US researchers are using what is being billed as one of the world’s fastest cameras to identify and isolate circulating tumour cells in a blood sample.
The new system boasts a throughput of 100,000 cells per second with a false-positive rate of one cell in a million.
It could be used in the early diagnosis of cancer and for monitoring the effectiveness of drug and radiation therapy. Alternatively, it could pick out unique stem cells used for regenerative medicine.
‘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 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.’
Currently, flow cytometry is the only high-throughput method for sorting cells, 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.
For a number of years, the UCLA team has been refining its serial time-encoded amplified microscopy (STEAM) camera, which can now take 36.7 million frames every second at a shutter speed of 27 picoseconds.
In its latest work, the team integrated this camera with advanced microfluidics and real-time image processing in order to classify cells in blood samples.
‘This technology can significantly reduce errors and costs in medical diagnosis,’ said lead author Keisuke Goda, a UCLA programme manager in electrical engineering and bioengineering.