Department of Gastroenterology, Yokohama City University Graduate School of Medicine, Yokohama, Japan; Department of Gastroenterology, Shin-Yurigaoka General Hospital, Kawasaki, Japan.
Department of Gastroenterology and Hepatology, Ogaki Municipal Hospital, Ogaki, Japan.
Clin Gastroenterol Hepatol. 2022 Nov;20(11):2533-2541.e7. doi: 10.1016/j.cgh.2021.11.003. Epub 2021 Nov 10.
BACKGROUND & AIMS: Ultrasound-guided attenuation parameter (UGAP) is recently developed for noninvasive evaluation of steatosis. However, reports on its usefulness in clinical practice are limited. This prospective multicenter study analyzed the diagnostic accuracy of grading steatosis with reference to magnetic resonance imaging-based proton density fat fraction (MRI-PDFF), a noninvasive method with high accuracy, in a large cohort.
Altogether, 1010 patients with chronic liver disease who underwent MRI-PDFF and UGAP were recruited and prospectively enrolled from 6 Japanese liver centers. Linearity was evaluated using intraclass correlation coefficients between MRI-PDFF and UGAP values. Bias, defined as the mean difference between MRI-PDFF and UGAP values, was assessed by Bland-Altman analysis. UGAP cutoffs for pairwise MRI-PDFF-based steatosis grade were determined using area under the receiver-operating characteristic curve (AUROC) analyses.
UGAP values were shown to be normally distributed. However, because PDFF values were not normally distributed, they were log-transformed (MRI-logPDFF). UGAP values significantly correlated with MRI-logPDFF (intraclass correlation coefficient = 0.768). Additionally, Bland-Altman analysis showed good agreement between MRI-logPDFF and UGAP with a mean bias of 0.0002% and a narrow range of agreement (95% confidence interval [CI], -0.015 to 0.015). The AUROCs for distinguishing steatosis grade ≥1 (MRI-PDFF ≥5.2%), ≥2 (MRI-PDFF ≥11.3%), and 3 (MRI-PDFF ≥17.1%) were 0.910 (95% CI, 0.891-0.928), 0.912 (95% CI, 0.894-0.929), and 0.894 (95% CI, 0.873-0.916), respectively.
UGAP has excellent diagnostic accuracy for grading steatosis with reference to MRI-PDFF. Additionally, UGAP has good linearity and negligible bias, suggesting that UGAP has excellent technical performance characteristics that can be widely used in clinical trials and patient care. (UMIN Clinical Trials Registry, Number: UMIN000041196).
超声衰减参数(UGAP)是最近开发的用于非侵入性评估脂肪变性的方法。然而,关于其在临床实践中的应用的报告有限。这项前瞻性多中心研究分析了在一个大样本中,参照具有高精度的基于磁共振成像的质子密度脂肪分数(MRI-PDFF),使用 UGAP 对脂肪变性进行分级的诊断准确性。
共招募了 1010 例患有慢性肝病的患者,这些患者在 6 家日本肝脏中心进行了 MRI-PDFF 和 UGAP 检查,前瞻性地进行了研究。使用 MRI-PDFF 和 UGAP 值之间的组内相关系数评估线性关系。通过 Bland-Altman 分析评估以 MRI-PDFF 为基础的脂肪变性等级的 UGAP 截断值。
UGAP 值呈正态分布。然而,由于 PDFF 值呈非正态分布,因此对其进行了对数转换(MRI-logPDFF)。UGAP 值与 MRI-logPDFF 显著相关(组内相关系数=0.768)。此外,Bland-Altman 分析显示 MRI-logPDFF 与 UGAP 之间具有良好的一致性,平均偏差为 0.0002%,一致性范围较窄(95%置信区间[CI],-0.015 至 0.015)。用于区分脂肪变性等级≥1(MRI-PDFF≥5.2%)、≥2(MRI-PDFF≥11.3%)和≥3(MRI-PDFF≥17.1%)的 AUROCs 分别为 0.910(95%CI,0.891-0.928)、0.912(95%CI,0.894-0.929)和 0.894(95%CI,0.873-0.916)。
UGAP 参照 MRI-PDFF 对脂肪变性分级具有优异的诊断准确性。此外,UGAP 具有良好的线性关系和可忽略的偏差,表明 UGAP 具有出色的技术性能特征,可广泛应用于临床试验和患者护理。(UMIN 临床试验注册编号:UMIN000041196)。