Unknown

Dataset Information

0

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


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 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, ? > 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.

SUBMITTER: Orringer DA 

PROVIDER: S-EPMC5612414 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

altmetric image

Publications


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 neur  ...[more]

Similar Datasets

| S-EPMC4193905 | biostudies-literature
| S-EPMC6938502 | biostudies-literature
| S-EPMC6526002 | biostudies-literature
| S-EPMC10114931 | biostudies-literature
| S-EPMC5587718 | biostudies-literature
| S-EPMC5844703 | biostudies-literature
| S-EPMC3396204 | biostudies-literature
| S-EPMC6103005 | biostudies-literature
| S-EPMC8149663 | biostudies-literature
| S-EPMC6059832 | biostudies-other