A new laser-guided imaging technology, based on work by Indian physicist CV Raman, can make brain surgery more accurate by allowing surgeons to distinguish brain tissue from tumours at a microscopic level.
A team of University of Michigan Medical School and Harvard University researchers describes how the technique allows them to "see" the tiniest areas of tumour cells in brain tissue.
The discovery relies on Raman scattering, a physics phenomena whereby shining a laser on an object emits a unique colour pattern of scattered light that represents its chemical composition.
The phenomena is named after CV Raman, one of the Indian scientists who co-discovered the effect and shared a 1930 Nobel Prize in physics for it.
The new imaging system, dubbed Stimulated Raman Scattering (SRS) microscopy, provided a colour-coded map that the researchers used to distinguish between healthy brain tissue and gliobastoma, the most common and most lethal form of primary brain cancer.
They used this technique to distinguish tumour from healthy tissue in the brains of living mice - and then showed that the same was possible in tissue removed from a patient with glioblastoma multiforme, one of the most deadly brain tumours.
"Though brain tumour surgery has advanced in many ways, survival for many patients is still poor, in part because surgeons can't be sure that they've removed all tumour tissue before the operation is over," said co-lead author Daniel Orringer.
"We need better tools for visualising tumour during surgery, and SRS microscopy is highly promising. With SRS we can see something that's invisible through conventional surgical microscopy," he said.
Over the past 15 years, Sunney Xie from the Harvard University - the senior author of the new paper Ė has advanced the technique for high-speed chemical imaging.
By amplifying the weak Raman signal by more than 10,000 times, it is now possible to make multicolour SRS images of living tissue or other materials.
The team can even make 30 new images every second Ė the rate needed to create videos of the tissue in real time.
The technique can distinguish brain tumour from normal tissue with remarkable accuracy, by detecting the difference between the signal given off by the dense cellular structure of tumour tissue, and the normal healthy grey and white matter.
The study was published in the journal Science Translational Medicine.