Minbiao Ji Scattering Microscopy Rapid , Label-Free Detection of Brain Tumors with Stimulated Raman

glioblastoma from healthy tissue, both outside and inside the operating room. a large collection of human specimens to see whether this technology may be useful in quickly distinguishing including pseudopalisading necrosis and microvascular proliferation. The next step will be to apply SRS microscopy to patient with glioblastoma. Certain diagnostic features were present in these specimens and readily identified by SRS, colleagues showed that SRS microscopy could identify hypercellular tumor regions in fresh surgical specimens from a (H&E) staining in the clinic because it avoids artifacts inherent in imaging frozen or fixed tissues. To this end, Ji and Imaging fresh tissue slices ex vivo could also complement or perhaps replace standard hematoxylin and eosin areas that appeared normal by eye, which suggests that this tool could be applied during surgery. using an imaging window into mouse brains, the authors found that SRS microscopy could locate tumor infiltration in as well as tumors, which are full of proteins. Intraoperatively, −− lipid-rich white matter and protein-rich cortex −− tissue SRS imaging. From the resulting spectra, the authors were able to differentiate the two major components of brain cancer (glioblastoma) cells into mice, allowed them to infiltrate and grow into tumors, and then removed slices for implanted human brain et al. ''Raman spectra.'' These spectra depend on the molecular composition of the tissue. Ji In SRS microscopy, laser beams are directed at the tissue sample to generate a series of output signals called demonstrated its ability to identify malignant human brain tissue. normal tissue, Ji and colleagues developed a stimulated Raman scattering (SRS) microscopy method and behind tumor tissue can allow cancer to spread and treatment to fail. To help the surgeon clearly see tumor versus During brain tumor surgery, precision is key. Removing healthy tissue can cause neurologic deficits; leaving Virtual Histology

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