Massively Parrell Rogue Cell Detection Using Serial Time-Encoded Amplified Microscopy of Inertially Ordered Cells in High Throughput Flow

Abstract

The aim of this project is to develop an instrument for high-throughput identification of rare circulating breast cancer cells to enable early detection and analysis of treatment effectiveness. While optical microscopy is useful for detailed examination of a small number of microscopic entities and hence identification of such cells, methods for conventional microscopy are incapable of statistically relevant evaluation and screening of large populations with high accuracy due to its low throughput and limited storage. During the second year of the CDMRP project, we succeeded in demonstrating an automated flow-through single-particle optical microscope that overcomes this limitation by performing sensitive blur-free image acquisition and non-stop real-time image-recording and classification of microparticles during high-speed flow. This is made possible by integrating ultrafast optical imaging technology, self-focusing microfluidic technology, optoelectronic communication technology, and information technology. To show the system s utility, we demonstrated high-throughput imagebased screening of budding yeast and rare breast cancer cells in spiked blood with an unprecedented throughput of 100,000 particles/s and a record false positive rate of one in a million. Our results were published in Proceedings of the National Academy of Sciences in July 2012 (http://www.pnas.org/content/early/2012/06/25/1204718109) and were also featured by UCLA Newsroom (http://newsroom.ucla.edu/portal/ucla/world-s-fastest-camera-used-to-235979.aspx).

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2012
Accession Number
ADA576649

Entities

People

  • Bahram Jalali
  • Dino Di Carlo

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Advanced Electronics
  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Acquisition
  • Breast Cancer
  • Cells
  • Charge Coupled Devices
  • Classification
  • Complementary Metal-Oxide Semiconductors
  • Detection
  • Digital Images
  • Ecology
  • Fungi
  • Image Processing
  • Images
  • Microscopes
  • Microscopy
  • Optical Images
  • Particles

Readers

  • Oncology and Biomarker-Based Cancer Detection.

Technology Areas

  • Microelectronics