University of Dundee, SUPA, School of Science and Engineering, Dundee, Scotland, UK.
University of Dundee, School of Medicine, Dundee, Scotland, UK.
Sci Rep. 2019 Apr 5;9(1):5742. doi: 10.1038/s41598-019-42008-0.
Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, time-resolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.
在全球范围内，前列腺癌是男性中最常见的疾病类型，仅排在肺癌之后。即使是最好的诊断标准也缺乏准确性，存在假阳性和不必要的手术干预等问题。缺乏明确的早期诊断工具是一个重大问题。我们提出了一种微流控平台，即时间分辨流体拉伸器（TR-HS），它允许每秒对数千个细胞进行非破坏性的动态力学响应研究。TR-HS 集成了高速成像和计算机视觉，能够自动检测和跟踪悬浮在流体中的单个细胞，并能够根据其力学特性对细胞进行分类。我们基于全细胞对流体力学负荷的时间分辨力学响应，证明了对健康和癌变前列腺细胞系的区分。此外，我们实施了有限元方法（FEM）模型，以描述我们设备中导致细胞变形的力。最后，我们报告了使用决策树分类器根据细胞的时间分辨圆度对这两种不同细胞群进行分类的情况。这种方法为细胞悬浮液的高通量评估提供了一种手段，可能代表了开发创新诊断设备的一种可行应用。
