Application of AI for Predictions Related to Brain Cancer

As discussed in my previous blog posts, a tool known as the Virtual Operative Assistant has been created that will allow medical students to practice surgery in a similar setting to the operating room, before they complete surgeries on actual patients (Mirchi et al., 2020). In addition to surgical training, making predictions related to a patient's prognosis, such as chance of survival, is one of the most important things for choosing the proper course of treatment. This blog post will cover another important prediction related to neuro-oncology- if a patient's tumor will metastasize to the brain.

A metastasis, or the formation of a second tumor away from the original tumor, is one of the most deadly complications that can occur from cancer. A recent study was performed in which an AI system was developed to outline characteristics of cancer cells in tissue grafts from patients that came from both the primary tumor and brain metastases (Oliver et al., 2019). A cell imaging algorithm was combined with AI and was used to study the movement of cells toward the area with damaged tissue and make out any differences between cells with and without brain metastatic potential. The device presented by the study used a 3D measurement of cancer cells behavior in a BBB, or brain-blood barrier model outside of the organism and determined which cells have brain metastatic characteristics. Cancer cells with potential to form metastatic tumors, have small particles called extracellular vesicles that can cross the blood-brain barrier allowing brain metastasis to form, a key characteristic that can help devices that use AI to predict the chance of metastasis (Oliver et al., 2019). 


In order to perform an experiment like this one, large amounts of data need to be gathered from many cells in the patient's tumor as well as from measurements of the cancer cells in the ex vivo model that were able to cross the barrier, to help identify the probability of metastases forming in the brain. Because the visual differences between cancer cells that can form metastasis in the brain and those that cannot are very small, AI can prove it be very helpful as it can combine with x-ray imaging of the BBB to accurately identify the microscopic distinctions between cells that have potential to metastasize and the cells that do not. The cells in the device were split into two subgroups that tested whether the extravasated groups of cells were a different size than the ones that had not passed through the BBB. The studies show a large difference in the behavior of cancer cells and normal cells when they came across the BBB. These differences show a possibility of extravasation occurring as a result of flexible cytoskeletons because cells need to become spherical in shape during extravasation for them to be able to cross the outer endothelial layer of the brain (Oliver et al., 2019).


The primary focus of this study was to find out if the physical characteristics of a cancer cell could determine its ability to metastasize elsewhere with the use of a special platform. The researchers believe that if cells are marked based on their characteristics and ability to pass the BBB, the AI algorithm could also predict if other cells could traverse the same barrier (Oliver et al., 2019). Medicine has great demand for a tool that can predict the potential for future brain metastases at the time of primary cancer diagnosis.This device is the perfect one for the job as it can run off of a low cost and also has a relatively fast turnaround time in addition to being able to find cancer cells that metastasized to the brain. In the future, this device could also be used to decide a course of treatment that would prevent metastases after predicting their possibility. Further use of AI, specifically in precision of screening and diagnosing lung cancer will be covered in my next blog post.




References

Mirchi, N., Bissonnette, V., Yilmaz, R., Ledwos, N., Winkler-Schwartz, A., & Del Maestro, R. (2020, February 27). The Virtual Operative Assistant: An explainable artificial intelligence tool for simulation-based training in surgery and medicine. Retrieved August 10, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7046231/

Oliver, C., Altemus, M., Westerhof, T., Cheriyan, H., Cheng, X., Dziubinski, M., . . . Merajver, S. (2019, March 27). A platform for artificial intelligence based identification of the extravasation potential of cancer cells into the brain metastatic niche. Retrieved August 24, 2020, from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510031/

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