ESTRO 36 Abstract Book

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S473 ESTRO 36
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Conclusion
The implemented clinical protocol for abdominal
compression is able to reduce the mean marker motion by
roughly 5 mm in the initial imaging as well as in the pre-
treatment imaging. Although the stand ard deviation in
both imaging modalities was reduced by the abdominal
compression setup, the reproducibility of the abdominal
compression reflected by the decreased standard
deviation in the pre-treatment imaging could only be
improved slightly.
PO-0868 Evaluation of Watchdog response to
anatomical changes during head and neck IMRT
treatment
T. Fuangrod1, J. Simpson 1,2, S. Bhatia1, S. Lim3, M.
Lovelock3, P. Greer 1,2
1 Calvary Mater Newcastle, Radiation Oncology, Waratah-
NSW, Australia
2 University of Newcastle, School of Mathematical and
Physical Sciences, Newcastle- NSW, Australia
3 Memorial Sloan-Kettering Cancer Center, Radiation
Oncology, New York, USA
Purpose or Objective
Watchdog is a real-time patient treatment verification
system using EPID, which has been clinically implemented
as an advanced patient safety tool. However, the use of
Watchdog requires an understanding of its dosimetric
response to clinically significant errors. The objective of
this study is to evaluate the Watchdog dosimetric response
to patient anatomical changes during the treatment
course in head and neck (HN) IMRT.
Material and Methods
Watchdog utilises a comprehensive physics-based model
to generate a series of predicted transit cine EPID image
as a reference data set, and compares these to measured
cine-EPID images acquired during treatment. The
agreement between the predicted and measured transit
images is quantified using c-comparison (4%, 4mm) on a
cumulative frame basis. The 71.3% c pass-rate error
detection threshold in HN IMRT has been determined from
our pilot study of 37 HN IMRT patients using the statistical
process control (SPC) technique (1). The major source of
errors was inter-fractional anatomy changes due to weight
loss and/or tumour shrinkage.
To evaluate the Watchdog dosimetric response to HN IMRT
anatomical changes, the patient CT data was modified and
used for calculating the predicted EPID images. First, soft-
tissue patient thickness reduction or weight loss was
progressively simulated with a range of 0%, 1%, 2.5%, 5%,
7.5%, 10%, and 12.5% based on real patient deformations
using in-house software. Second, Watchdog dosimetric
response was determined for four HN patients with
observed weight loss during treatment who had a second
CT during treatment for replanning purposes. Watchdog
dosimetry was calculated using the second CT compared
to the original CT. The SPC-based threshold was applied
to determine the Watchdog performance for HN IMRT
anatomical change detection. These simulations provide
the decision rule for HN IMRT replanning based on
Watchdog assessment.
(1) Fuangrod (2016). Radiation Oncology, 11(1), 106
Results
From the simulation of patient weight loss (thickness
reduction), Watchdog has less sensitivity to small patient
thickness reduction. From figure 1 left, it can imply that
dropping by 25% c pass-rate refers to 10% patient
thickness reduction or approximately 1.5 cm shrinkage. In
clinical case validation, Watchdog was able to detect the
significant patient anatomical changes that lead to the
decision to replan all four HN IMRT patients (see figure 1
right). Based on this study, we found that Watchdog
system can detect the clinically significant anatomical
change in HN IMRT based on 1) at least 3 out of 7 fields of
the fraction are below the SPC-based threshold, 2) the
lowest c pass-rate is less than 30%, and 3) a 25% c pass-
rate drop equates to approximately a 1.5 cm (-10.0%)
patient thickness reduction.
Conclusion
The Watchdog dosimetic response to HN patient
anatomical changes has been evaluated based on the
simulation of patient thickness reduction/weight loss and
clinical cases of HN IMRT replan. Using the SPC-based
threshold, Watchdog is able to detect clinically significant
anatomical changes in HN IMRT treatment.
PO-0869 A population-based estimate of proton beam
specific range uncertainties in the thorax
Y.Z. Szeto1, M.G. Witte1, M. Van Herk2, J. Sonke1
1Netherlands Cancer Institute Antoni van Leeuwenhoek
Hospital, Radiotherapy department, Amsterdam, The
Netherlands
2Institute of Cancer Sciences- University of Manchester,
Molecular and Clinical Cancer Sciences, Manchester,
United Kingdom
Purpose or Objective
Proton therapy has great potential for locally advanced
lung cancer patients because of considerable reduction of
intermediate and low dose to the healthy tissues.
However, due to their finite beam range, proton dose
distributions are more susceptible to anatomical
variations. The purpose of this study was to derive a
population-based map of beam specific range
uncertainties due to anatomical variations.
Material and Methods
The planning CT (pCT) of 100 NSCLC patients treated
between 2010 and 2013 with (chemo-)radiotherapy were
included. To simulate realistic anatomical variations, we
used a previously developed statistical model, based on
principal component analysis for systematic variations in
the thorax. This model generates deformation vector
fields that deform the planning CT to induce systematic
differences between the anatomy of planning and
delivery. For each patient, we synthesized 1000 CTs (sCT)
representing plausible variations in treatment anatomy.
Subsequently, the water-equivalent path length
differences (∆R) between the pCT and sCTs was calculated
at the beam’s distal and proximal edge of the GTV for 13
equally spaced angles of 15⁰ through the ipsilateral lung.
Undershoot and overshoot at the distal edge results in an
under-coverage of the target and higher dose in normal
tissues respectively, and vice versa at the proximal edge.
To summarize the results, first for each scan and angle,
the 95th percentile ∆R in undershoot (∆Ru) and overshoot