Abstract
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 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) - that 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.
| Original language | English (US) |
|---|---|
| Article number | 0027 |
| Journal | Nature Biomedical Engineering |
| Volume | 1 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 10 2017 |
All Science Journal Classification (ASJC) codes
- Biotechnology
- Bioengineering
- Medicine (miscellaneous)
- Biomedical Engineering
- Computer Science Applications
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