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一项关于供体肝脏磁共振质子密度脂肪分数(MRI-PDFF)的离体研究,用于评估脂肪变性和预测早期移植物功能障碍。

A pilot study of ex-vivo MRI-PDFF of donor livers for assessment of steatosis and predicting early graft dysfunction.

机构信息

Division of Transplant Surgery, Methodist University Hospital Transplant Institute, Memphis, TN, United States of America.

Department of Surgery, University of Tennessee Health Science Center, Memphis, TN, United States of America.

出版信息

PLoS One. 2020 May 14;15(5):e0232006. doi: 10.1371/journal.pone.0232006. eCollection 2020.

Abstract

BACKGROUND

The utility of ex vivo Magnetic resonance imaging proton density fat fraction (MRI-PDFF) in donor liver fat quantification is unknown.

PURPOSE

To evaluate the diagnostic accuracy and utility in predicting early allograft dysfunction (EAD) of ex vivo MRI-PDFF measurement of fat in deceased donor livers using histology as the gold standard.

METHODS

We performed Ex vivo, 1.5 Tesla MRI-PDFF on 33 human deceased donor livers before implantation, enroute to the operating room. After the exclusion of 4 images (technical errors), 29 MRI images were evaluable. Histology was evaluable in 27 of 29 patients. EAD was defined as a peak value of aminotransferase >2000 IU/mL during the first week or an INR of ≥1.6 or bilirubin ≥10 mg/dL at day 7.

RESULTS

MRI-PDFF values showed a strong positive correlation (Pearson's correlation coefficient) when histology (macro-steatosis) was included (r = 0.78, 95% confidence interval 0.57-0.89, p<0.0001). The correlation appeared much stronger when macro plus micro-steatosis were included (r = 0.87, 95% confidence interval 0.72-0.94, p<0.0001). EAD was noted in 7(25%) subjects. AUC (Area Under the Curve) for macro steatosis (histology) predicted EAD in 73% (95% CI: 48-99), micro plus macro steatosis in 76% (95% CI: 49-100). AUC for PDFF values predicted EAD in 67(35-98). Comparison of the ROC curves in a multivariate model revealed, adding MRI PDFF values to macro steatosis increased the ability of the model in predicting EAD (AUC: 79%, 95% CI: 59-99), and addition of macro plus micro steatosis based on histology predicted EAD even better (AUC: 90%: 79-100, P = 0.054).

CONCLUSION

In this pilot study, MRI-PDFF imaging showed potential utility in quantifying hepatic steatosis ex-vivo donor liver evaluation and the ability to predict EAD related to severe allograft steatosis in the recipient.

摘要

背景

在供体肝脏脂肪定量中,离体磁共振成像质子密度脂肪分数(MRI-PDFF)的实用性尚不清楚。

目的

使用组织学作为金标准,评估离体 MRI-PDFF 测量供体肝脏脂肪的诊断准确性及其在预测早期移植物功能障碍(EAD)中的作用。

方法

我们在 33 例人类已故供体肝脏植入前、运往手术室的过程中进行了 1.5T 离体 MRI-PDFF 检查。排除 4 个图像(技术误差)后,可评估 29 个 MRI 图像。27 例患者的组织学可评估。EAD 定义为移植后第 1 周内转氨酶峰值>2000IU/mL 或第 7 天 INR≥1.6 或胆红素≥10mg/dL。

结果

当组织学(大脂肪变性)包括在内时,MRI-PDFF 值显示出很强的正相关(Pearson 相关系数)(r=0.78,95%置信区间 0.57-0.89,p<0.0001)。当包括大脂肪变性和微脂肪变性时,相关性更强(r=0.87,95%置信区间 0.72-0.94,p<0.0001)。7(25%)例患者出现 EAD。大脂肪变性(组织学)的 AUC(曲线下面积)预测 EAD 的准确率为 73%(95%CI:48-99),大脂肪变性加微脂肪变性预测 EAD 的准确率为 76%(95%CI:49-100)。PDFF 值的 AUC 预测 EAD 的准确率为 67%(35-98)。在多变量模型中比较 ROC 曲线发现,将 MRI PDFF 值添加到大脂肪变性中可提高模型预测 EAD 的能力(AUC:79%,95%CI:59-99),而基于组织学的大脂肪变性加微脂肪变性预测 EAD 的效果更好(AUC:90%:79-100,P=0.054)。

结论

在这项初步研究中,MRI-PDFF 成像在供体肝脏脂肪评估的离体评估中具有潜在的实用性,并能够预测受体中严重移植物脂肪变性引起的 EAD。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/006d/7224456/f2cad89e264f/pone.0232006.g001.jpg

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