ESTRO 36 Abstract Book

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S427 ESTRO 36 2017
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Conclusion
Traditionally, there is no way of applying a reference
detector when measuring small fields, especially for SRS
Brainlab conical collimators. The lack of reference signal
usually requires to acquire more signals in each measured
point to suppress the linac output fluctuation, which
results into a long measurement procedure. However, by
the introduction of stealth chamber,“continuous mode”
became available to us which substantially shorten the
measurement time while a good agreement between
measurements with and without stealth chamber for both
PDDs and Profiles was still reached. The use of stealth
chamber is a good solution to spare time during small field
dosimetry measurements. This aspect is important during
the commissioning of the stereotactic unit but it becomes
fundamental for the frequently quality control
performed.
PO-0808 Comparison of multi-institutional QA for
VMAT of Nasopharynx with simulated delivery errors
D.I. Thwaites1, E.M. Pogson1, S. Arumugam2, C.R.
Hansen3 , M. Currie4 , S. Blake1, N. Roberts5, M. Carolan4,
P. Vial 2, J. Juresic 2, C. Ochoa2, J. Yakobi2, A. Haman2, A.
Trtovac2, T. Al-Harthi1, L. Holloway2
1 University of Sydney, Institute of Medical Physics-
School of Physics, Camperdown, Australia
2 Liverpool and Macarthur Cancer Treatment Centres,
Medical Physics-Radiation Oncology, Liverpool, Australia
3 Odense University Hospital, Laboratory of Radiation
Physics, Odense, Denmark
4 Illawarra Cancer Care Centre, Medical Physics -
Radiation Oncology, Wollongong, Australia
5 University of Wollongong, Centre of Medical Radiation
Physics, Wollongong, Australia
Purpose or Objective
Quality assurance of individual treatment plans is often
performed using phantom measurement and analysing
acceptable delivery accuracy by gamma analysis with a
required pass rate. Simplifying a complex treatment plan
and measurement into a single number is
problematic. This study evaluates the sensitivity of
different equipment to simulated machine errors and
explores the role of different planning approaches to this
Material and Methods
VMAT plans were generated for a selected patient in
Pinnacle3 at three institutions, as per their local protocol.
An automated VMAT plan was also generated by institution
3 using Pinnacle 3 Autoplanning. Simulated machine errors
were deliberately introduced to the plans utilising Python.
These included collimator (°), MLC field size (mm) and
MLC shift (mm) errors of 5, 2, 1, -1, -2 and -5 units. Error-
introduced plans were then recalculated and reviewed.
The DVH metrics listed in Table 1 were deemed
unacceptable if their differences relative to the relevant
baseline plan were above the tolerances listed. Plans were
considered unacceptable if any one or more of the limits
were exceeded.
Table 1. DVH metrics and limits.
For each error type (i.e. in Collimator, C; MLC shift,
S; MLC Field Size, FS), the smallest error plans that were
deemed unacceptable were delivered within the given
institution; on an Elekta Linac, measured using an
Arccheck for institutions 1 and 3, and on a Varian Linac ,
measured using a Delta4 for institution 2. Gamma analysis
was performed in SNC Patient version 6.6 or Delta4
software respectively, utilising a 3%/3mm and 2%/2mm
global gamma pass rate (10% isodose threshold with
correction off). Before each set of measurements, MLC
checks and a complex benchmark patient test were used
to ensure the Linacs' performances were within normal
range.
Results
The global 3%/3mm gamma pass is able to detect the
majority of unacceptable plans; however some plans with
significant errors still pass. Interestingly the error type/s
that passed differed at differing institutions (Figure 1).
Figure 1. The smallest error plans (including Collimator
(C), MLC shift (S), and MLC Field Size (FS) error) which
exceeded global gamma pass rates. Errors detected if the
gamma pass rate was < 95% (for 3%/3mm) or <88%
(2%/2mm). Plans that passed are illustrated above the red