最小管腔分割不确定性对患者特定冠状动脉模拟的影响:FFRCT 一览

IF 2.2 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Daniel Fernández-Martínez, María Reyes González-Fernández, Juan Manuel Nogales-Asensio, Conrado Ferrera
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引用次数: 0

摘要

我们研究了最小管腔分割不确定性对冠状动脉计算机断层扫描血管造影获得的分数血流储备的影响。共有 14 个不同狭窄位置和严重程度的特定患者冠状动脉模型参与了这项研究。通过 3D-OD CFD 模拟评估了每种情况下的最佳分割冠状动脉管腔。研究结果表明,这种不确定性的敏感性随着远端狭窄严重程度的增加而增加。有中度或重度远端冠状动脉病变的病例应进行精确彻底的分割操作或有创 FFR 测量,尤其是当 FFR 值接近临界值(0.80)时。因此,我们认为在评估结果时考虑病变的位置和严重程度至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Impact of minimal lumen segmentation uncertainty on patient-specific coronary simulations: A look at FFRCT

Impact of minimal lumen segmentation uncertainty on patient-specific coronary simulations: A look at FFRCT

Impact of minimal lumen segmentation uncertainty on patient-specific coronary simulations: A look at FFRCT

We examined the effect of minimal lumen segmentation uncertainty on Fractional Flow Reserve obtained from Coronary Computed Tomography Angiography FFR CT . A total of 14 patient-specific coronary models with different stenosis locations and degrees of severity were enrolled in this study. The optimal segmented coronary lumens were disturbed using intra ± 6 % and inter-operator ± 15 % variations on the segmentation threshold. FFR CT was evaluated in each case by 3D-OD CFD simulations. The findings suggest that the sensitivity of FFR CT to this type of uncertainty increases distally and with the stenosis severity. Cases with moderate or severe distal coronary lesions should undergo either exact and thorough segmentation operations or invasive FFR measurements, particularly if the FFR CT is close to the cutoff (0.80). Therefore, we conclude that it is crucial to consider the lesion's location and degree of severity when evaluating FFR CT results.

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来源期刊
International Journal for Numerical Methods in Biomedical Engineering
International Journal for Numerical Methods in Biomedical Engineering ENGINEERING, BIOMEDICAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
4.50
自引率
9.50%
发文量
103
审稿时长
3 months
期刊介绍: All differential equation based models for biomedical applications and their novel solutions (using either established numerical methods such as finite difference, finite element and finite volume methods or new numerical methods) are within the scope of this journal. Manuscripts with experimental and analytical themes are also welcome if a component of the paper deals with numerical methods. Special cases that may not involve differential equations such as image processing, meshing and artificial intelligence are within the scope. Any research that is broadly linked to the wellbeing of the human body, either directly or indirectly, is also within the scope of this journal.
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