Neurology & Neurosurgery

A new technology that combines AI with advanced optical imaging provides accurate, near real-time intraoperative diagnosis of brain tumors.

Daniel A. Orringer, MD, a neurosurgeon, expects the system to transform the conventional workflow for intraoperative histology, streamlining microscopic imaging. It may also make microscopic and genetic data more accessible to surgical teams.

During surgery, data are gathered using stimulated Raman histology (SRH), a breakthrough in optics that provides rapid, label-free, submicrometer-resolution images of unprocessed biologic tissues.

Advances in fiber-laser technology enable SRH images to be used in concert with intraoperative MRI and fluorescence-guided surgery to provide precision guidance.

Using AI algorithms, deep convolutional neural networks (CNNs) apply trainable feature extractors, which provide a learned and optimized hierarchy of image features for classification. Dr. Orringer and his team have developed a way to use CNNs to facilitate brain tumor diagnosis during surgery. Working in parallel, SRH imaging and deep CNNs predict diagnosis at the bedside.

AI algorithms currently under development may hold promise in predicting prognosis and treatment response based on a tumor’s genetic classification.

In addition, clinical trials for brain lesions increasingly incorporate an intraoperative component. Patients could potentially receive an investigational drug during surgery, Dr. Orringer says, driven by advances in AI-based diagnosis. READ THE FULL ARTICLE