Rapid, label-free detection of diffuse glioma recurrence using intraoperative stimulated Raman histology and deep neural networks.

ABSTRACT:

Background

Detection of glioma recurrence remains a challenge in modern neuro-oncology. Noninvasive radiographic imaging is unable to definitively differentiate true recurrence versus pseudoprogression. Even in biopsied tissue, it can be challenging to differentiate recurrent tumor and treatment effect. We hypothesized that intraoperative stimulated Raman histology (SRH) and deep neural networks can be used to improve the intraoperative detection of glioma recurrence.

Methods

We used fiber laser-based SRH, a label-free, nonconsumptive, high-resolution microscopy method (<60 sec per 1 × 1 mm2) to image a cohort of patients (n = 35) with suspected recurrent gliomas who underwent biopsy or resection. The SRH images were then used to train a convolutional neural network (CNN) an

SUBMITTER: Hollon TC 

PROVIDER: S-EPMC8631085 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature