935 / 1096
S919
ESTRO 36
_______________________________________________________________________________________________
EP-1684 Optimal window for assessing treatment
responsiveness on repeated FDG-PET scans in NSCLC
patients
M. Lazzeroni
1
, J. Uhrdin
2
, S. Carvalho
3
, W. Van Elmpt
3
, P.
Lambin
3
, A. Dasu
4
, I. Toma-Dasu
5
1
Karolinska Institutet, Medical Radiation Physics-
Department of Oncology-Pathology, Stockholm, Swede
2
RaySearch Laboratories AB, RaySearch Laboratories AB,
Stockholm, Sweden
3
GROW-School for Oncology and Developmental Biology-
Maastricht University Medical Center, Department of
Radiation Oncology, Maastricht, The Netherlands
4
The Skandion Clinic, The Skandion Clinic, Uppsala,
Sweden
5
Stockholm University, Medical Radiation Physics-
Department of Physics, Stockholm, Sweden
Purpose or Objective
A previous study has shown that the early response to
treatment in NSCLC can be evaluated by stratifying the
patients in good and poor responders based on calculations
of the effective radiosensitivity, αeff, derived from two
FDG-PET scans taken before the treatment and during the
second week of radiotherapy [1]. However, the optimal
window during the treatment for assessing αeff was not
investigated. This study aims at assessing αeff of NSCLC
tumours on a new cohort of patients for which the second
scan was taken during the third week of treatment. The
optimal window for response assessment could be
determined by investigating the ability of the method to
predict treatment outcome through a comparison of the
results of a ROC analysis for the new cohort of patients,
imaged at three weeks, with the results of the previous
study in which patients were imaged at two weeks.
Material and Methods
Twenty-eight NSCLC patients were imaged with FDG-PET
before the treatment and during the third week of
radiotherapy. The patients received 45 Gy in 1.5 Gy
fractions twice-daily followed by a dose-escalation up to
maximum 69 Gy in daily fractions of 2 Gy. The outcome of
the treatment was reported as overall survival (OS) at two
years. αeff was determined at the voxel level taking into
account the voxel SUV in the two images and the dose
delivered until the second scan. Correlations were sought
between the average (a_αeff) or negative fraction
(nf_αeff) of αeff
values and the OS. The AUC and the p-
value resulting from the ROC analysis were compared to
the corresponding values reported for the case when the
second scan was taken during the second week of
treatment.
Results
The ROC curves in Figure 1 show the correlation between
a_αeff and OS and also the correlation between nf_αeff
and OS in the present and the earlier analysis. The results
expressed as AUC and p-value show the lack of correlation
between either a_αeff
(AUC=0.5, p=0.7) or nf_αeff
(AUC=0.5, p=0.8) and the OS for the scan at 3 weeks.
This
contrasts with the case when the second image was taken
during the second week of treatment (AUC=0.9,
p<0.0001). From the comparison of the ROC curves it
results that the values of αeff
can be used for predicting
the OS if the second scan is taken during the second week,
but not during the third week.
Conclusion
The optimal window for assessing the responsiveness to
treatment based on αeff calculations derived from
repeated FDG PET scans in NSCLC patients appears to be
the second week of the treatment but validation on a
larger cohort of patients is warranted.
[1] Toma-Dasu I, Uhrdin J, Lazzeroni M, Carvalho S, van
Elmpt W, Lambin P, Dasu A. Evaluating tumor response of
non-small cell lung cancer patients with 18F-
fludeoxyglucose positron emission tomography: potential
for treatment individualization. Int J Radiat Oncol Biol
Phys. 2015 1;91(2):376-84.
EP-1685 CT-Radiomics outperforms FMISO-PET/CT for
the prediction of local control in head-and-neck cancer
J.A. Socarras Fernandez
1
, D. Mönnich
1
, F. Lippert
1
, D.
Welz
2
, C. Pfannenberg
3
, C. La Fougere
4
, G. Reischl
5
, D.
Zips
2
, D. Thorwarth
1
1
University Hospital Tübingen, Radiation Oncology -
Section for Biomedical Physics, Tübingen, Germany
2
University Hospital Tübingen, Radiation Oncology,
Tübingen, Germany
3
University Hospital Tübingen, Diagnostic and
Interventional Radiology, Tübingen, Germany
4
University Hospital Tübingen, Radiology - Section of
Nuclear Medicine, Tübingen, Germany
5
University Hospital Tübingen, Radiology - Section of
Radiopharmacy, Tübingen, Germany
Purpose or Objective
FMISO-PET has proven to capture probabilities of hypoxia
in tumors, which may predict risks of local recurrence
across patients. On the other hand, Radiomics
hypothesizes that heterogeneity of tumors can be
extracted from medical images. In this study, we
investigate the performance of CT-radiomics features and
FMISO PET/CT for prediction of local recurrence in head
and neck cancer (HNC) patients.
Material and Methods
A cohort of 22 HNC patients who underwent FMISO PET/CT
before primary Radiotherapy (RT) treatment was used.
Planning CT scans as well as FMISO PET/CT were acquired
prior to RT, FMISO PET data was analysed using maximum
tumour-to-muscle ratios (TMR
max
) 4h post injection. 92
Robust radiomics features including intensity-based as
well as texture features were extracted from the planning
CT images in the gross tumour volume (GTV). Six highly
significant radiomics features were selected from a simple
filter method based on cumulative distribution function
(CDF) in a univariate fashion in addition to a logistic
regression classification model (LoG) to build a predictive
model. Area under the curve of the receiver operating
characteristic curve (AUC-ROC) was computed for TMR
max
and the model including the six selected radiomics
Features. Finally, a combined model using FMISO TMR
max
and two radiomics features (one from texture and one
from intesity) were constructed.