Quantitative assessment of the generalizability of a brain tumor Raman spectroscopy machine learning model to various tumor types including astrocytoma and oligodendroglioma.

ABSTRACT:

Significance

Maximal safe resection of brain tumors can be performed by neurosurgeons through the use of accurate and practical guidance tools that provide real-time information during surgery. Current established adjuvant intraoperative technologies include neuronavigation guidance, intraoperative imaging (MRI and ultrasound), and 5-ALA for fluorescence-guided surgery.

Aim

We have developed intraoperative Raman spectroscopy as a real-time decision support system for neurosurgical guidance in brain tumors. Using a machine learning model, trained on data from a multicenter clinical study involving 67 patients, the device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. Here, the aim is to assess the generalizability of

SUBMITTER: Leblond F 

PROVIDER: S-EPMC11758428 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature