Chen Jia-Liang, Duan Shao-Jie, Xie Sheng, Yao Shu-Kun
Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China.
Graduate School, Beijing University of Chinese Medicine, Beijing 100029, China.
World J Radiol. 2025 May 28;17(5):104272. doi: 10.4329/wjr.v17.i5.104272.
Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. The accuracy of noninvasive biomarkers for detecting hepatic steatosis is still limited.
To assess the diagnostic performance of noninvasive steatosis biomarkers in diagnosing NAFLD using magnetic resonance imaging proton density fat fraction (MRI-PDFF) as the gold standard.
A total of 131 suspected NAFLD patients (60% male, median age 36 years) undergoing MRI-PDFF were consecutively recruited from a tertiary hospital. Steatosis grades determined by MRI-PDFF were classified as none (< 5%), mild (5%-11%), moderate (11%-17%), and severe (≥ 17%). Six steatosis biomarkers were calculated according to clinical parameters and laboratory tests, including fatty liver index, hepatic steatosis index, ZJU index, Framingham steatosis index, triglycerides and glucose index, and visceral adiposity index. The accuracy of these biomarkers in detecting hepatic steatosis was evaluated using the area under the receiver operating characteristic curves (AUCs). The Youden index was used to determine the optimal cut-off for each biomarker. The linear trend analysis of each biomarker across the steatosis grades was conducted by Mantel-Haenszel test. Spearman's rank correlation assessed the relationship between steatosis biomarkers and MRI-PDFF.
Steatosis grades based on MRI-PDFF prevalence were: None 27%, mild 40%, moderate 15% and severe 18%. Six steatosis biomarkers showed a linear trend across the steatosis grades and a significant positive correlation with MRI-PDFF. The six steatosis biomarkers demonstrated AUCs near 0.90 (range: 0.857-0.912, all < 0.001) for diagnosing NAFLD by MRI-PDFF ≥ 5%. The optimal cut-offs showed sensitivity between 84.4%-91.7% and specificity between 71.4%-85.7%. The diagnostic performance of these biomarkers in detecting moderate-to-severe and severe steatosis was relatively weaker.
These noninvasive steatosis biomarkers accurately diagnosed NAFLD and correlated well with MRI-PDFF for detecting NAFLD, but they did not effectively detect moderate or severe steatosis.
非酒精性脂肪性肝病（NAFLD）是最常见的慢性肝病。用于检测肝脂肪变性的非侵入性生物标志物的准确性仍然有限。
以磁共振成像质子密度脂肪分数（MRI-PDFF）作为金标准，评估非侵入性脂肪变性生物标志物在诊断NAFLD中的诊断性能。
从一家三级医院连续招募了131例接受MRI-PDFF检查的疑似NAFLD患者（60%为男性，中位年龄36岁）。根据MRI-PDFF确定的脂肪变性分级分为无（<5%）、轻度（5%-11%）、中度（11%-17%）和重度（≥17%）。根据临床参数和实验室检查计算六种脂肪变性生物标志物，包括脂肪肝指数、肝脂肪变性指数、浙江大学指数、弗雷明汉姆脂肪变性指数、甘油三酯和葡萄糖指数以及内脏脂肪指数。使用受试者操作特征曲线下面积（AUC）评估这些生物标志物检测肝脂肪变性的准确性。用约登指数确定每种生物标志物的最佳截断值。通过Mantel-Haenszel检验对每种生物标志物在脂肪变性分级中的线性趋势进行分析。Spearman等级相关性评估脂肪变性生物标志物与MRI-PDFF之间的关系。
基于MRI-PDFF患病率的脂肪变性分级为：无27%，轻度40%，中度15%，重度18%。六种脂肪变性生物标志物在脂肪变性分级中呈线性趋势，且与MRI-PDFF呈显著正相关。六种脂肪变性生物标志物通过MRI-PDFF≥5%诊断NAFLD的AUC接近0.90（范围：0.857-0.912，均<0.001）。最佳截断值的敏感性在84.4%-91.7%之间，特异性在71.4%-85.7%之间。这些生物标志物在检测中度至重度和重度脂肪变性方面的诊断性能相对较弱。
这些非侵入性脂肪变性生物标志物能准确诊断NAFLD，且在检测NAFLD方面与MRI-PDFF相关性良好，但它们不能有效检测中度或重度脂肪变性。
