.0）	18.5（17.6，20.1）	27.8（20.9，30.0）	H=61.045	＜0.001
UDFF肝左叶	11.0（7.0，24.0）	8.0（5.8，9.3）	10.0（6.0，16.0）	19.0（15.8，27.5）	35.0（26.8，37.5）	H=43.458	＜0.001
MRI-PDFF[%，M（Q₁，Q₃）]	10.1（7.1，17.4）	5.4（5.0，5.9）	9.3（7.8，12.5）	19.6（18.5，20.4）	30.2（27.5，34.0）	H=78.890	＜0.001

部位	肝脏脂肪含量	AUC（95%CI）	截断值（%）	敏感度（%，95%CI）	特异度（%，95%CI）	PPV（%，95%CI）	NPV（%，95%CI）
肝右叶	MRI-PDFF≥6.4%	0.882（0.817~0.948）	5.8	78.8（69.0~86.2）	93.8（71.7~99.7）	98.5（91.5，100.0）	45.4（28.8,63.0）
	MRI-PDFF≥17.4%	0.970（0.941~0.998）	15.3	96.2（81.1~99.8）	92.0（83.6~96.3）	80.7（63.3，91.4）	98.6（92.2，100.0）
	MRI-PDFF≥22.1%	0.962（0.926~0.998）	16.3	95.0（76.4~99.7）	87.7（78.7~93.2）	65.5（45.4，82.0）	98.6（91.6，100.0）
肝左叶	MRI-PDFF≥6.4%	0.709（0.587~0.832）	9.3	68.2（57.7~77.2）	75.0（50.5~89.8）	93.5（84.3，98.2）	30.7（17.2,48.2）
	MRI-PDFF≥17.4%	0.921（0.867~0.975）	15.8	92.3（75.9~98.6）	76.0（65.2~84.3）	57.1（41.2，72.2）	96.6（88.3，99.7）
	MRI-PDFF≥22.1%	0.942（0.893~0.990）	15.8	100.0（83.9~100.0）	72.8（62.3~81.3）	47.6（32.3，63.6）	100（93.9，100.0）

部位	肝脏脂肪含量	AUC（95%CI）	截断值（%）	敏感度（%，95%CI）	特异度（%，95%CI）	PPV（%，95%CI）	NPV（%，95%CI）
肝右叶	MRI-PDFF≥6.4%	0.882（0.817~0.948）	5.8	78.8（69.0~86.2）	93.8（71.7~99.7）	98.5（91.5，100.0）	45.4（28.8,63.0）
	MRI-PDFF≥17.4%	0.970（0.941~0.998）	15.3	96.2（81.1~99.8）	92.0（83.6~96.3）	80.7（63.3，91.4）	98.6（92.2，100.0）
	MRI-PDFF≥22.1%	0.962（0.926~0.998）	16.3	95.0（76.4~99.7）	87.7（78.7~93.2）	65.5（45.4，82.0）	98.6（91.6，100.0）
肝左叶	MRI-PDFF≥6.4%	0.709（0.587~0.832）	9.3	68.2（57.7~77.2）	75.0（50.5~89.8）	93.5（84.3，98.2）	30.7（17.2,48.2）
	MRI-PDFF≥17.4%	0.921（0.867~0.975）	15.8	92.3（75.9~98.6）	76.0（65.2~84.3）	57.1（41.2，72.2）	96.6（88.3，99.7）
	MRI-PDFF≥22.1%	0.942（0.893~0.990）	15.8	100.0（83.9~100.0）	72.8（62.3~81.3）	47.6（32.3，63.6）	100（93.9，100.0）

[1]	Shuaiya Xu, Yuxin Zhang, Yang Wang, Qiong He, Yao Zhang. Value of a ConvNeXt deep learning model for assessing significant hepatic steatosis in liver diseases [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2026, 23(01): 15-22.
[2]	Yuanyuan Wang, Yunlin Li, Jingbo Guan, Min Sun, Yaning Xie, Dakun Zhang, Zihao Zhang. Quantitative analysis of hepatic steatosis in patients with hypertriglyceridemia using ultrasound derived fat fraction: a preliminary study [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2026, 23(01): 23-29.
[3]	Ruixia Gao, Jiahao Han, Danlei Song, Pingping Wang, Jia Li. Comparison of three ultrasound-based techniques for diagnosing hepatic steatosis in overweight people [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2025, 22(07): 600-607.
[4]	Yanan Zhao, Ming Fang, Shaoyan Xu, Shumei Wei, Hui Zhang, Yining Huang, Yajing Liu, Pintong Huang. Value of multiple acoustic technical parameters combined with serological indicators in diagnosis of hepatic steatosis [J]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2023, 20(11): 1164-1173.
[5]	Group of Surgical Operation, Group of Organ Transplantation, Society of Surgery, Chinese Medical Association. Expert consensus on assessment of donor and liver graft for split liver transplantation [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2022, 11(02): 133-138.
[6]	Group of Surgical Operation, Group of Organ Transplantation, Society of Surgery, Chinese Medical Association. Consensus and Guideline Expert consensus of split liver transplantation [J]. Chinese Journal of Hepatic Surgery(Electronic Edition), 2020, 09(05): 429-434.
[7]	Li Chen, Changqing Yang, Fengshang Zhu. Strengthen the investigation of the cross-talk mechanism between inflammatory bowel disease and metabolic dysfunction-associated steatotic liver disease [J]. Chinese Journal of Digestion and Medical Imageology(Electronic Edition), 2024, 14(05): 385-389.
[8]	Weiting Lu, Huilian Shi, Qinlei Chen, Jianhai Wu, Shaowei Liu, Fei Qiao. Characteristics of magnetic resonance imaging proton density fat fraction in patients with metabolic associated fatty liver disease [J]. Chinese Journal of Clinicians(Electronic Edition), 2021, 15(07): 503-508.
[9]	Baohua Song, Bin Wang, Qingqing Shuai, Xiuzhi Zhang. Exploring the relationship and threshold effects of lymphocyte-to-high-density lipoprotein cholesterol ratio in metabolic dysfunction-associated steatotic liver disease [J]. Chinese Journal of Obesity and Metabolic Diseases(Electronic Edition), 2026, 12(01): 1-8.
[10]	Ting Feng, Junzhao Ye. Research progress on fecal microbiota transplantation in the treatment of obesity and metabolic dysfunction-associated steatotic liver disease [J]. Chinese Journal of Obesity and Metabolic Diseases(Electronic Edition), 2024, 10(02): 138-144.

Please choose a citation manager

Content to export