ESTRO 36 Abstract Book

S851

ESTRO 36 2017

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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.

was developed to describe the synergistic

effect of immunotherapy and radiotherapy observed in a

previous pre-clinical study in glioma carrying rats.

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.

Serre R, et al. Mathematical model of cancer

immunotherapy and its synergy with radiotherapy. Cancer

Res

76(17):4931–40, 2016.

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

, R. Leijenaar

, W. Van Elmpt

, S.

Walsh

, A. Jochems

, P. Lambin

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

radiomics, i.e. the change of radiomic features over time,

has not yet been extensively explored. Cone-beam CT

(CBCT) imaging can be performed daily for lung cancer

patients and is therefore a potential candidate for delta

radiomics, which may allow further treatment

individualization. In this study we explored delta

radiomics using CBCT imaging by investigating the number

of features changing at a specific time point during

treatment. Moreover, we investigated the differences

between patients having an overall survival of less or more

than 2 years.

Material and Methods

A total of 40 stage II-IV NSCLC patients, receiving

curatively intended radiotherapy for a period of at least

six weeks, were included in the study. The CBCT images

used in this study were 1) CBCT prior to the first fraction

of treatment (CBCTfx1), 2) CBCT prior the second fraction

of treatment (CBCTfx2), 3) CBCT one week after the start

of treatment (CBCTweek2), 4) CBCT three weeks after the

start of treatment (CBCTweek4) and 5) CBCT five weeks

after the start of treatment (CBCTweek6). For 38 patients

CBCTfx1 and CBCTfx2 were available, whereas for 33

patients all weekly CBCTs were available. All patients had

a minimal follow-up of 2 years. Per time point, a total of

1046 radiomic features were derived from the primary

tumor volume. The images prior to the first and second

fraction were used to calculate the variability in imaging

features using the coefficient of repeatability (COR),

defined as 1.96*SD. The weekly images were used to

investigate the number of features changing more than

the COR with respect to baseline (CBCTfx1).

Results

Figure 1 represents the total number of features that

changed more than the COR, ranging from 0 to 999

features. The median number of features that changed for

the group with overall survival <2 years was 279, whereas

this was 500 for the group with overall survival >2 years

(Mann-Whitney U test, p = 0.06). For 8 out of 10 patients

that survived >2 years, more features (31.7%) changed one

week after CBCTfx1 than for 13 out of 23 patients that did

not survive two years.

Conclusion

This study shows that a large proportion of the radiomic

features derived from cone-beam CT images change

significantly during the course of treatment, meaning that

an interval of about two weeks is feasible for a radiomics

study using CBCT imaging. The larger number of features

that changed in the group with overall survival >2 years

could reflect an early response of the tumor to the

treatment. In future research, the prognostic value of

changing radiomic features (delta radiomics) should be

explored in a larger cohort.

EP-1601 Do higher CT pixel values outside the GTV

predict for poorer lung cancer survival?

M. Van Herk

, J. Kennedy

, E. Vasquez Osorio

, C. Faivre-

Finn

, A. McWilliam

University of Manchester, Division of Molecular and

Clinical Cancer Sciences- Faculty of Biology- Medicine

and Health, Manchester, United Kingdom

The Christie NHS Foundation Trust, Department of

Infomatics, Mancehster, United Kingdom