Fast Camera Detects Rogue Cancer Cells

Such rogue cells are not limited to cancer–they also include stem cells used for regenerative medicine and other cell types.

An optical microscope developed by UCLA engineers could make the tough task a whole lot easier.

"To catch these elusive cells, the camera must be able to capture and digitally process millions of images continuously at a very high frame rate," said Bahram Jalali, who holds the Northrop Grumman Endowed Opto-Electronic Chair in Electrical Engineering at the UCLA Henry Samueli School of Engineering and Applied Science (Los Angeles, CA, USA). "Conventional CCD and CMOS cameras are not fast and sensitive enough. It takes time to read the data from the array of pixels, and they become less sensitive to light at high speed."

The technology builds on the photonic time-stretch camera technology created by Dr. Jalali's team in 2009 to produce the world's fastest continuous-running camera.

Detecting the cells is difficult. Achieving good statistical accuracy requires an automated, high-throughput instrument that can examine millions of cells in a reasonably short time. Microscopes equipped with digital cameras are currently the gold standard for analyzing cells, but they are too slow to be useful for this application.

The current flow-cytometry method has high throughput, but because it relies on single-point light scattering, as opposed to taking a picture, it is not sensitive enough to detect very rare cell types, such as those present in early-stage or pre-metastasis cancer patients.

"To further validate the clinical utility of the technology, we are currently performing clinical tests in collaboration with clinicians," said Keisuke Goda, a UCLA program manager in electrical engineering and bioengineering. "The technology is also potentially useful for urine analysis, water quality monitoring, and related applications."

In the July 2012 online issue of the journal Proceedings of the National Academy of Sciences of the USA (PNAS), Drs. Jalali, Di Carlo, and their colleagues describe how they integrated this camera with advanced microfluidics and real-time image processing in order to classify cells in blood samples. The new blood-screening technology has a throughput of 100,000 cells per second, approximately 100 times higher than conventional imaging-based blood analyzers.

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UCLA Henry Samueli School of Engineering and Applied Science