Kohira Toshikazu, Oeda Satoshi, Eto Erina, Kubotsu Yoshihito, Norita Misa, Inoue Kaori, Hara Nagisa, Noge Shotaro, Tanaka Kenichi, Yoshimura Shigenobu, Oza Noriko, Anzai Keizo, Eguchi Yuichiro, Ng Cheng Han, Huang Daniel Q, Muthiah Mark D, Kawaguchi Atsushi, Aishima Shinichi, Isoda Hiroshi, Kuwashiro Takuya, Takahashi Hirokazu
Liver Center, Saga University Hospital, Nabeshima 5-1-1, Saga City, 8498501, Saga, Japan.
Department of Clinical Gastroenterology, Eguchi Hospital, Ogi, Saga, Japan.
Sci Rep. 2025 Aug 30;15(1):31982. doi: 10.1038/s41598-025-17396-1.
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.
肝脏脂肪变性可以通过超声技术进行测量,如配备FibroScan的受控衰减参数(CAP)。为了更广泛地筛查和定量评估肝脏脂肪变性,开发了一种使用通过人体生物电阻抗分析(BIA)获得的身体成分数据的预测模型。在包括365例疑似代谢功能障碍相关脂肪性肝病患者的训练队列中,采用逐步选择法确定与CAP相关的BIA相关变量。利用这些显著变量,开发了一个预测公式,并获得了估计的CAP(eCAP)。在训练、验证(n = 408)和肝活检(n = 158)队列中,通过受试者操作特征(ROC)曲线分析测试了eCAP预测肝脏脂肪变性的诊断性能。躯干体脂质量、骨骼肌指数和年龄是与CAP相关的显著变量。eCAP的计算公式为219.1 - 0.4479×年龄 + 3.476×躯干BFM + 7.045×SMI。训练队列中ROC曲线下面积为0.814,验证队列中为0.808。当eCAP = 281 dB/m为临界值时,灵敏度和特异度分别为72.5%和82.1%。对于灵敏度≥90%,eCAP的临界值为266 dB/m。在肝活检队列中,eCAP预测病理脂肪变性的ROC曲线下面积为0.826,与CAP(0.871)无统计学差异。完全基于非侵入性BIA的eCAP可以预测肝脏脂肪变性。