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在光学相干断层扫描中使用基于相关性的方法对纤毛驱动的流体流动进行三维三矢量分量测速。

Three-dimensional, three-vector-component velocimetry of cilia-driven fluid flow using correlation-based approaches in optical coherence tomography.

作者信息

Huang Brendan K, Gamm Ute A, Bhandari Vineet, Khokha Mustafa K, Choma Michael A

机构信息

Department of Biomedical Engineering, Yale University, 55 Prospect St., New Haven, Connecticut 06520, USA.

Department of Diagnostic Radiology, Yale University, 333 Cedar St., New Haven, Connecticut 06510, USA.

出版信息

Biomed Opt Express. 2015 Aug 24;6(9):3515-38. doi: 10.1364/BOE.6.003515. eCollection 2015 Sep 1.

Abstract

Microscale quantification of cilia-driven fluid flow is an emerging area in medical physiology, including pulmonary and central nervous system physiology. Cilia-driven fluid flow is most completely described by a three-dimensional, three-component (3D3C) vector field. Here, we generate 3D3C velocimetry measurements by synthesizing higher dimensional data from lower dimensional measurements obtained using two separate optical coherence tomography (OCT)-based approaches: digital particle image velocimetry (DPIV) and dynamic light scattering (DLS)-OCT. Building on previous work, we first demonstrate directional DLS-OCT for 1D2C velocimetry measurements in the sub-1 mm/s regime (sub-2.5 inch/minute regime) of cilia-driven fluid flow in Xenopus epithelium, an important animal model of the ciliated respiratory tract. We then extend our analysis toward 3D3C measurements in Xenopus using both DLS-OCT and DPIV. We demonstrate the use of DPIV-based approaches towards flow imaging of Xenopus cerebrospinal fluid and mouse trachea, two other important ciliary systems. Both of these flows typically fall in the sub-100 μm/s regime (sub-0.25 inch/minute regime). Lastly, we develop a framework for optimizing the signal-to-noise ratio of 3D3C flow velocity measurements synthesized from 2D2C measures in non-orthogonal planes. In all, 3D3C OCT-based velocimetry has the potential to comprehensively characterize the flow performance of biological ciliated surfaces.

摘要

纤毛驱动的流体流动的微观量化是医学生理学中一个新兴的领域,包括肺和中枢神经系统生理学。纤毛驱动的流体流动最完整地由三维、三分量(3D3C)矢量场来描述。在这里,我们通过合成使用两种基于光学相干断层扫描(OCT)的单独方法获得的低维测量数据来生成3D3C测速测量结果:数字粒子图像测速法(DPIV)和动态光散射(DLS)-OCT。基于先前的工作,我们首先展示了用于非洲爪蟾上皮中纤毛驱动的流体流动的亚1毫米/秒(亚2.5英寸/分钟)范围内的一维二分量(1D2C)测速测量的定向DLS-OCT,非洲爪蟾上皮是纤毛呼吸道的一个重要动物模型。然后,我们使用DLS-OCT和DPIV将分析扩展到非洲爪蟾中的3D3C测量。我们展示了基于DPIV的方法用于非洲爪蟾脑脊液和小鼠气管的流动成像,这是另外两个重要的纤毛系统。这两种流动通常都处于亚100微米/秒(亚0.25英寸/分钟)范围内。最后,我们开发了一个框架,用于优化从非正交平面中的二维二分量(2D2C)测量合成的3D3C流速测量的信噪比。总之,基于3D3C OCT的测速法有潜力全面表征生物纤毛表面的流动性能。

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