Modeling dose‐painting effects in radiotherapy by means of an agent based model
Last modified: 2014-06-09
Abstract
Radiotherapy, the use of ionizing radiation to eliminate pathological tissues, is a treatment
of choice for more than 50% of patients diagnosed with solid tumors. Technical and
methodological advances have allowed radiation oncology to achieve local tumor control in
a considerable number of patients. However, locoregional recurrence (LRR) after treatment
remains a problem in many clinical settings. For instance, In Glioblastoma Multiforme
(GBM), the most common and aggressive malignant primary brain tumor, LRR occurs in
about 90% of cases. Such recurrence is often associated to the onset of radioresistance and
is strongly correlated with the development of significant intratumoral heterogeneity.
Unfortunately, current medical techniques are unable to deduce sufficient information
about tumor heterogeneity by means of non‐invasive methods.
In this talk a mathematical model for heterogeneous tumor growth is proposed, and the
effects of different homogeneous and heterogeneous radiation dose distributions are
investigated by means of computer simulations [1]. Specifically, an individual cell‐based
model is considered for a simplified situation where two different tumor cell phenotypes
corresponding to GBM cell lines coexist in a tumor, which we assume to strongly differ in
their respective cell cycle duration and radiosensitivity properties. As a consequence of such
differences, the spatial distribution of the corresponding phenotypes, whence the resulting
tumor heterogeneity can be predicted as growth proceeds. Moreover, heterogeneous
dosimetries can be selected to enhance tumor control by boosting radiation in the region
occupied by the more radioresistant tumor cell phenotype. When compared with
homogeneous dose distributions currently delivered in clinical practice, such heterogeneous
radiation dosimetries always yield better results than their homogeneous counterparts.
[1] J. C. L. Alfonso, N. Jagiella, L. Núñez, M. A. Herrero, D. Drasdo (2014) Estimating Dose
Painting Effects in Radiotherapy: A Mathematical Model. PLoS ONE 9(2): e89380. doi:
10.1371/journal.pone.0089380.
of choice for more than 50% of patients diagnosed with solid tumors. Technical and
methodological advances have allowed radiation oncology to achieve local tumor control in
a considerable number of patients. However, locoregional recurrence (LRR) after treatment
remains a problem in many clinical settings. For instance, In Glioblastoma Multiforme
(GBM), the most common and aggressive malignant primary brain tumor, LRR occurs in
about 90% of cases. Such recurrence is often associated to the onset of radioresistance and
is strongly correlated with the development of significant intratumoral heterogeneity.
Unfortunately, current medical techniques are unable to deduce sufficient information
about tumor heterogeneity by means of non‐invasive methods.
In this talk a mathematical model for heterogeneous tumor growth is proposed, and the
effects of different homogeneous and heterogeneous radiation dose distributions are
investigated by means of computer simulations [1]. Specifically, an individual cell‐based
model is considered for a simplified situation where two different tumor cell phenotypes
corresponding to GBM cell lines coexist in a tumor, which we assume to strongly differ in
their respective cell cycle duration and radiosensitivity properties. As a consequence of such
differences, the spatial distribution of the corresponding phenotypes, whence the resulting
tumor heterogeneity can be predicted as growth proceeds. Moreover, heterogeneous
dosimetries can be selected to enhance tumor control by boosting radiation in the region
occupied by the more radioresistant tumor cell phenotype. When compared with
homogeneous dose distributions currently delivered in clinical practice, such heterogeneous
radiation dosimetries always yield better results than their homogeneous counterparts.
[1] J. C. L. Alfonso, N. Jagiella, L. Núñez, M. A. Herrero, D. Drasdo (2014) Estimating Dose
Painting Effects in Radiotherapy: A Mathematical Model. PLoS ONE 9(2): e89380. doi:
10.1371/journal.pone.0089380.