定量超声造影对脑死亡供者肝脂肪变性的诊断和分级。

IF 2.9 2区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Quantitative Imaging in Medicine and Surgery Pub Date : 2025-01-02 Epub Date: 2024-12-16 DOI:10.21037/qims-24-1004
Weiming He, Jiazhen Chen, Yuqiang Wu, Yuguang Xu, Junying Gao, Jianlong Wu, Xingwen Li, Xiaozhen Liu, Mingman Zhang, Qiang Sun
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引用次数: 0

摘要

背景:肝脂肪变性(HS)的存在是评估肝移植适宜性的重要组织学参数。然而,到目前为止,还没有研究使用超声造影(CEUS)来诊断和分级脑死亡供者的HS。本研究旨在利用超声造影检测和量化脑死亡供者的肝脏微循环灌注,并评估超声造影在HS诊断和分级中的应用。方法:本前瞻性研究纳入了2020年6月至2024年1月期间年龄≥18岁的脑死亡供者的88个肝脏(44个伴有HS, 44个不伴有HS)。献血者平均年龄45.42±9.59岁,男性70例(79.5%)。取器官前24 h对脑死亡供者肝脏进行超声造影,绘制时间-强度曲线。主要测量指标包括到达时间、到达峰时间、肝动脉峰值强度(PIHA)、门静脉峰值强度(PIPV)、肝实质峰值强度(PILP)、肝肾指数(HRI)。采用Logistic回归分析确定与HS相关的显著因素,并采用受试者工作特征曲线的曲线下面积(AUC)评价诊断效果。结论:超声造影在脑死亡供者HS的诊断和分级方面有良好的效果。PIHA是超声造影衍生的参数,可作为中重度HS的诊断工具。
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Quantitative contrast-enhanced ultrasonography in the diagnosis and grading of hepatic steatosis in brain-dead donors.

Background: The presence of hepatic steatosis (HS) is a crucial histological parameter for evaluating the suitability of liver transplantation. However, to date, no studies have used contrast-enhanced ultrasonography (CEUS) to diagnose and grade HS in brain-dead donors. This study aimed to detect and quantify hepatic microcirculatory perfusion in brain-dead donors using CEUS and to assess the utility of CEUS in the diagnosis and grading of HS.

Methods: This prospective study enrolled 88 livers from brain-dead donors (44 with HS and 44 without HS) aged ≥18 years between June 2020 and January 2024. The donors had a mean age of 45.42±9.59 years, and 70 were male (79.5%). CEUS was conducted on the livers of the brain-dead donors 24 h before organ procurement, and time-intensity curves were generated. The main measures included the arrival time, time-to-peak, peak intensity of the hepatic artery (PIHA), peak intensity of the portal vein (PIPV), and peak intensity of the liver parenchyma (PILP), and hepatorenal index (HRI). Logistic regression analyses were used to identify the significant factors associated with HS, and the areas under the curve (AUC) of the receiver operating characteristic curves were used to evaluate diagnostic performance.

Results: The PIHA (P<0.001), PIPV (P<0.001), and PILP (P=0.001) were significantly shorter in the steatosis group than the non-steatosis group. The one-way analysis of variance revealed significant decreases in the PIHA (P<0.001), PIPV (P<0.001), and PILP (P<0.001) as HS grades increased. The multivariate regression analysis indicated that the PIHA was an independent factor for both HS [odds ratio (OR) =0.97, 95% confidence interval (CI): 0.94-0.99, P=0.01] and moderate-to-severe HS (OR =0.96, 95% CI: 0.93-0.99, P=0.009). The AUC values of the PIHA and HRI for diagnosing moderate-to-severe HS were 0.88 and 0.69, respectively. The optimal cut-off value of the PIHA for diagnosing moderate-to-severe HS was 173.04, with a sensitivity of 92.9% (13 of 14 livers), specificity of 68.9% (51 of 74 livers), and positive and negative predictive values of 36.1% and 98.1%, respectively.

Conclusions: CEUS showed promising results in the diagnosis and grading of HS in brain-dead donors. The PIHA, a CEUS-derived parameter, could serve as a diagnostic tool for moderate-to-severe HS.

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Quantitative Imaging in Medicine and Surgery
Quantitative Imaging in Medicine and Surgery Medicine-Radiology, Nuclear Medicine and Imaging
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4.20
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17.90%
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252
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