Infiltrating gliomas are often difficult to distinguish from normal brain, leading to incomplete resections. Current strategies that label tumor cells suffer from inhomogeneous distribution within tumors, limited blood-brain barrier penetration, and other signal/noise and FDA approval limitations. Ji and colleagues recently reported a novel imaging technique using simulated Raman scattering (SRS) microscopy to differentiate healthy brain tissue from tumor-infiltrated brain tissue based on histoarchitectural and biochemical differences.1
SRS microscopy images biological tissues based on intrinsic components such as lipids, proteins, and DNA (Figures 1A and 1B). Different Raman spectra are seen in various brain regions due to macromolecule composition. The differential ratio of Raman signals at 2930 and 2845 cm−1 (S2930/S2845) reflects the different lipid and protein concentrations of brain regions. Highly cellular regions/solid tumors had a mean intensity ratio of S2930/S2845 = 4.0 ± 0.3, whereas normal cortex had a mean ratio of 1.6 ± 0.1, and white matter had a ratio of 0.93 ± 0.04 (Figure 1C). The authors used SRS microscopy to detect normal tissue architecture of the brain areas like the hippocampal cornus ammonis 1 (CA1) region. Unlike dye-based technologies, SRS microscopy is a label-free technique. Furthermore, SRS microscopy has 3-D capabilities, making it ideal for immediate intraoperative imaging and potentially supplanting tissue sections for neuropathologic analysis. The authors showed that 2-color SRS microscopy can detect gliomas in an ex vivo GBM xenograft mouse model. Results obtained from this technique correlated with H&E findings commonly used for GBM diagnoses.
The greatest advantage of SRS microscopy is its ability to detect tumor margins that appear normal under standard bright-field conditions. Coronal brain sections of human GBM xenografts were imaged with SRS and H&E microscopy for comparison. Compared to H&E diagnosis given by 3 different neuropathologists, SRS microscopy was 98.7% accurate (74/75) in diagnosing normal tissues, 98.7% accurate (74/75) in diagnosing infiltrating gliomas, and 100% (75/75) accurate in diagnosing high-density gliomas. The authors also tested feasibility of in vivo SRS microscopy. GBM xenografts in mice were exposed using a cranial window for SRS imaging. Although tumor was not grossly visible on the brain surface, SRS microscopy successfully detected tumor (Figure 2) that was later verified with H&E stained sections acquired from a coronal plane perpendicular to the imaging plane. SRS microscopy was also validated with fresh human GBM specimens and corresponded with H&E analysis.
SRS microscopy cannot provide all the current architectural, genetic, and biochemical data available from tissue sectioning, but potentially permits real-time discrimination of glioma boundaries and normal brain, limited to only 100 μm of spatial resolution. Furthermore, SRS microscopy image quality is affected by respiratory and cardiac cycles. Future advances in applying this technology, such as via intraoperative handheld SRS microscopy, may permit intraoperative rapid detection of residual tumor at resection edges, thereby maximizing safe surgical resection and improving glioma patient outcomes.
1. Ji M, Orringer DA, Freudiger CW, et al.. Rapid, label-free detection of brain tumors with stimulated Raman scattering microscopy. Sci Transl Med. 2013;5(201):201ra119.