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Rapid intraoperative histology of unprocessed surgical specimens via fibre-laser-based stimulated Raman scattering microscopy

Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5612414/
https://www.ncbi.nlm.nih.gov/pubmed/28955599
http://dx.doi.org/10.1038/s41551-016-0027
Descripción
Sumario:Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method – stimulated Raman histology (SRH) – which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohen's kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.