Mathematical simulation and prediction of tumor volume using RBF artificial neural network at different circumstances in the tumor microenvironment. (November 2021)
- Record Type:
- Journal Article
- Title:
- Mathematical simulation and prediction of tumor volume using RBF artificial neural network at different circumstances in the tumor microenvironment. (November 2021)
- Main Title:
- Mathematical simulation and prediction of tumor volume using RBF artificial neural network at different circumstances in the tumor microenvironment
- Authors:
- Akbarpour Ghazani, Mehran
Saghafian, Mohsen
Jalali, Peyman
Soltani, Madjid - Abstract:
- Uncontrolled proliferation of cells in a tissue caused by genetic mutations inside a cell is referred to as a tumor. A tumor which grows rapidly encounters a barrier when it grows to a certain size in presence of preexisting vasculature. This is the time when it has to find a way to go on the growth. The tumor starts to secrete tumor angiogenic factors (TAFs) and stimulate preexisting vessels to grow new sprouts. These new sprouts will find their way to the tumor in the extracellular matrix (ECM) by the gradient of TAF. As these new capillaries anastomose and reach tumor, fresh oxygen is available for the tumor and it will reinitiate the growth. Number of initial sprouts, distance of initial tumor cells from the vessel(s) and initial density of the tumor at the time of sprout formation are questions which are to be investigated. In the present study, the aim is to find the response of tumor cells and vessels to the reciprocal effects of each other in different circumstances in the tissue. Together with a mathematical formulation, a radial basis function (RBF) neural network is established to predict the number of tumor cells at different circumstances including size and distance of initial tumors from the parent vessel. A final formulation is given for the final number of tumor cells as a function of initial tumor size and distance between a parent vessel and a tumor. Results of this simulation demonstrate that, increasing the distance between a tumor and a parent vesselUncontrolled proliferation of cells in a tissue caused by genetic mutations inside a cell is referred to as a tumor. A tumor which grows rapidly encounters a barrier when it grows to a certain size in presence of preexisting vasculature. This is the time when it has to find a way to go on the growth. The tumor starts to secrete tumor angiogenic factors (TAFs) and stimulate preexisting vessels to grow new sprouts. These new sprouts will find their way to the tumor in the extracellular matrix (ECM) by the gradient of TAF. As these new capillaries anastomose and reach tumor, fresh oxygen is available for the tumor and it will reinitiate the growth. Number of initial sprouts, distance of initial tumor cells from the vessel(s) and initial density of the tumor at the time of sprout formation are questions which are to be investigated. In the present study, the aim is to find the response of tumor cells and vessels to the reciprocal effects of each other in different circumstances in the tissue. Together with a mathematical formulation, a radial basis function (RBF) neural network is established to predict the number of tumor cells at different circumstances including size and distance of initial tumors from the parent vessel. A final formulation is given for the final number of tumor cells as a function of initial tumor size and distance between a parent vessel and a tumor. Results of this simulation demonstrate that, increasing the distance between a tumor and a parent vessel decreases the number of final tumor cells. Specially, this decrement becomes faster beyond a certain distance. Moreover, initial tumors in bigger domains must become much bigger before inducing angiogenesis which makes it harder for them to survive. … (more)
- Is Part Of:
- Proceedings of the Institution of Mechanical Engineers. Volume 235:Number 11(2021)
- Journal:
- Proceedings of the Institution of Mechanical Engineers
- Issue:
- Volume 235:Number 11(2021)
- Issue Display:
- Volume 235, Issue 11 (2021)
- Year:
- 2021
- Volume:
- 235
- Issue:
- 11
- Issue Sort Value:
- 2021-0235-0011-0000
- Page Start:
- 1335
- Page End:
- 1355
- Publication Date:
- 2021-11
- Subjects:
- Mathematical oncology -- angiogenesis -- vascular tumor -- hybrid tumor modeling -- artificial neural network -- radial basis function
Biomedical engineering -- Periodicals
Medical instruments and apparatus -- Periodicals
610.28 - Journal URLs:
- http://pih.sagepub.com/ ↗
http://journals.pepublishing.com/content/119779 ↗
http://www.uk.sagepub.com/home.nav ↗ - DOI:
- 10.1177/09544119211028380 ↗
- Languages:
- English
- ISSNs:
- 0954-4119
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17615.xml