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食管癌切除术后微血管灌注的评估:动态荧光成像的定量模型。

Estimation of microvascular perfusion after esophagectomy: a quantitative model of dynamic fluorescence imaging.

机构信息

Department of Biomedical Engineering & Physics, Amsterdam University Medical Centers, Amsterdam, The Netherlands.

Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam, The Netherlands.

出版信息

Med Biol Eng Comput. 2019 Sep;57(9):1889-1900. doi: 10.1007/s11517-019-01994-z. Epub 2019 Jun 26.

Abstract

Most common complications of esophagectomy stem from a perfusion deficiency of the gastric conduit at the anastomosis. Fluorescent tracer imaging allows intraoperative visualization of tissue perfusion. Quantitative assessment of fluorescence dynamics has the potential to identify perfusion deficiency. We developed a perfusion model to analyze the relation between fluorescence dynamics and perfusion deficiency. The model divides the gastric conduit into two well-perfused and two anastomosed sites. Hemodynamics and tracer transport were modeled. We analyzed the value of relative time-to-threshold (RTT) as a predictor of the relative remaining flow (RRF). Intensity thresholds for RTT of 20% to 50% of the maximum fluorescence intensity of the well-perfused site were tested. The relation between RTT and RRF at the anastomosed sites was evaluated over large variations of vascular conductance and volume. The ability of RTT to distinguish between sufficient and impaired perfusion was analyzed using c-statistics. We found that RTT was a valuable estimate for low RRF. The threshold of 20% of the maximum fluorescence intensity provided the best prediction of impaired perfusion on the two anastomosed sites (AUC = 0.89 and 0.86). The presented model showed that for low flows, relative time-to-threshold may be used to estimate perfusion deficiency.

摘要

食管切除术最常见的并发症源于吻合处胃管的灌注不足。荧光示踪剂成像可在术中观察组织灌注。荧光动力学的定量评估有可能识别灌注不足。我们开发了一种灌注模型来分析荧光动力学与灌注不足之间的关系。该模型将胃管分为两个灌注良好的部位和两个吻合部位。对血液动力学和示踪剂输送进行了建模。我们分析了相对达阈时间 (RTT) 作为相对剩余流量 (RRF) 预测值的价值。测试了 RTT 相对荧光强度达到最大荧光强度的 20%至 50%的强度阈值。在血管导纳和容积的较大变化范围内,评估了吻合部位 RTT 与 RRF 之间的关系。使用 C 统计量分析 RTT 区分充足和受损灌注的能力。我们发现 RTT 是低 RRF 的有价值的估计值。最大荧光强度的 20%的阈值在两个吻合部位提供了对受损灌注的最佳预测(AUC 分别为 0.89 和 0.86)。所提出的模型表明,对于低流量,相对达阈时间可用于估计灌注不足。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdda/6706368/c6b1c6af9792/11517_2019_1994_Fig1_HTML.jpg

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