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Material and Methods
The mechanistic prediction is based on a radiobiological
TCP model describing the interplay between tumor cell
proliferation and hypoxia (Jeong et al., PMB 2013). The
study presented here (see Sup. Figure 1) focuses on a
cohort of 35 head and neck cancer patients treated with
chemoradiotherapy which received baseline FDG PET and
FMISO dynamic PET, and intra-treatment FMISO dynamic
PET scans, and which excluded subjects having a
significant increase in hypoxia during treatment. The
model is used to predict the radiobiological evolution of
each tumor voxel of the baseline image up until the intra-
treatment scan (9.2±3.4 days). The main inputs to the
model are the initial fractions of proliferative and hypoxic
tumor cells in each voxel, obtained from an approximate
solution to a system of linear equations relating cell
fractions to voxel-level FDG uptake, perfusion (FMISO K
1
)
and hypoxia (FMISO k
3
). For each lesion, the predicted
levels of intra-treatment hypoxia are compared to the
measured k
3
from the intra-treatment scan. A single global
parameter (the average fraction of extremely hypoxic
cells that take up FMISO) is determined from a training
subset of 29 lesions by minimizing the average discrepancy
between each lesion’s measured and predicted intra-
treatment k
3
histograms (Cramér-von Mises criterion). A
validation subset of 10 lesions is held out to test the
resulting model.
Results
The average fraction of extremely hypoxic cells that take
up FMISO is 0.15 (95% CI 0.05 – 0.30 on bootstrap). In the
training subset, the model predicts the mean, median and
standard deviation of each lesion’s intra-treatment k
3
histograms (Pearson’s linear correlation coefficients
between predicted and measured values of ρ=0.62, 0.60
and 0.69 respectively, all with positive 95% CI on bootstrap
– see Sup. Table 1). In the validation subset, only the
predictions of the intra-treatment mean and median k
3
of
each lesion are significant (ρ=0.59 and 0.60 respectively).
Conclusion
This work presents a methodology to e stimate the
parameters of a mechanistic, radiobiological l TCP model
based on pre-treatment FMISO and FDG PET scans. The
method is able to predict mean and median values of
intra-treatment hypoxia for each of the lesions in a
validation dataset held out from the analysis. This could
potentially be used in the future to, for example, select
patients for a de-escalation protocol based on their
expected response. More patients will be added to the
analysis in order to refine the prediction, find the defining
characteristics of the outliers, and consolidate the results.
PO-0891 Quality assessment of target volume
delineation and dose planning in the Skagen Trial 1
G. Francolini
1
, M. Thomsen
2
, E. Yates
2
, C. Kirkove
3
, I.
Jensen
4
, E. Blix
5
, C. Kamby
6
, M. Nielsen
7
, M. Krause
8
, M.
Berg
9
, I. Mjaaland
10
, A. Schreiber
11
, U. Kasti
12
, K. Boye
13
,
B. Offersen
14
1
Azienda Ospedaliera Universitaria Careggi, Department
of Radiation oncology, Firenze, Italy
2
Aarhus University hospital, Department of Medical
physics, Aarhus, Denmark
3
Catholic University of Louvain, Department of Radiation
Oncology, Brussels, Belgium
4
Aalborg University Hospital, Department of Medical
Physics, Aalborg, Denmark
5
University Hospital of North Norway, Department of
Oncology, Tromso, Norway
6
Rigshospitalet, Department of Oncology, Copenhagen,
Denmark
7
Odense University Hospital, Department of Oncology,
Odense, Denmark
8
University Hospital Carl Gustav Carus, Department of
Radiation Oncology, Dresden, Germany
9
Hospital of Vejle, Department of Physics, Vejle,
Denmark
10
Stavanger University Hospital, Department of
Oncology, Stavanger, Norway
11
Praxis für Strahlentherapie, Department of Radiation
oncology, Dresden, Germany
12
Sørlandet Sykehus HF, Department of Oncology,
Kristiansand, Norway
13
Zealand University Hospital, Department of Oncology,
Naestved, Denmark
14
Aarhus University Hospital, Department of Oncology,
Aarhus, Denmark
Purpose or Objective
Skagen Trial 1 is a multicenter, non-inferiority trial
randomising early breast cancer patients to loco-regional
irradiation with 50 Gy/25 fractions vs 40 Gy/15fractions.
Primary endpoint is arm lymphedema.
The protocol has pre-specified criteria for target volume
delineation and dose planning, and quality assessment of
this is reported. Inter-observer variability in delineation
and its impact on dose parameters were assessed.
Automated atlas-based segmentation was used in order to
streamline assessment procedure.
Material and Methods