Person:

Ramkissoon, Shakti H.

Surgery is an essential component in the treatment of brain tumors. However, delineating tumor from normal brain remains a major challenge. We describe the use of stimulated Raman scattering (SRS) microscopy for differentiating healthy human and mouse brain tissue from tumor-infiltrated brain based on histoarchitectural and biochemical differences. Unlike traditional histopathology, SRS is a label-free technique that can be rapidly performed in situ. SRS microscopy was able to differentiate tumor from nonneoplastic tissue in an infiltrative human glioblastoma xenograft mouse model based on their different Raman spectra. We further demonstrated a correlation between SRS and hematoxylin and eosin microscopy for detection of glioma infiltration (κ = 0.98). Finally, we applied SRS microscopy in vivo in mice during surgery to reveal tumor margins that were undetectable under standard operative conditions. By providing rapid intraoperative assessment of brain tissue, SRS microscopy may ultimately improve the safety and accuracy of surgeries where tumor boundaries are visually indistinct.

Differentiating tumor from normal brain is a major barrier to achieving optimal outcome in brain tumor surgery. New imaging techniques for visualizing tumor margins during surgery are needed to improve surgical results. We recently demonstrated the ability of stimulated Raman scattering (SRS) microscopy, a nondestructive, label-free optical method, to reveal glioma infiltration in animal models. We show that SRS reveals human brain tumor infiltration in fresh, unprocessed surgical specimens from 22 neurosurgical patients. SRS detects tumor infiltration in near-perfect agreement with standard hematoxylin and eosin light microscopy (κ = 0.86). The unique chemical contrast specific to SRS microscopy enables tumor detection by revealing quantifiable alterations in tissue cellularity, axonal density, and protein/lipid ratio in tumor-infiltrated tissues. To ensure that SRS microscopic data can be easily used in brain tumor surgery, without the need for expert interpretation, we created a classifier based on cellularity, axonal density, and protein/lipid ratio in SRS images capable of detecting tumor infiltration with 97.5% sensitivity and 98.5% specificity. Quantitative SRS microscopy detects the spread of tumor cells, even in brain tissue surrounding a tumor that appears grossly normal. By accurately revealing tumor infiltration, quantitative SRS microscopy holds potential for improving the accuracy of brain tumor surgery.

Conventional methods for intraoperative histopathologic diagnosis are labor- and time-intensive and may delay decision-making during brain tumor surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain tumor infiltration in fresh, unprocessed human tissues. Previously, the execution of SRS microscopy in a clinical setting has not been possible. We report the first demonstration of SRS microscopy in an operating room using a portable fiber-laser-based microscope in unprocessed specimens from 101 neurosurgical patients. Additionally, we introduce an image-processing method, stimulated Raman histology (SRH), which leverages SRS images to create virtual hematoxylin and eosin- stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, the concordance of SRH and conventional histology for predicting diagnosis was nearly perfect (κ>0.89) and accuracy exceeded 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain tumor subtype with 90% accuracy. This study provides insight into how SRH can now be used to improve the surgical care of brain tumor patients.