When brain tumours recur, survival rates go down, and patients with the most lethal tumour type often die within a year.

That’s because cancerous tissue is left behind after the initial surgery, and it continues to grow, sometimes even faster than the original tumour.

Now a new study, led by UC San Francisco and University of Michigan, has demonstrated that using an artificial intelligence (AI)-powered diagnostic tool helps neurosurgeons identify invisible cancer that has spread nearby.

The technique has the potential to delay the recurrence of high-grade tumours and it could prevent it in lower-grade tumours.

Similar AI techniques will be tested in surgeries for breast, lung, prostate, and head and neck cancers, according to the study, which appears in Nature.

“This technique will improve our ability to identify tumours and hopefully improve survival due to the added tumour being removed,” said senior author Shawn Hervey-Jumper, MD, of the UCSF Department of Neurological Surgery and the Weill Institute for Neurosciences.

“This model provides physicians with real-time, accurate and clinically actionable diagnostic information within seconds of tissue biopsy.”

The tool, which is open source and patented by UCSF, is known as FastGlioma, and has not yet been approved by the Food and Drug Administration.

In the study, neurosurgeons examined tumour samples from 220 patients with high-grade and low-grade diffuse glioma, the most common type of adult brain tumour.

They found that 3.8% of patients for whom FastGlioma had been applied had remaining high-risk tissue, compared with 24% of patients for whom the tool had not been applied.

“FastGlioma has the potential to change the field of neurosurgery by immediately improving comprehensive management of patients with glioma,” said senior author Todd Hollon, MD, of the Department of Neurosurgery at University of Michigan.

“The technology works faster and more accurately than current standards of care methods for tumour detection and could be generalised to other paediatric and adult brain tumour diagnoses.”

FastGlioma works by combining the predictive power of AI with stimulated Raman histology (SRH), an imaging technology that visualises fresh tissue samples at the bedside within one-to-two minutes.

This eliminates time-consuming processing and interpretation of tumour cells in pathology labs.

The AI system is “trained” on a dataset of more than 11,000 tumour specimens and 4 million microscopic views.

This allows it to classify images and distinguish between tumour and healthy tissue with a high degree of accuracy.

Neurosurgeons receive diagnostic information in 10 seconds, enabling them to continue with surgery if required.

“If surgery to remove residual cells cannot be performed, other therapeutic options can be immediately considered,” said Hervey-Jumper.

“These include focal therapies like radiation or targeted chemotherapy in which treatment is delivered via catheter directly to the brain.”

Source: University of California - San Francisco