ability to distinguish and isolate rare cells from among a large
population of assorted cells has become increasingly important for the
early detection of disease and for monitoring disease treatments.
cancer tumor cells are a perfect example. 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% of
cancer mortalities. Such “rogue” cells are not limited to cancer—they
also include stem cells used for regenerative medicine and other cell
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.
Now, a new optical microscope developed by UCLA engineers could make the tough task a whole lot easier.
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. “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.”
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.
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.
technology builds on the photonic time-stretch camera technology
created by Jalali’s team in 2009 to produce the world’s fastest
In the latest issue of the journal Proceedings of the National Academy of Sciences,
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
achievement required the integration of several cutting-edge
technologies through collaborations between the departments of
bioengineering and electrical engineering and the California NanoSystems
Institute and adds to the significant technology infrastructure being
developed at UCLA for cell-based diagnostics,” Di Carlo said.
Both Jalali and Di Carlo are members of the California NanoSystems Institute at UCLA.
research demonstrates real-time identification of rare breast cancer
cells in blood with a record low false-positive rate of one cell in a
million. Preliminary results indicate that this new technology has the
potential to quickly enable the detection of rare circulating tumor
cells from a large volume of blood, opening the way for statistically
accurate early detection of cancer and for monitoring the efficiency of
drug and radiation therapy.
technology can significantly reduce errors and costs in medical
diagnosis,” said lead author Keisuke Goda, a UCLA program manager in
electrical engineering and bioengineering.
results were obtained by mixing cancer cells grown in a laboratory with
blood in various proportions to emulate real-life patient blood.
further validate the clinical utility of the technology, we are
currently performing clinical tests in collaboration with clinicians,”
said Goda, also a member of the California NanoSystems Institute. “The
technology is also potentially useful for urine analysis, water quality
monitoring and related applications.”