Guillermo Lorenzo et. al. Tissue-scale, personalized modeling and simulation of prostate cancer growth. Proceedings of the National Academy of Sciences, 2016; 201615791 DOI: 10.1073/pnas.1615791113
New research coauthored by Brigham Young University researchers may lead to a more accurate system for early detection, diagnosis, and treatment of prostate cancer.
The new study, published in Proceedings of the National Academy of Sciences, details a computer model that uses medical images to reproduce the growth patterns of prostate cancer on the anatomy of a patient’s prostate.
This type of mathematical modelling and simulation of disease (aka predictive medicine) can lead to personalised treatment and more accurate forecasting of clinical outcomes.
Current diagnosis methods include invasive biopsy procedures which too often lead to patients being over-treated or under-treated. Complicating matters is the fact that prostate cancer can remain undiagnosed because early stages of the disease may not produce symptoms until a tumour is either very large or has invaded other tissues.
The new system could lead to both earlier diagnosis and less invasive testing.
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