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hospitals, remote points of care, or at
the doctor’s practice.
A concept comes alive
The idea for the high-throughput
‘cell sorter’ chip was developed
two years ago (see https://vimeo.
com/82078661 and figure2). R&D
manager Liesbet Lagae was awarded
a prestigious ERC-grant to further
develop the promising idea. And
imec scientists made the first building
blocks and integrated them in a chip
of 4cm x 2cm (figure3), with the
following process for a cell analysis:
A drop of blood is inserted into the
input channel
The cells move through a
microfluidic channel with a high speed
of a few meters per second
One by one, the cells pass over an
image sensor while they are
illuminated by a laser
Based on the holographic image on
the sensor, a powerful computation
chip reconstructs an image of each
individual cell
The cell is identified (a tumor cell,
bacteria ...)
If the cell is of a type that we want
to investigate, it is separated in a
distinct microfluidic channel. This is
done with the help of steam bubbles
generated with heating elements
In the different output channels,
the live cells are collected for further
examination
A smart combination of silicon
technology, lens free microscopy and
ultrasmall steam bubbles
The ‘cell sorter’ chip is fabricated in
silicontechnology,thesametechnology
also used to make computer and
memory chips. One of the advantages
is that all building blocks can be mass-
produced extremely compact and be
integrated in a cost-efficient way. This
cost advantage becomes even greater
if more, parallel sorting structures are
integrated on the chip.
For visualizing and identifying cells,
the cell sorter uses lens-free digital
holographic microscopy. A laser on top
of the microfluidic channel illuminates
the cells as they pass. An image
sensor placed under the channel
captures the interference pattern of
the laser light and the light that has
passed through the cells. With this
interference pattern, an image of
the cell can be reconstructed. The
image quality is comparable to that
of phase contrast microscopy. We
optimized this technology, improving
the resolution considerably by using
a light point source (which creates a
‘zoom’ effect).
Experiments with blood samples
have shown that this technique
allows to distinguish between three
major classes of white blood cells:
granulocytes,
monocytes,
and
lymphocytes. These types differ in
their size and granularity of the cell
contents. In the experiments, we
first looked at samples that contain
only one type of cell. This allowed to
optimize the classification algorithm.
Next, we analyzed a full blood sample,
with the results shown in figure 5.
These results are highly comparable
with those obtained with a clinical
hematology analyzer (figure 6), which
proves the validity of the lens-free
microscopy technique.
The microfluidic switch that we use
to separate the cells of various types
is based on small, starlike heating
elements (figure 7). Our prototype
contains 288 such elements, situated
Figure 1: ‘Cell sorter’ chip that identifies and sorts 3,000
cells per second
Figure 2: Concept of the high-throughput ‘cell
sorter’ chip
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