Rapid Intraoperative Diagnosis of Pediatric Brain Tumors Using Stimulated Raman Histology

Todd C. Hollon, Spencer Lewis, Balaji Pandian, Yashar S. Niknafs, Mia R. Garrard, Hugh Garton, Cormac O. Maher, Kathryn McFadden, Matija Snuderl, Andrew P. Lieberman, Karin Muraszko, Sandra Camelo-Piragua, Daniel A. Orringer

Abstract:

Accurate histopathologic diagnosis is essential for providing
optimal surgical management of pediatric brain tumors. Current
methods for intraoperative histology are time- and labor-inten-
sive and often introduce artifact that limit interpretation. Stim-
ulated Raman histology (SRH) is a novel label-free imaging
technique that provides intraoperative histologic images of fresh,
unprocessed surgical specimens. Here we evaluate the capacity of
SRH for use in the intraoperative diagnosis of pediatric type brain
tumors. SRH revealed key diagnostic features in fresh tissue
specimens collected from 33 prospectively enrolled pediatric type
brain tumor patients, preserving tumor cytology and histoarch-
itecture in all specimens. We simulated an intraoperative consul-
tation for 25 patients with specimens imaged using both SRH and
standard hematoxylin and eosin histology. SRH-based diagnoses
achieved near-perfect diagnostic concordance (Cohen's kappa, k > 0.90) and an accuracy of 92% to 96%. We then developed a
quantitative histologic method using SRH images based on rapid
image feature extraction. Nuclear density, tumor-associated mac-
rophage infiltration, and nuclear morphology parameters from
3337 SRH fields of view were used to develop and validate a
decision-tree machine-learning model. Using SRH image features,
our model correctly classified 25 fresh pediatric type surgical
specimens into normal versus lesional tissue and low-grade versus
high-grade tumors with 100% accuracy. Our results provide
insight into how SRH can deliver rapid diagnostic histologic data
that could inform the surgical management of pediatric brain
tumors. Significance: A new imaging method simplifies diagnosis and
informs decision making during pediatric brain tumor surgery.