An optical biopsy needle to diagnose cancer

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February 7, 2018
Frédéric Leblond and Joannie Desroches

Performing a biopsy can sometimes be like going fishing. It’s not easy to find the core of the tumor in order to take a small tissue sample to see if it contains cancer cells. A technology developed by engineers Frédéric Leblond and Joannie Desroches promises to revolutionize biopsies of the future in order to improve the diagnosis and treatment of cancer. 

Aiguille de biopsie

“We’ve developed an optical biopsy needle capable of immediately detecting cancerous tissue with an 84% diagnostic accuracy rate for brain cancer,” explained Leblond, a researcher at the University of Montreal Hospital Research Centre (CRCHUM) and a professor in Polytechnique Montréal’s Physics Engineering Department.

In a recent Scientific Reports article, a Nature publication, the scientists present the results of the first studies conducted with this tool, which was designed in collaboration with neurosurgeon Kevin Petrecca of the Montreal Neurological Institute and Hospital and the company Medtronic.  

“A commercial biopsy needle with an integrated Raman detection system allows us to take optical measurements when the needle is inserted into the brain, to ensure that the surgeon is removing a sample that truly represents the core of the tumour, and not healthy peripheral tissue. Our studies with animals and a dozen patients show that we can detect cancerous tissue containing more than 60% cancer cells with very good accuracy,” explained Desroches, a doctoral student in Leblond’s laboratory and the study’s first author.

“We believe that this approach will reduce the risks associated with surgical procedures and maybe one day eliminate the need to extract a tissue sample, as we will be able to determine whether there are cancer cells or not. We could potentially determine the type and grade of the tumor simply by interrogating the tissue at the tip of the needle,” pointed out Leblond.  

Currently, brain biopsies are performed using magnetic resonance imaging (MRI). Preoperative images serve as maps to guide the surgeon, who takes a tissue sample and sends it to pathology to validate the diagnosis, while the patient waits some twenty minutes on the operating table. But to get an exact picture of the cancer in question, as well as its extent and the stage of the illness, it’s important to aim accurately. Sometimes the target is missed and healthy tissue is taken. 

The method developed by Leblond’s team eliminates trial and error because it uses Raman spectroscopy technology, which detects the light scattered by the cells. Because cancer cells and normal cells react differently to the light sent, they each reveal specific molecular signatures. 

Schéma

“The engineers are now exploring artificial intelligence as a way of fine-tuning their diagnostic tool. “We are currently building a database to compare the results obtained by the probe with the pathological analyses. The goal is to be able to guide the needle to the best spot in order to make an accurate diagnosis of the tumour. This is an ambitious project, because we need hundreds of pieces of data for each type of tumour,” explained Desroches.

The researchers hope that this new diagnostic tool will be marketed within five to ten years. “If the results are positive, this approach will allow us to make diagnoses faster, more economical, more accurate and will offer a safer approach. And, most importantly, we will be able to better predict the behaviour of cancer cells and tailor monitoring and treatment accordingly,” concluded Leblond. 


Source: University of Montreal Hospital Research Centre (CRCHUM)