High-throughput lensfree imaging and characterization of a heterogeneous cell solution on a chip.
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.
Electrical Engineering Department, University of California, P.O. Box 951594, Los Angeles, California 90095.
Ting-Wei
TW
Su
Electrical Engineering Department, University of California, P.O. Box 951594, Los Angeles, California 90095.
Sungkyu
S
Seo
Electrical Engineering Department, University of California, P.O. Box 951594, Los Angeles, California 90095.
Anthony
A
Erlinger
Electrical Engineering Department, University of California, P.O. Box 951594, Los Angeles, California 90095.|Biomedical Engineering IDP, University of California, Los Angeles, California.|California NanoSystems Institute (CNSI), University of California, Los Angeles, California.
Aydogan
A
Ozcan
D016475:3T3 Cells; D000465:Algorithms; D000818:Animals; D019992:Databases as Topic; D003663:Decision Trees; D004582:Electronics, Medical / Q000295:instrumentation / Q000379:methods; D004912:Erythrocytes / Q000166:cytology; D019044:Image Cytometry / Q000295:instrumentation* / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D056656:Lab-On-A-Chip Devices; D051379:Mice; D046208:Microchip Analytical Procedures / Q000379:methods; D008863:Microspheres; D055095:Optics and Photonics / Q000295:instrumentation / Q000379:methods; D019095:Point-of-Care Systems; D012568:Schizosaccharomyces / Q000166:cytology