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Results
A total of 315 simulations were performed. Figure 2 shows
the total doses necessary to kill 50% to 99.9% of the tumor
cells, depending on the fractionation. The mean (SD)
doses (Gy) to kill 99% of the tumor cells were therefore 72
(±14), 68 (±13) and 65 (±12) for fractionations (Gy) of 2,
2.5 and 3, respectively. The mean (SD) doses (Gy) to kill
99.9% of the tumor cells were therefore 107 (±17),
101(±16) and 94 (±15) for fractionations (Gy) of 2, 2.5 and
3, respectively. The foci with GS 7: 4+3 needed
significantly higher doses than the foci with GS 7: 3+4 to
destroy the tumor cells from 50% to 99.9%, at all
fractionations (Mann-Whitney test).
Conclusion
Our histopathological specimen based simulations allowed
to estimate the total doses necessary to kill the tumor
cells, depending on the fractionation. GS: 4+3 tissue
appears more radioresistant than GS:3+4 tissue.
EP-1599 Mathematical modeling of the synergistic
combination of cancer immunotherapy and
radiotherapy
C. Ceberg
1
, J. Ahlstedt
2
, H. Redebrant Nittby
3
1
Ceberg Crister, Medical Radiation Physic- Lund
University, Lund, Sweden
2
Lund University, The Rausing Laboratory, Lund, Sweden
3
Skåne University Hospital, Department of Neurosurgery,
Lund, Sweden
Purpose or Objective
Cancer immunotherapy is a promising treatment modality
that is currently under strong development with a large
number of ongoing pre-clinical and clinical studies. In an
attempt to improve the treatment efficacy combinatorial
strategies are explored, and the combination of
immunotherapy and radiotherapy is of particular interest,
since more than half of all cancer patients already receive
radiotherapy as part of their treatment. It is well known
that radiation has immunomodulatory effects. In addition
to killing off tumor cells as well as immune effector cells,
radiation also affects the release of tumor antigens, the
dendritic cell activity and antigen presentation, the
presence of immunosuppressive cells in the tumor
microenvironment and tumor infiltrating lymphocytes, the
regulation of immunogenic cell surface receptors, and
immunogenic cell death. However, the balance between
pro-tumor and anti-tumor effects is delicate, and the
application of immunotherapy in combination with
radiotherapy has to be designed very carefully in order to
tip the immunomodulatory effect of radiation in the right
direction. There are many parameters that can be varied
in this equation, including time, dose and fractionation.
Therefore, in order to better understand the
immunomodulatory effect of radiation, and to be able to
optimize the combined treatment, there is a great need
for mathematical models.
Material and Methods
In this work, a mathematical model based on the work by
Serre et al.
1
was developed to describe the synergistic
effect of immunotherapy and radiotherapy observed in a
previous pre-clinical study in glioma carrying rats.
2
Animals with intracranial tumors were given indoleamine
2,3-dioxygenase (IDO) inhibitory treatments with
intraperitoneal injections of 1-methyl tryptophan (1-MT),
in combination with radiotherapy given as single fractions
of 8 Gy.
1
Serre R, et al. Mathematical model of cancer
immunotherapy and its synergy with radiotherapy. Cancer
Res
76(17):4931–40, 2016.
2
Ahlstedt J, et al. Effect of Blockade of Indoleamine 2, 3-
dioxygenase in Conjunction with Single Fraction
Irradiation in Rat Glioma. J J Rad Oncol 2(3):022, 2015.
Results
Using the mathematical model tumor growth and survival
curves were simulated, and the parameters of the model
were fit to the experimental data. Good agreement for
median survival time was achieved both for the two
modalities given separately as monotherapies, as well as
for
the
combined
treatment,
see
Figure.
Conclusion
Conclusion: The simplified mathematical model presented
in this work captures the general features of the
synergistic combination of IDO-inhibitory immunotherapy
and single fraction radiotherapy. The model can be used
to explore possible alternative time, dose and
fractionation, in order to gain improved insight into the
effects of these parameters, and to generate plausible
hypotheses for further pre-clinical studies.
EP-1600 Delta radiomics of NSCLC using weekly cone-
beam CT imaging: a feasibility study
J. Van Timmeren
1
, R. Leijenaar
1
, W. Van Elmpt
1
, S.
Walsh
1
, A. Jochems
1
, P. Lambin
1
1
Department of Radiation Oncology - MAASTRO, GROW
School for Oncology and Developmental Biology -
Maastricht University Medical Centre MUMC, Maastricht,
The Netherlands
Purpose or Objective
Currently, prognostic information is commonly derived
using radiomics features from medical images acquired
prior to treatment. However, the potential of delta