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Real-time, 3D microscopic tissue imaging could be a
revolution for medical fields such as cancer diagnosis, minimally invasive
surgery, and ophthalmology. University
of Illinois researchers
have developed a technique to computationally correct for aberrations in
optical tomography, bringing the future of medical imaging into focus.
The computational technique could provide faster, less-expensive,
and higher-resolution tissue imaging to a broader population of users. The
group describes its technique in an online early edition of the Proceedings of the National Academy of Sciences.
“Computational techniques allow you to go beyond what the
optical system can do alone, to ultimately get the best quality images and 3D
datasets,” said Steven Adie, a postdoctoral researcher at the Beckman Institute
for Advanced Science and Technology at the U. of I. “This would be very useful for real-time imaging applications such as
image-guided surgery.”
Aberrations, such as astigmatism or distortion, plague
high-resolution imaging. They make objects that should look like fine points
appear to be blobs or streaks. The higher the resolution, the worse the problem
becomes. It’s especially tricky in tissue imaging, when precision is vital to a
correct diagnosis.
Adaptive optics can correct aberrations in imaging. It’s
widely used in astronomy to correct for distortion as starlight filters through
the atmosphere. A complex system of mirrors smooth out the scattered light
before it enters the lens. Medical scientists have begun applying adaptive
optics hardware to microscopes, hoping to improve cell and tissue imaging.
“It’s the same challenge, but instead of imaging through the
atmosphere, we’re imaging through tissue, and instead of imaging a star, we’re
imaging a cell,” said Stephen Boppart, a professor of electrical and computer
engineering, of bioengineering and of internal medicine at the U. of I. “But a lot of the optical problems are the same.”
Unfortunately, hardware-based adaptive optics are
complicated, tedious to align and extremely expensive. They can only focus on
one focal plane at a time, so for tomography—3D models constructed from
sectional images as in a CT scan, for example—the mirrors have to be adjusted
and a new image scanned for each focal plane. In addition, complex corrective
systems are impractical for handheld or portable devices, such as surgical
probes or retinal scanners.
Therefore, instead of using hardware to correct a light
profile before it enters the lens, the Illinois
team uses computer software to find and correct aberrations after the image is
taken. Boppart’s group teamed up with with Scott Carney, a professor of
electrical and computer engineering and the head of the Optical Science Group
at the Beckman Institute, to develop the technique, called computational
adaptive optics. They demonstrated the technique in gel-based phantoms laced
with microparticles as well as in rat lung tissue. They scan a tissue sample
with an interferometric microscope, which is an optical imaging device using
two beams of light. The computer collects all of the data and then corrects the
images at all depths within the volume. Blurry streaks become sharp points,
features emerge from noise, and users can change parameters with the click of a
mouse.
“Being able to correct aberrations of the entire volume
helps us to get a high-resolution image anywhere in that volume,” said Adie. “Now you can see tissue structures that previously were not very clear at all.”
Computed adaptive optics can be applied to any type of
interferometric imaging, such as optical coherence tomography, and the
computations can be performed on an ordinary desktop computer, making it
accessible for many hospitals and clinics.
Next, the researchers are working to refine the algorithms
and explore applications. They are combining their computational adaptive
optics with graphics processors, looking forward to real-time in vivo applications for surgery,
minimally invasive biopsy, and more.
For example, computational adaptive optics could be very
useful for ophthalmologists. Boppart’s group previously has developed various
handheld optical tomography devices for imaging inside the eye, particularly retinal
scanning. Aberrations are very common in the human eye, making it difficult to
acquire clear images. But adaptive optics hardware is too expensive or too
complicated for most practicing ophthalmologists. With a computational
solution, many more ophthalmologists could more effectively examine and treat
their patients.
“The effectiveness is striking,” Boppart said. “Because of
the aberrations of the human eye, when you look at the retina without adaptive
optics you just see variations of light and dark areas that represent the rods
and cones. But when you use adaptive optics, you see the rods and cones as
distinct objects.”
In addition, the ability to correct data post-acquisition
allows the researchers to develop microscope systems that maximize light
collection instead of worrying about minimizing aberrations. This could lead to
better data for better image rendering.
“We are working to compute the best image possible,” said
Boppart, who also is affiliated with the Institute for Genomic Biology at the
U. of I.
