TY - GEN
T1 - Computational modeling of cancer growth using microvascular input from in vivo microct images
AU - Zangooei, Mohammad Hossein
AU - Margolis, Ryan
AU - Hoyt, Kenneth
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/13
Y1 - 2021/4/13
N2 - Despite the number of clinical and experimental surveys, a computational model of cancer growth in which the abundance of data can be structured and understood is lacking. The goal of this project was to provide a comprehensive and expandable simulation method to predict and visualize cancer and microvascular network growth. This novel method offers the advantage of a multiscale model that incorporates data from in vivo microscale computed tomography (microCT) images of the microvasculature in breast cancer-bearing animals. We use a lattice-based model that is designed so that different evolutionary scenarios can be established to predict the impact of nutrient stress on tumor morphology and growth patterns. Overall, simulation results show tumor progression similar to that known to occur in clinical practice.
AB - Despite the number of clinical and experimental surveys, a computational model of cancer growth in which the abundance of data can be structured and understood is lacking. The goal of this project was to provide a comprehensive and expandable simulation method to predict and visualize cancer and microvascular network growth. This novel method offers the advantage of a multiscale model that incorporates data from in vivo microscale computed tomography (microCT) images of the microvasculature in breast cancer-bearing animals. We use a lattice-based model that is designed so that different evolutionary scenarios can be established to predict the impact of nutrient stress on tumor morphology and growth patterns. Overall, simulation results show tumor progression similar to that known to occur in clinical practice.
KW - Artificial intelligence
KW - Cancer growth
KW - Computational modeling
KW - Deep Q-network
KW - Medical imaging
UR - http://www.scopus.com/inward/record.url?scp=85107207318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85107207318&partnerID=8YFLogxK
U2 - 10.1109/ISBI48211.2021.9433960
DO - 10.1109/ISBI48211.2021.9433960
M3 - Conference contribution
AN - SCOPUS:85107207318
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 299
EP - 302
BT - 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
PB - IEEE Computer Society
T2 - 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
Y2 - 13 April 2021 through 16 April 2021
ER -