Citation:
Gago-Arias, A.; Neira, S.; Terragni, F.; Pardo-Montero, J. A Mathematical Model of Thyroid Disease Response to Radiotherapy. Mathematics 2021, 9, 2365.
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
European Commission Ministerio de Ciencia, Innovación y Universidades (España) Universidad Carlos III de Madrid Agencia Estatal de Investigación (España)
Sponsor:
This project has received funding from the Instituto de Salud Carlos III (PI17/01428
grant, FEDER co-funding). This project has received funding from the European Unions Horizon
2020 research and innovation programme under the Marie Skodowska-Curie grant agreement
No 839135. This project has received funding from FEDER/Ministerio de Ciencia, Innovación y
Universidades;Agencia Estatal de Investigación, under grant MTM2017-84446-C2-2-R.
Project:
Gobierno de España. MTM2017-84446-C2-2-R info:eu-repo/grantAgreement/EC/H2020/839135 Universidad Carlos III de Madrid. PI17/01428
Keywords:
Mathematical model
,
Radiobiology
,
Radioiodine therapy
,
Thyroid
We present a mechanistic biomathematical model of molecular radiotherapy of thyroid
disease. The general model consists of a set of differential equations describing the dynamics of
different populations of thyroid cells with varying degrees of damage causedWe present a mechanistic biomathematical model of molecular radiotherapy of thyroid
disease. The general model consists of a set of differential equations describing the dynamics of
different populations of thyroid cells with varying degrees of damage caused by radiotherapy
(undamaged cells, sub-lethally damaged cells, doomed cells, and dead cells), as well as the dynamics
of thyroglobulin and antithyroglobulin autoantibodies, which are important surrogates of treatment
response. The model is presented in two flavours: on the one hand, as a deterministic continuous
model, which is useful to fit populational data, and on the other hand, as a stochastic Markov model,
which is particularly useful to investigate tumor control probabilities and treatment individualization.
The model was used to fit the response dynamics (tumor/thyroid volumes, thyroglobulin and
antithyroglobulin autoantibodies) observed in experimental studies of thyroid cancer and Graves’
disease treated with 131I-radiotherapy. A qualitative adequate fitting of the model to the experimental
data was achieved. We also used the model to investigate treatment individualization strategies for
differentiated thyroid cancer, aiming to improve the tumor control probability. We found that simple
individualization strategies based on the absorbed dose in the tumor and tumor radiosensitivity
(which are both magnitudes that can potentially be individually determined for every patient) can
lead to an important raise of tumor control probabilities.[+][-]