健康筛查项目中定量超声波肝脂肪变性的诊断性能：一项前瞻性单中心研究。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-07-01 Epub Date: 2024-05-29 DOI:10.14366/usg.24040

Jeung Hui Pyo, Soo Jin Cho, Sung Chul Choi, Jae Hwan Jee, Jeeyeong Yun, Jeong Ah Hwang, Goeun Park, Kyunga Kim, Wonseok Kang, Mira Kang, Young Hye Byun

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引用次数: 0

摘要

目的：本研究以磁共振成像衍生质子密度脂肪分数（MRI-PDFF）为参考标准，比较了定量超声波成像（QUS）与传统超声波成像（US）在评估健康检查人群肝脂肪变性方面的诊断性能：这项单中心前瞻性研究共纳入 427 名接受腹部磁共振成像和超声波检查的人员。测量包括组织衰减成像（TAI）中的衰减系数和组织散射分布成像（TSI）中的散射分布系数。对 QUS 和 MRI-PDFF 之间的相关性进行了评估。通过分析接收者操作特征曲线下的面积，比较了 QUS、传统 B 型 US 及其组合模型检测肝脏脂肪含量≥5%（MRI-PDFF ≥5%）和≥10%（MRI-PDFF ≥10%）的诊断能力。此外，还利用多变量线性回归分析确定了影响 QUS 诊断性能的临床风险因素：结果：TAI和TSI与MRI-PDFF密切相关（分别为r=0.759和r=0.802；均为P<0.001），在肝脏脂肪变性的检测和分级方面表现出良好的诊断性能。与单独使用 TAI、TSI 或 B 型 US 相比，联合使用 QUS 和 B 型 US 可获得最高的 ROC 曲线下面积（AUCs）（检测肝脏脂肪含量≥5% 和≥10% 分别为 0.947 和 0.975；均为 P<0.05）（AUCs：检测肝脏脂肪含量≥5% 分别为 0.887、0.910、0.878，检测肝脏脂肪含量≥10% 分别为 0.951、0.922、0.875）。QUS的独立决定因素包括皮肝囊距离（β=7.134）、肝纤维化（β=4.808）、丙氨酸氨基转移酶（β=0.202）、甘油三酯水平（β=0.027）和糖尿病（β=3.710）：结论：QUS 是健康体检中检测和分级肝脂肪变性的有效筛查工具。

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Diagnostic performance of quantitative ultrasonography for hepatic steatosis in a health screening program: a prospective single-center study.

Purpose: This study compared the diagnostic performance of quantitative ultrasonography (QUS) with that of conventional ultrasonography (US) in assessing hepatic steatosis among individuals undergoing health screening using magnetic resonance imaging-derived proton density fat fraction (MRI-PDFF) as the reference standard.

Methods: This single-center prospective study enrolled 427 participants who underwent abdominal MRI and US. Measurements included the attenuation coefficient in tissue attenuation imaging (TAI) and the scatter-distribution coefficient in tissue scatter-distribution imaging (TSI). The correlation between QUS and MRI-PDFF was evaluated. The diagnostic capabilities of QUS, conventional B-mode US, and their combined models for detecting hepatic fat content of ≥5% (MRI-PDFF ≥5%) and ≥10% (MRI-PDFF ≥10%) were compared by analyzing the areas under the receiver operating characteristic curves. Additionally, clinical risk factors influencing the diagnostic performance of QUS were identified using multivariate linear regression analyses.

Results: TAI and TSI were strongly correlated with MRI-PDFF (r=0.759 and r=0.802, respectively; both P<0.001) and demonstrated good diagnostic performance in detecting and grading hepatic steatosis. The combination of QUS and B-mode US resulted in the highest areas under the ROC curve (AUCs) (0.947 and 0.975 for detecting hepatic fat content of ≥5% and ≥10%, respectively; both P<0.05), compared to TAI, TSI, or B-mode US alone (AUCs: 0.887, 0.910, 0.878 for ≥5% and 0.951, 0.922, 0.875 for ≥10%, respectively). The independent determinants of QUS included skinliver capsule distance (β=7.134), hepatic fibrosis (β=4.808), alanine aminotransferase (β=0.202), triglyceride levels (β=0.027), and diabetes mellitus (β=3.710).

Conclusion: QUS is a useful and effective screening tool for detecting and grading hepatic steatosis during health checkups.

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