The acronym MRI is probably one of the most commonly quoted medical terms around. Magnetic Resonance Imaging was a revolution in healthcare when it first made its commercial appearance in 1980, following many decades of theoretical and fundamental research.
Today, these enormous machines 鈥� 鈥� are indispensable tools in the detection of a variety of diseases, most notably for many forms of cancer. Their use has become extremely common; in the US, for example, there are an estimated .
But for someone actually suffering from cancer, getting an MRI scan to monitor the progress of the disease is no small feat. Many steps are involved: book the appointment, wait for the appointment, travel to the hospital or facility, undergo the process and then wait for the results. All of these steps could represent weeks or even months of waiting, during which time the disease could have progressed, perhaps even to critical stages.
MRI power, mobile phone size
So imagine a world where you could take the power and accuracy of an MRI scan and put it in the palm of your hand. This is precisely what the MIF team MoSERS is not just proposing but has in fact already built.
This project started in bioengineering Professor Sara Mahshid鈥檚 lab and is being led by PhD candidates Mahsa Jalali and Carolina del Real Mata. From idea to development, the team established strong collaboration with Dr. Janusz Rak鈥檚 team at the MUHC and Professor Walter Reisner in the Department Physics.
The technology works by analyzing changes in extracellular vesicles (EVs) which are nano-sized cell particles within the body that act as the body鈥檚 鈥�postal system鈥�. Small changes in EVs over time offer important information on how the patient鈥檚 cells are responding to cancer treatment.
鈥淲ith this technology, we can monitor the profile of how the cancer cells are changing throughout time and in response to the therapies,鈥� explains Jalali. 鈥淭his allows for a more personalized therapy to the patient.鈥�
Operating the tiny device is simple: A small sample is taken and loaded into a microchip where EV markers are profiled. Once the EV markers have been identified, machine learning interprets how the body is responding to treatment based on the changes in markers. Results are available in a matter of minutes.
鈥淒ecision making and analysis is based on AI, which helps remove human bias and give a more assertive type of assessment,鈥� explains Carolina del Real Mata who is perfecting the machine learning aspect of the technology.
Overall, the technology will enable patients to receive better insight into how their cancer is progressing and responding to treatment. The MoSERS technology requires only a small blood sample, making it minimally invasive. The process is also less time consuming than traditional methods of cancer treatment monitoring, and thanks to the machine learning element will not require skilled operation to interpret results.
鈥淭he whole point of the test is that you can go to your local doctor鈥檚 office and get the results immediately,鈥� described del Real Mata. 鈥淵ou don鈥檛 need big, centralized facilities like hospitals. This can allow for point of care testing.鈥�
This point is furthered by Professor Mahshid who believes that one of the powers of their technology will be accessibility, even in traditionally marginalized communities.
鈥淭he end goal is to have MoSERS鈥檚 technology in the hands of healthcare providers in any location, including lower resource locations, in order to be able to monitor the wellbeing of patients regularly and make their lives easier,鈥� she said.
鈥淲e are trying to translate nanotechnology to be able to screen how the molecular profile of cancer species changes in the bloodstream and how it is affecting the body,鈥� summarized Jalali. 鈥淭his would allow us to monitor how cancer progresses in response to therapies with just a droplet of blood.鈥�
Theranos anyone?
The promise of using a single drop of blood to detect a variety of illnesses was made infamous by the case of The convicted fraudster claimed to have invented a machine that could perform over 240 medical tests with a single drop of blood.
But any comparisons with the MoSERS team end at one simple fact: 鈥淓lizabeth Holmes didn鈥檛 have a PhD and didn鈥檛 go through the process of building the technology from the ground up,鈥� said Jalali.
鈥淭here is no scientific evidence or background to what Elizabeth Holmes proposed. We are coming from a scientific research lab with work on viruses and cancers that have been peer reviewed extensively,鈥� added Professor Mahshid. 鈥淚 think that before thinking about potential commercialization, the scientific foundation should be right and that is exactly what we did.鈥�
The scientific advances made by Mahshid and her lab have been widely reported on in peer reviewed publications, including the and . Jalali and del Real Mata are driving the project鈥檚 commercialization.
鈥淚 like to support entrepreneurs from my lab to the best I can, and I am involved in commercialization on the side of the university,鈥� noted Prof Mahshid. 鈥淚t鈥檚 a very exciting path that I always try and promote in the lab, especially for students that are already involved in the technology and the patents, they can really be the driving force behind the company.鈥�
Veterans of the MIF
They are aided on their commercialization journey by the 不良研究所 Innovation Fund. The team were a part of the first cohort of the MIF with another project: , which was aimed at detecting viral infection. Applying this year as MoSERS, the team received $25,000 in the Discover stage of the MIF program.
鈥淲e need to fully automate the microchip, it鈥檚 ready to be used but still requires a skillful person to obtain the data. So, we want to fully automate the process and then move towards our first minimally viable product,鈥� explained Prof Mahshid.
鈥淭he MIF has given us the opportunity to bring in an intern to help from the business side of things, who is expanding our market research and helping us better communicate our ideas,鈥� said Jalali. 鈥淚t鈥檚 been very valuable to have her on board.鈥�
The next steps for the project include further verifying the validity of their technology with larger patient samples. Scaling up the project could eventually help the team realize their goal of putting MRI-level accuracy in the palm of your hand.
