NEW YORK (360Dx) – A team led by researchers at the University of Illinois at Urbana-Champaign have developed a new microscopy method that could improve label-free imaging of living tissues.
Called SLAM (simultaneous label-free autofluorescence-multiharmonic) microscopy, the approach is a version of label-free multiphoton intravital microscopy (LFM IVM), which uses a light source to stimulate molecules in a tissue of interest and microscopy to observe the autofluorescence of these molecules, allowing researchers to obtain cellular information without needing exogenous labels.
"Basically, the photons interact with the tissue, they modulate the molecules of the tissue in different ways, and then we get light signals that come back that we collect, said Stephen Boppart, professor of electrical and computer engineering at the University of Illinois and senior author on a May Nature Communications study presenting the SLAM technique.
In addition to structural information, LFM IVM captures metabolic information due to the fact that certain cellular metabolites (primarily FAD and NADH) have distinct autofluorescence signals, which lets researchers track them within the cell.
"We can get functional information about how metabolically active cells are, and that's something that can't be done with standard histology or even immunohistochemistry," Boppart said.
Researchers have developed a variety of platforms for LFM IVM, but they have faced challenges in that different molecules respond optimally to different wavelengths of light, and it has been difficult to develop a source that can simultaneously excite multiple structural and metabolic elements within a cell in a way that produces strong, distinct signals from all of them in a single experiment.
This has led some to use sequential approaches, imaging tissues twice or more to collect data on the structures and molecules of interest. However, Boppart said, the rapid pace of cellular metabolism makes this less than ideal.
"Everything changes within seconds," he said, noting that being able to excite and image a wider range of cellular features simultaneously means that "all of those different channels are co-registered in space and time."
The key innovation behind the method was development of a laser source that is able to excite multiple features effectively. As demonstrated in the Nature Communications study, the SLAM technique can simultaneously detect in real-time NADH and FAD along with noncentrosymmetric and interfacial structural features.
In an email, Emmanuel Beaurepaire, a researcher at the Ecole Polytechnique's Laboratory for Optics & Biosciences who was not involved in the SLAM work, said it was "an interesting advance for label-free IVM," noting that it had previously been difficult to efficiently combine detection of NADH with good morphologica data and that the use of a single laser makes it "a robust technique and well adapted to look at live tissues."
He added that the movies the researchers generated using the approach "are beautiful and convincing."
Beaurepaire said, however, that some combinations of features might be detected less effectively than others "because of spectral overlap." He added that because the approach uses 10MHz pulses for sample excitation compared to the more commonly used 80MHz pulses, it could be slower as "we expect the maximum detected fluorescence flux to be lower with 10 MHz compared to 80MHz excitation."
Asked how he could imagine Boppart and his colleagues improving the SLAM platform, Beaurepaire suggested that a version using multipoint excitation could speed up sample imaging. He added that a portable version of the system could be useful.
Boppart said that he and his colleagues have, in fact, built a portable system that sits on a cart, which they have used in operating rooms for analysis of breast tissue removed during tumor surgery.
"The samples are handed to us, we image them right there in the operating room, and then we hand them back to the nurses to take and send off to pathology," he said, adding that he and his colleagues are submitting a study based on this work.
"It allows us to have that real-time inter-operative view of the metabolism and the cell dynamics," he said. "The idea is that can we assess the tumor micro-environment and get a sense of how aggressive that tumor is and use that for critical assessment and staging in real time."
Boppart said that his lab planned to launch a company to commercialize the SLAM technology, though he declined to provide much detail beyond noting that though the company has not incorporated yet, it has investors and potential customers.
More generally, he said the approach could prove useful in any case where tissue is being taken out for histological assessment, providing an immediate analysis that could complement conventional histology or immunohistochemistry techniques.
He cited as an example the case of core needle biopsies.
"People take core needle biopsies of abnormal masses in the liver, or kidneys, or elsewhere, they'll do an aspirate," Boppart said. "But they don't know if they got the lesion until they send it off to pathology, and they have to wait. And there are many times where it will come back non-diagnostic or they will have missed the lesion."
"This is an opportunity in real time to be able to identify that it is or is not abnormal tissue," he said. "I think that real-time feedback [from SLAM microscopy] can add some efficiency, save some cost and time, and give some early diagnostic information."
Boppart said he and his colleagues are also working to integrate the SLAM microscopy approach with another label-free imaging technique, CARS (Coherent anti-Stokes Raman Scattering), which uses differences in the vibrations of molecules to distinguish between them.
CARS could add another layer of information to the data collected via SLAM, allowing the researchers to, for instance, distinguish between proteins and lipids or between different types of lipids, Boppart said.