CRS Neurosurgical Pathology
The goal of brain tumor surgery is to maximize tumor removal without injuring critical brain structures. Achieving this goal is challenging as it can be difficult to distinguish tumor from nontumor tissue during the surgery. Image-Guided Surgery (IGS) is being widely used for brain tumor resection. Preoperative MRI coregistered to the patient via neuronavigation systems is commonly used to guide surgery intraoperatively. However, resection of tumor tissue causes the surrounding brain to shift, which increasingly reduces spatial accuracy. In parallel, intraoperative hematoxylin and eosin (H&E)-stained cryosection is often used to provide a preliminary diagnosis. However, it is not practical to use frozen section pathology to actively guide and optimize the extent of tumor resection because the conventional H&E staining approach is too time-consuming and labor-intensive.
In 2007, our lab demonstrated that label-free coherent Raman scattering (CRS) imaging of lipid (2854 cm-1, CH2 stretching) and protein (2930 cm-1, CH3 vibration) in the fresh tissue specimen could render pathology-like images of the brain . CRS imaging can be realized with either CARS or SRS. Unlike traditional histopathology, SRS is a label-free technique that can be rapidly performed in situ. Since then, through extensive collaborations with the Departments of Neurosurgery at the Brigham and Women’s Hospital, Harvard Medical School, and the University of Michigan Medical School, we have been focusing on developing the methodology of rapid and label-free neurosurgical pathology with SRS imaging.
Video 1 shows that two-color SRS imaging (lipid, green; protein, blue) could differentiate tumor from nonneoplastic tissue in an infiltrative human glioblastoma xenograft mouse model based on their different Raman spectral features. Very fine brain structure and subcellular resolution at the tumor margin could be visualized .
By imaging fresh surgical specimens from 22 neurosurgical patients, we further show that SRS microscopy reveals tumor infiltration in near-perfect agreement with standard H&E stained light microscopy. To evaluate the ability of SRS imaging to detect microscopic infiltration within and around a brain tumor, we used a cadaveric specimen from a newly diagnosed GBM patient. A 1-cm-thick coronal section of the patient’s brain was serially sampled at the green points shown along 5-mm iso-distance lines (Fig. 1A). SRS imaging at the gross tumor margin (0 mm), 5 mm away from the tumor margin, and 15 mm away from the tumor margin reveal dense tumor, infiltrating tumor and normal tissue, validated by H&E staining, EGFR immunohistochemistry and neurofilament immunostaining (Fig. 1B) .
To further transform this technology for clinical use, we evaluated large-scale human data (4,422 fields of view of 41 entire specimens from 12 patients with a range of brain tumor types) and correlated this data with H&E staining. We investigated brain tumor tissue heterogeneity including necrosis, angiogenesis, extensive lipid droplets and collagen deposition, and irregularity and disruption of myelinated fibers. We captured and confirmed many essential diagnostic hallmarks for glioma classification. As shown in Fig. 2, cell-to-cell correlation has been achieved between label-free SRS and H&E-stained images. This work provides a significant collection of reference images (Harvard Dataverse, DOI: 10.7910/DVN/EZW4EK) for critically establishing the methodology of label-free neurosurgical pathology with SRS .
Mostly recently, we demonstrate the first application of SRS microscopy in the operating room using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRS and conventional histology for predicting diagnosis (Cohen’s kappa, κ > 0.89), with accuracy exceeding 92%. These results provide insight into how SRS microscopy could now be used to improve the surgical care of brain-tumor patients .
 Evans, Conor L.; Xu, Xiaoyin; Kesari, Santosh; Xie, X. Sunney; Wong, Stephen T.C.; Young, Geoffrey S. “Chemically-selective Imaging of Brain Structures with CARS Microscopy,” Optics Express, 15, 12076-12087 (2007).
 Ji, Minbiao; Orringer, Daniel A.; Freudiger, Christian W.; Ramkissoon, Shakti; Liu, Xiaohui; Lau, Darryl; Golby, Alexandra J.; Norton, Isaiah; Hayashi, Marika; Agar, Nathalie Y. R.; Young, Geoffrey S.; Spino, Cathie; Santagata, Sandro; Camelo-Piragua, Sandra; Ligon, Keith L.; Sagher, Oren; Xie, X. Sunney. “Rapid, Label-Free Detection of Brain Tumors with Stimulated Raman Scattering Microscopy,” Science Translational Medicine 5, 201ra119 DOI: 10.1126/scitranslmed.3005954 (2013).
 Ji, Minbiao; Lewis, Spencer; Camelo-Piragua, Sandra; Ramkissoon, Shakti H; Snuderl, Matija; Venneti, Sriram; Fisher-Hubbard, Amanda; Garrard, Mia; Fu, Dan; Wang, Anthony C; Heth, Jason A; Maher, Cormac O; Sanai, Nader; Johnson, Timothy D; Freudiger, Christian W; Sagher, Oren; Xie, X Sunney and Orringer, Daniel A “Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy,” Sci Transl Med 7(309), 309ra163, DOI:10.1126/scitranslmed.aab0195 (2015).
 Lu, Fa-Ke; Calligaris, David; Olubiyi, Olutayo I.; Norton, Isaiah; Yang, Wenlong; Santagata, Sandro; Xie, X. Sunney; Golby, Alexandra J.; Agar, Nathalie Y. R. “Label-Free Neurosurgical Pathology with Stimulated Raman Imaging,” Cancer Res 76, 3451-3462. DOI: 10.1158⁄0008-5472.CAN-16-027 (2016).
 Orringer, Daniel A.; Pandian, Balaji; Niknafs, Yashar S.; Hollon, Todd C.; Boyle, Julianne; Lewis, Spencer; Garrard, Mia; Hervey-Jumper, Shawn L.; Garton, Hugh J. L.; Maher, Cormac O.; Heth, Jason A.; Sagher, Oren; Wilkinson, D. Andrew; Snuderl, Matija; Venneti, Sriram; Ramkissoon, Shakti H.; McFadden, Kathryn A.; Fisher-Hubbard, Amanda; Lieberman, Andrew P.; Johnson, Timothy D.; Xie, X. Sunney; Trautman, Jay K.; Freudiger, Christian W.; Camelo-Piragua, Sandra. “Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy,” Nat Biomed Eng 1, 0027. DOI: DOI: 10.1038/s41551-016-0027 (2017).