Quantification of liver steatosis of metabolic dysfunction-associated steatotic liver disease based on body composition analysis
Liver steatosis can be measured with ultrasound techniques such as the controlled attenuation parameter (CAP) on an equipped FibroScan. For more widespread screening and quantitative evaluation of liver steatosis, a predictive model using body composition data obtained by body bioelectrical impedance analysis (BIA) was developed. In the training cohort including 365 patients suspected of having metabolic dysfunction-associated steatotic liver disease, a stepwise selection method was used to determine the BIA-related variables associated with CAP. Using the significant variables, a predictive formula was developed, and the estimated CAP (eCAP) was obtained. The diagnostic performance of eCAP was tested to predict liver steatosis with receiver operating characteristic (ROC) curve analysis in the training, validation (n = 408) and liver biopsy (n = 158) cohorts. The body fat mass of the trunk, skeletal muscle index and age were significant variables associated with CAP. eCAP was obtained as 219.1 - 0.4479 × age + 3.476 × BFM of trunk + 7.045 × SMI. The area under the ROC curve was 0.814 in the training cohort and 0.808 in the validation cohort. The sensitivity and specificity were 72.5% and 82.1% with a cut-off value of eCAP = 281 dB/m. For sensitivity ≥ 90%, the cut-off of eCAP was 266 dB/m. In the liver biopsy cohort, the presence of pathological steatosis was predicted with eCAP as an area under the ROC curve = 0.826, which was not statistically different from CAP (0.871). Completely non-invasive BIA-based eCAP could predict liver steatosis.
Authors
- Toshikazu Kohira
- Daniel Q. Huang (ORCID: https://orcid.org/0000-0002-5165-5061)
- Nagisa Hara
- Yoshihito Kubotsu (ORCID: https://orcid.org/0000-0002-7293-0659)
- Noriko Oza
- Takuya Kuwashiro
- Satoshi Oeda (ORCID: https://orcid.org/0000-0002-0014-6275)
- Misa Norita
- Shotaro Noge
- Hiroshi Isoda (ORCID: https://orcid.org/0000-0002-8549-6492)
- Keizo Anzai (ORCID: https://orcid.org/0000-0002-8208-5321)
- Erina Eto (ORCID: https://orcid.org/0000-0001-7060-8626)
- Mark Dhinesh Muthiah (ORCID: https://orcid.org/0000-0002-9724-4743)
- Yuichiro Eguchi (ORCID: https://orcid.org/0000-0003-4693-5736)
- Kazuhiro Takahashi (ORCID: https://orcid.org/0000-0003-1900-4389)
- Cheng Han Ng (ORCID: https://orcid.org/0000-0002-8297-1569)
- Shigenobu Yoshimura (ORCID: https://orcid.org/0000-0002-9672-9095)
- Kenichi Tanaka (ORCID: https://orcid.org/0000-0003-3538-3163)
- Shinichi Aishima (ORCID: https://orcid.org/0000-0002-7319-8623)
- Atsushi Kawaguchi (ORCID: https://orcid.org/0000-0002-8911-3321)
- Kaori Inoue (ORCID: https://orcid.org/0009-0007-8770-2011)
Institutions
- Kyushu University (JP)
- National University of Singapore (SG)
- Saga University (JP)
- Saga-Ken Medical Centre Koseikan (JP)
- Noguchi Hospital (JP)
- National University Hospital (SG)
- Shirasagi Hospital (JP)
Publication Details
- Journal
- Scientific Reports
- Published
- 2025-08-30
- DOI
- https://doi.org/10.1038/s41598-025-17396-1
- Citations
- 2
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.71
Funders
- Japan Agency for Medical Research and Development
- Japan Society for the Promotion of Science