Su Ting-Wei, Seo Sungkyu, Erlinger Anthony, Ozcan Aydogan
Electrical Engineering Department, University of California, P.O. Box 951594, Los Angeles, California 90095.
Biomedical Engineering IDP, University of California, Los Angeles, California.
Biotechnol Bioeng. 2009 Feb 15;102(3):856-868. doi: 10.1002/bit.22116.
A high-throughput on-chip imaging platform that can rapidly monitor and characterize various cell types within a heterogeneous solution over a depth-of-field of approximately 4 mm and a field-of-view of approximately 10 cm(2) is introduced. This powerful system can rapidly image/monitor multiple layers of cells, within a volume of approximately 4 mL all in parallel without the need for any lenses, microscope-objectives or any mechanical scanning. In this high-throughput lensless imaging scheme, the classical diffraction pattern (i.e., the shadow) of each micro-particle within the entire sample volume is detected in less than a second using an opto-electronic sensor chip. The acquired shadow image is then digitally processed using a custom developed "decision algorithm" to enable both the identification of the particle location in 3D and the characterization of each micro-particle type within the sample volume. Through experimental results, we show that different cell types (e.g., red blood cells, fibroblasts, etc.) or other micro-particles all exhibit uniquely different shadow patterns and therefore can be rapidly identified without any ambiguity using the developed decision algorithm, enabling high-throughput characterization of a heterogeneous solution. This lensfree on chip cell imaging platform shows a significant promise especially for medical diagnostic applications relevant to global health problems, where compact and cost-effective diagnostic tools are urgently needed in resource limited settings.
本文介绍了一种高通量片上成像平台,该平台能够在约4毫米的景深和大约10平方厘米的视场内,快速监测和表征异质溶液中的各种细胞类型。这个强大的系统可以在大约4毫升的体积内对多层细胞进行快速成像/监测,所有操作并行进行,无需任何透镜、显微镜物镜或任何机械扫描。在这种高通量无透镜成像方案中,使用光电传感器芯片在不到一秒的时间内检测整个样品体积内每个微粒的经典衍射图案(即阴影)。然后,使用定制开发的“决策算法”对获取的阴影图像进行数字处理,以确定微粒在三维空间中的位置,并表征样品体积内每种微粒的类型。通过实验结果,我们表明不同的细胞类型(如红细胞、成纤维细胞等)或其他微粒都呈现出独特不同的阴影图案,因此使用开发的决策算法可以快速无误地识别它们,从而实现对异质溶液的高通量表征。这种无透镜片上细胞成像平台显示出巨大的前景,特别是对于与全球健康问题相关的医学诊断应用,在资源有限的环境中迫切需要紧凑且经济高效的诊断工具。