Virtual Brain Tumors Could Transform How Cancer is Treated
Brain tumors, such as glioblastoma, are very hard to treat and even surgery isn’t sufficient to fully remove the tumor since tiny particles of cancerous cells remain and proliferate within a short time. However, ongoing work at Cedars-Sinai promises to transform brain cancer treatment by creating a digital twin of a patient’s tumor and then predicting how the cancer will grow and how it could respond to different therapies. In this way, treatment teams can better personalize treatments for individual patients.
At the heart of this work is Kristin Swanson, PhD, who is engaged in pioneering work that combines mathematics and neuro-oncology. The goal of this multi-disciplinary team is to make it possible to develop predictive models for disease-processes that currently seem unpredictable.
The virtual tumors that they create are based on different forms of patient data, such as biopsy information and imaging data. Using the predictive framework that they developed, Swanson’s team is able to get information about a specific tumor that couldn’t be obtained by simply looking at MRI scan results.
After feeding a patient’s data into their system, several models get to work simultaneously. One model in the system forecasts how the tumor is likely to spread and grow. Another model transforms subtle features on MRI scans into various biological signatures like immune system activity, tumor proliferation rates and cell density.
Together, the different models working simultaneously but on different aspects generate a simulation of how a patient’s tumor is likely to evolve, and how that particular tumor could respond to the different therapies being considered for that patient.
Swanson explains that those virtual tumors created behave exactly like the actual tumor in the patient. This enables the team to conduct virtual tests on how a given treatment will impact the patient’s tumor before that treatment is actually administered. In this way, patients can be spared from undergoing treatments that won’t be beneficial or that could even be counterproductive. It also saves valuable time as the most promising treatment is selected and given to the patient.
The team ensures the virtual tumors are as accurate as possible by feeding the system with any latest imaging or other patient data so that the models generate information that is relevant to the current reality of the patient.
At the moment, the team has been successful in conducting preliminary studies on their approach and they are now working to have their system approved by the FDA for use in selecting participants for different clinical trials testing brain cancer therapies. Thereafter, they hope to advance their system to the level where it can be approved for use in hospital settings so that brain tumor specialists can use it in treating patients.
As this system makes its way towards integration in patient care, brain cancer therapies like those being developed by companies like CNS Pharmaceuticals Inc. (NASDAQ: CNSP) could have a better impact if they are selected for the patients who are most likely to benefit from them.
NOTE TO INVESTORS: The latest news and updates relating to CNS Pharmaceuticals Inc. (NASDAQ: CNSP) are available in the company’s newsroom at https://ibn.fm/CNSP
Please see full terms of use and disclaimers on the BioMedWire website applicable to all content provided by BMW, wherever published or re-published: http://BMW.fm/Disclaimer
Brain tumors, such as glioblastoma, are very hard to treat and even surgery isn’t sufficient to fully remove the tumor since tiny particles of cancerous cells remain and proliferate within a short time. However, ongoing work at Cedars-Sinai promises to transform brain cancer treatment by creating a digital twin of a patient’s tumor and then predicting how the cancer will grow and how it could respond to different therapies. In this way, treatment teams can better personalize treatments for individual patients.
At the heart of this work is Kristin Swanson, PhD, who is engaged in pioneering work that combines mathematics and neuro-oncology. The goal of this multi-disciplinary team is to make it possible to develop predictive models for disease-processes that currently seem unpredictable.
The virtual tumors that they create are based on different forms of patient data, such as biopsy information and imaging data. Using the predictive framework that they developed, Swanson’s team is able to get information about a specific tumor that couldn’t be obtained by simply looking at MRI scan results.
After feeding a patient’s data into their system, several models get to work simultaneously. One model in the system forecasts how the tumor is likely to spread and grow. Another model transforms subtle features on MRI scans into various biological signatures like immune system activity, tumor proliferation rates and cell density.
Together, the different models working simultaneously but on different aspects generate a simulation of how a patient’s tumor is likely to evolve, and how that particular tumor could respond to the different therapies being considered for that patient.
Swanson explains that those virtual tumors created behave exactly like the actual tumor in the patient. This enables the team to conduct virtual tests on how a given treatment will impact the patient’s tumor before that treatment is actually administered. In this way, patients can be spared from undergoing treatments that won’t be beneficial or that could even be counterproductive. It also saves valuable time as the most promising treatment is selected and given to the patient.
The team ensures the virtual tumors are as accurate as possible by feeding the system with any latest imaging or other patient data so that the models generate information that is relevant to the current reality of the patient.
At the moment, the team has been successful in conducting preliminary studies on their approach and they are now working to have their system approved by the FDA for use in selecting participants for different clinical trials testing brain cancer therapies. Thereafter, they hope to advance their system to the level where it can be approved for use in hospital settings so that brain tumor specialists can use it in treating patients.
As this system makes its way towards integration in patient care, brain cancer therapies like those being developed by companies like CNS Pharmaceuticals Inc. (NASDAQ: CNSP) could have a better impact if they are selected for the patients who are most likely to benefit from them.
NOTE TO INVESTORS: The latest news and updates relating to CNS Pharmaceuticals Inc. (NASDAQ: CNSP) are available in the company’s newsroom at https://ibn.fm/CNSP
Please see full terms of use and disclaimers on the BioMedWire website applicable to all content provided by BMW, wherever published or re-published: http://BMW.fm/Disclaimer
