Engineers have developed a new optical microscope that could make the tough task of distinguishing and isolating rare cells from among a large population of assorted cells for the early detection and monitoring of cancer a whole lot easier.
Typically, there are only a handful of them among a billion healthy cells, yet they are precursors to metastasis, the spread of cancer that causes about 90 percent of cancer mortalities.
Such “rogue” cells are not limited to cancer — they also include stem cells used for regenerative medicine and other cell types.
Unfortunately, detecting such 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.
“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,” 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, said.
“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,” Jalali said.
The current flow-cytometry method has high throughput, but since 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 overcome these limitations, an interdisciplinary team of researchers led by Jalali and Dino Di Carlo, a UCLA associate professor of bioengineering, with expertise in optics and high-speed electronics, microfluidics, and biotechnology, has developed a high-throughput flow-through optical microscope with the ability to detect rare cells with sensitivity of one part per million in real time.
This technology builds on the photonic time-stretch camera technology created by Jalali’s team in 2009 to produce the world”s fastest continuous-running camera.
In the study, 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 boasts a throughput of 100,000 cells per second, approximately 100 times higher than conventional imaging-based blood analyzers.
The study has been published in the journal Proceedings of the National Academy of Sciences.