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使用三维计算流体动力学的快速虚拟血流储备分数

Rapid virtual fractional flow reserve using 3D computational fluid dynamics.

作者信息

Newman Thomas, Borker Raunak, Aubiniere-Robb Louise, Hendrickson Justin, Choudhury Dipankar, Halliday Ian, Fenner John, Narracott Andrew, Hose D Rodney, Gosling Rebecca, Gunn Julian P, Morris Paul D

机构信息

Department of Infection, Immunity and Cardiovascular Disease, The Medical School, University of Sheffield, Beech Hill Road, Sheffield, S10 2RX, UK.

Department of Cardiology, Sheffield Teaching Hospitals NHS Foundation Trust, Chesterman Wing, Northern General Hospital, Herries Road, Sheffield, S5 7AU, UK.

出版信息

Eur Heart J Digit Health. 2023 Apr 21;4(4):283-290. doi: 10.1093/ehjdh/ztad028. eCollection 2023 Aug.

Abstract

AIMS

Over the last ten years, virtual Fractional Flow Reserve (vFFR) has improved the utility of Fractional Flow Reserve (FFR), a globally recommended assessment to guide coronary interventions. Although the speed of vFFR computation has accelerated, techniques utilising full 3D computational fluid dynamics (CFD) solutions rather than simplified analytical solutions still require significant time to compute.

METHODS AND RESULTS

This study investigated the speed, accuracy and cost of a novel 3D-CFD software method based upon a graphic processing unit (GPU) computation, compared with the existing fastest central processing unit (CPU)-based 3D-CFD technique, on 40 angiographic cases. The novel GPU simulation was significantly faster than the CPU method (median 31.7 s (Interquartile Range (IQR) 24.0-44.4s) vs. 607.5 s (490-964 s), < 0.0001). The novel GPU technique was 99.6% (IQR 99.3-99.9) accurate relative to the CPU method. The initial cost of the GPU hardware was greater than the CPU (£4080 vs. £2876), but the median energy consumption per case was significantly less using the GPU method (8.44 (6.80-13.39) Wh vs. 2.60 (2.16-3.12) Wh, < 0.0001).

CONCLUSION

This study demonstrates that vFFR can be computed using 3D-CFD with up to 28-fold acceleration than previous techniques with no clinically significant sacrifice in accuracy.

摘要

目的

在过去十年中,虚拟血流储备分数(vFFR)提高了血流储备分数(FFR)的效用,FFR是一种全球推荐的用于指导冠状动脉介入治疗的评估方法。尽管vFFR计算速度有所加快,但利用完整三维计算流体动力学(CFD)解决方案而非简化解析解的技术仍需大量时间来计算。

方法与结果

本研究在40例血管造影病例中,将基于图形处理单元(GPU)计算的新型三维CFD软件方法与现有的最快的基于中央处理器(CPU)的三维CFD技术在速度、准确性和成本方面进行了比较。新型GPU模拟比CPU方法显著更快(中位数31.7秒(四分位间距(IQR)24.0 - 44.4秒)对607.5秒(490 - 964秒),<0.0001)。相对于CPU方法,新型GPU技术的准确率为99.6%(IQR 99.3 - 99.9)。GPU硬件的初始成本高于CPU(4080英镑对2876英镑),但使用GPU方法时每例的中位数能耗显著更低(8.44(6.80 - 13.39)瓦时对2.60(2.16 - 3.12)瓦时,<0.0001)。

结论

本研究表明,使用三维CFD计算vFFR的速度比以前的技术快28倍,且在准确性上没有临床显著牺牲。

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