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S258
ESTRO 36
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(CBCT)], which is registered to the planning CT (pCT) using
a rigid body alignment. In the presence of non-rigid
anatomical changes, it is not obvious which isocenter shift
is the best with respect to target coverage and normal
tissue sparing. We evaluate an alternative approach,
where the dose is recalculated on daily scatter-corrected
CBCT (scCBCT) images and the isocenter shift is
determined using an interactive multicriterial
optimization of DVH objectives.
Material and Methods
To enable dose calculations, the CBCT projections were
scatter corrected using forward projections of the virtual
CT (deformable image registration of pCT on CBCT) as a
prior (Park et al. 2015, Med Phys). PTV and OAR structures
were transferred from the pCT to the scCBCTs and
corrected by an experienced clinician. In MIRA, a research
planning system interpolation between pre-calculated
sample dose distributions for a set of 13 isocenter
positions allows navigating continuously on the set of
Pareto-optimal isocenters. DVH parameters can be
manipulated interactively. The resulting isodose lines and
integral DVHs of this trade-off are displayed in real time,
allowing the user to repeatedly manipulate the
parameters until the clinically optimal solution is found.
For the resulting isocenter shift, a final dose calculation is
performed. The approach is evaluated for an exemplary
head and neck (H&N) patient case. The prescribed dose
was 54Gy in 30 fractions with 2 integrated boosts of 60Gy
and 66Gy, respectively. For 5 scCBCTs the optimized dose
distribution was compared to the ones of the clinically
applied shifts. To evaluate the accuracy of the underlying
dose interpolation, 100 random isocenter shifts for each
of the scCBCTs were interpolated and compared to an MC
calculation using a 2%/2mm gamma criterion.
Results
Dose interpolation accuracy was high [median gamma pass
rate: 99.0% (range 96.6-100.0%)].
The spinal cord D
2%
was
comparable for both approaches (mean change -0.2Gy,
range -1.7 to 0.2Gy). The mean dose of the parotid glands
could be improved for 2 out of 5 fractions (one of them is
displayed in Fig. 1), for the other 3 it could be preserved
(mean change -1.0Gy, range -2.2Gy to +0.4Gy). Target
coverage was preserved. The mean Euclidean distance
between the clinical and the optimized isocenter was
1.8mm (range 0.8-3.2mm).
Figure 1:
Comparison between a clinical (dashed) and an
optimized shift (solid). The mean dose to the left parotid
gland improved from 30.6 to 26.1Gy.
Conclusion
Compared to a rigid bony alignment, the novel,
interactive, DVH based positioning offers increased
control over OAR dose and PTV coverage. For a first H&N
case, in some fractions the dose to the parotid gland was
improved.
Acknowledgements: DFG-MAP and BMBF-SPARTA
OC-0487 Pre-treatment characteristics can predict
anatomical changes occurring during RT in lung cancer.
L. Hoffmann
1
, A. Khalil
2
, M. Knap
2
, M. Alber
3
, D. Møller
1
1
Aarhus University Hospital, Department of Medical
physics, Aarhus, Denmark
2
Aarhus University Hospital, Department of Oncology,
Aarhus, Denmark
3
Heidelberg University Hospital, Department of
Oncology, Heidelberg, Germany
Purpose or Objective
Anatomical changes such as the resolving atelectasis seen
in Fig 1. prompt adaptive radiotherapy (ART) for a large
number of lung cancer patients in order to avoid target
under dosage. ART may re-establish the original dose
distribution on the cost of additional work load. We
investigated the correlation between patient
characteristics before RT and anatomical changes during
RT in order to identify the patients eligible for ART.
Material and Methods
A decision support protocol for ART was used for
treatment of 165 lung cancer patients. The patient setup
on the primary tumour (T) was based on daily pre-
treatment cone-beam CTs. Deviations in T >2mm, lymph
nodes (N) >5mm or changes in atelectasis (A) or pleural
effusion (PE) triggered replanning. The daily CBCTs were
retrospectively reviewed to score changes above trigger
limit in T or N position/shape, changes in A or PE, as well
as T or N shrinkage >1cm. The findings were correlated to
pre-treatment patient characteristics as histology, T and
N volume, location and number, A or PE, and T or N
adjacent to or surrounding the bronchi. Fisher’s exact test
was used for comparison. p<0.05 was considered
significant.
Results
Fifty three patients (32%) were adapted due to changes in
A (8%), T (6%), N (15%) or T+N (3%), and 7% had more than
one replan. Atelectasis was seen at planningCT in 50
patients (30%) while in 12 patients (7%), it appeared during
RT. Presence of A before or during RT was not significantly
correlated with replanning. However, the changes in A
during RT significantly increased the probability of
replanning. (p=0.03), see Fig.2. Additionally, A within
5mm of T or N was significant (p=0.01). Only 11 patients
(6%) had changes in PE, but only in one patient was
replanning indicated. Patients with T0 or N0 had a
significant low risk of replanning (p=0.01, p=0.03) while
patients with two or more N had a high rate of replanning
(ns). Nodes in stations 1,2,3 or 4,7 or 10,11,12 had
significantly higher rate of replanning as compared to
patients with nodes in station 5,6 and 8,9. Node-volume
>30cm
3
had a significantly higher rate of replanning
(p=0.02). No correlation was found for T location, T size,
T or N adjacent to bronchi or for T or N shrinkage.
Histology was not significant for replanning. The imaging
rate may be decreased for patients with T0 and no A, as
none of these were adapted. For patients with N0 and no
A, only 11%, were replanned. On the contrary, 60% of the
patients with A and N volume>30cm
3
were replanned.