Today's workflow for determining a diagnosis during an operation
requires the surgeon wait for 30 to 40 minutes while tissue is sent to a
dedicated pathology lab for processing, sectioning, staining, mounting
The entire team in the operating room may be idle
while waiting for pathology results. A more efficient surgical procedure would save money by requiring less time in the operating room.
‘Stimulated Raman histology improved speed and diagnostic efficiency, in an operating room. This could change the pace and structure of an operation.’
Neurosurgeons and pathologists at Michigan Medicine are the first to
execute stimulated Raman histology, a method that improves speed and
diagnostic efficiency, in an operating room. They detail the advance in a
new Nature Biomedical Engineering
The researchers imaged tissue from 101 neurosurgical patients using
conventional methods and the new method. Both techniques, they found,
produced accurate results but the new method was much faster.
That, if applied widely, could change the pace and structure of an operation.
"By achieving excellent image quality in fresh tissues, we're able
to make a diagnosis during surgery," says first author Daniel A.
Orringer, assistant professor of neurosurgery at the University of
Michigan Medical School. "This eliminates the lengthy process of
sending tissues out of the OR for processing and interpretation."
"Our technique may disrupt the intraoperative diagnosis process in a
great way, reducing it from a 30-minute process to about three minutes,"
Orringer says. "Initially, we developed this technology as a means of
helping surgeons detect microscopic tumor, but we found the technology
was capable of much more than guiding surgery."
Stimulated Raman scattering microscopy, the technology behind SRH,
was developed in 2008, but the hazardous lasers it involved made it
unsuitable for use in an operating room. A clinical version has now been
developed and tested in the operating room for more than a year at U-M,
with the fiber-laser-based microscope mounted right onto a clinical
cart that plugs into the wall.
To interpret the samples, researchers developed SRH, which creates images familiar to those currently in use.
SRH uses virtual coloring to highlight the cellular and
architectural features of brain tumors, with a result resembling
traditional staining. The pathologist is then able to differentiate the
tumor tissue from normal brain as usual.
"It's very similar to what we currently do in our intraoperative
diagnosis, with the exception that the tissue is fresh, has not been
processed or stained," says senior author Sandra Camelo-Piragua, assistant professor of pathology at the U-M Medical School.
In the Nature Biomedical Engineering
were given 30 specimen samples, processed via SRH or traditional
methods. They were told the same information about each patient's
medical history and the location of the tumor and asked to make a
Those pathologists, the U-M researchers found, were equally likely
to make a correct diagnosis whether they used SRH or conventional
"SRH imaging will ensure that appropriate and good quality tissue is
collected to reach our ultimate goal: accurate diagnosis,"
As Orringer and his team continue to improve this imaging
technology, they're also teaching a computer how to use SRH images to
They built and validated a machine learning process that was able to
predict brain tumor subtype with 90 percent accuracy in a subset of 30
"The more we feed the computer, the more accurate its diagnoses will become," Orringer says.
Using SRH might also improve the workflow for facilities without
access to expert neuropathologists. Orringer notes that smaller
hospitals may be able to partner with larger systems that do have
access, since there are fewer than 800 board-certified neuropathologists
compared to the approximately 1,400 U.S. institutions performing brain
"Bringing the SRH to smaller hospitals would extend their
capabilities because the images can be interpreted remotely," he says.
Sample preparation is minimal and the SRH could quickly deliver virtual
histologic sections to aid diagnosis remotely.
The next step is a large-scale clinical trial, with an eventual goal
of showing equivalence between SRH technique for making diagnoses,
Orringer says. The prototype system is currently intended for research