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A.79
YOURELASTICSOLUTION GROUP: MULTI-INSTITUTIONAL STUDY TO
EVALUATE DIR ALGORITHMS FOR STRUCTURE DELINEATION VIA
COMPUTATIONAL PHANTOMS
M. Fusella
*
, a ,C. Fiandra
b ,E. Lanzi
c ,G. Loi
a ,L.C. Orlandini
d ,F. Lucio
e ,S. Strolin
f ,E. Gin
o g ,E. Mezzenga
h ,A. Roggi
o i ,L. Tan
a j ,E. Cagn
i k ,G. Orlandi
l ,C. Garibaldi
m .a
Department of Medical Physics, University Hospital “Maggiore
della Carità”, Novara, Italy;
b
Department of Radiation Oncology, Unviersity of
Turin, Turin, Italy;
c
R&D Department, Tecnologie Avanzate, Torino, Italy;
d
Department of Medical Physics, Centro Oncologico Fiorentino – CFO, Firenze,
Italy;
e
Department of Medical Physics, Santa Croce e Carle Hospital, Cuneo,
Italy;
f
Laboratory of Medical Physics and Expert Systems, Regine Elena national
Cancer Institute, Roma, Italy;
g
Department of Medical Physics, A.O. Ordine
Mauriziano, Torino, Italy;
h
Istituto Scientifico Romagnolo per lo Studio e la Cura
del Tumori – IRST IRCCS, Meldola, Italy;
i
Veneto Institute of Oncology, IOV-IRCCS,
Padova, Italy;
j
Health Physics Unit, Univeristy Hospital of Pisa, Pisa, Italy;
k
S.
Maria Nuova Hospital, Department of Medical Physics, Reggio Emilia, Italy;
l
Department of Medical Physics, Ospedale Civile Giuseppe Mazzini, Teramo,
Italy;
m
Unit of Medical Physics, European Institute of Oncology, Milano, Italy
Purpose:
To investigate the accuracy of various algorithms for deform-
able image registration (DIR) to propagate regions of interest (ROIs) in
computational phantoms based on patient images using different com-
mercial systems. This work is part of an Italian multi-institutional study
to test on common datasets the accuracy, reproducibility and safety of DIR
applications in adaptive radiotherapy.
Material and Methods:
Fifteen institutions with five available commer-
cial solutions provided data to assess the agreement of DIR-propagated ROIs
with automatically drawn ROIs considered as ground-truth for the com-
parison. The DIR algorithms were tested on CT patient data from three
different anatomical districts: head and neck, thorax and pelvis. For each
dataset two deformation vector fields were applied to the reference data
set using ImSimQA software. A three way ANOVA was performed to iden-
tify major predictors of DIR performances followed by a post hoc Sceffè test
to analyze intragroup differences; the logit transform of the Jaccard con-
formity index was used as metric.
Results:
ANOVA test showed that site, center and deformation strength were
significant predictors of DIR performance, but post hoc tests confirmed that
only for site and deformation the differences were significant, while there
were not significant differences among centers except for two that were
underperformers in the pelvis patients. DIR showed less accurate results
in the smallest or more elastic organs, like parotids or lung tumors.
Conclusions:
This work illustrates some clinical scenarios for ROI mapping
between different CT by mean of DIR, with ground truth provided by spe-
cific software. The results highlight that DIR performances depend on site
and deformation strength. Improved working protocols are needed in order
to reduce inter-institution variability in those conditions, like the pelvis,
where large deformations and small gray gradients affect DIR accuracy.
http://dx.doi.org/10.1016/j.ejmp.2016.01.083A.80
IMPACT OF IMAGE QUALITY ON DEFORMABLE IMAGE REGISTRATION
PERFORMANCES IN PELVIS PATIENTS
M. Fusella
* , a ,G. Lo
i a ,C. Fiandr
a b ,E. Lanzi
c .a
Department of Medical Physics,
A.O.U. Maggiore della Carità, Novara, Italy;
b
Department on Radiation Oncology,
A.O.U. Città della Salute e della Scienza, Torino, Italy;
c
Tecnologie Avanzate Srl,
Torino, Italy
Purpose:
To investigate the accuracy and robustness, against image noise
and artifacts (typical of CBCT images), of a commercial algorithms for de-
formable image registration (DIR), to propagate regions of interest (ROIs)
in computational phantoms based on patient images.
Material and Methods:
The DIR algorithm (Anaconda, implemented in
RayStation, RaySearch) was tested on real prostate patient data. Two spe-
cific deformation vector fields (DVFs) were applied to the reference data
set (CTref) using the ImSimQA software, obtaining two deformed CTs. For
each dataset sixteen different levels of noise and capping artifacts were
applied to simulate CBCT images. DIR was performed between CTref, and
each deformed CTs and CBCTs. A two way ANOVA was performed to iden-
tify major predictors of DIR performances; the logit transform of the Jaccard
conformity index (JCI) was used as metric and compared against SNR and
artifact intensity of all CBCTs.
Results:
More than 200 DIR-mapped ROIs were analyzed. The ANOVA test
states that deformation strength and artifacts were significant prognostic
factors of DIR performances; noise appeared to have a minor role in DIR
process as implemented in RayStation as expected by the image similar-
ity metric built in the registration algorithm.
Conclusions:
This work illustrates the impact of image quality on DIR per-
formances in some clinical scenarios with well-known DVFs. Clinical issues
like adaptive radiation therapy (ART) and dose accumulation need accu-
rate and robust DIR software. The RayStation DIR algorithm resulted in robust
against noise, but sensitive to image artifacts. This result highlights the need
of robustness quality assurance against image noise and artifacts in the com-
missioning of a DIR commercial system and underlines the importance to
adopt optimized protocols for CBCT image acquisitions in ART clinical
implementation.
http://dx.doi.org/10.1016/j.ejmp.2016.01.084A.81
ROBUST VMAT OPTIMIZATION IN LUNG SBRT WITH A COMMERCIAL
SYSTEM
M. Fusella
*
, G. Loi, M. Oronzio, F. Puricelli, C. Secco.
Department of Medical
Physics, A.O.U. Maggiore della Carità, Novara, Italy
Purpose:
To validate the robust optimization (RO) algorithm built in a com-
mercial treatment planning system (TPS) in the clinical setting of lung SBRT.
Material and Methods:
Originally developed for adrotherapy, RO is a tool
based on a Min–Max optimization for setup uncertainties with density cor-
rection built in RayStation TPS. RO robustness was investigated for moving
targets in the context of lung SBRT accounting for patient setup errors, in-
terplay and interface effects. 4D-CT images including 10 ventilation phases
of 3 lung SBRT patients and of a moving lung phantom with inserts were
used to generate RO plans. RO was done selecting arbitrary single phases
and the average CTs; silico tests were performed comparing the RO results
with the 4D dose calculated on each phase scan and perturbed for setup
errors. Dosimetric accuracy has been assessed measuring the dose deliv-
ered by the RO plan with GafChromic EBT3 films inserted in the phantom
simulating various motion patterns. Target covertures were compared with
the standard plan based on ITV generation from the ten phases of 4DCT
and PTV expansion. DVH analysis and measured dose profiles were used
to quantify ITV covertures.
Results:
In silico test on patient and phantom data showed variations of
relevant DVH points for ITV, CTV, OARs less than 2.5% with setup shifts up
to 3 mm and no difference for CT type. Similar results were obtained with
the standard approach. The dose measurements showed a good agree-
ment between the calculated and measured profiles with γ (2,2) criteria
passed in the high and falloff dose region corresponding to ITV for both
RO and standard plans, with RO slightly better.
Conclusions:
RO implemented in RayStation is safety deliverable in lung
SBRT providing similar or slightly better results than the standard ITV and
PTV approaches for moving targets. RO brings advantages in terms of time
sparing, leading us to develop a simpler and faster clinical/technical pro-
tocol for lung SBRT (~50 vs ~150 min).
http://dx.doi.org/10.1016/j.ejmp.2016.01.085A.82
QUANTITATIVE EVALUATION OF AUTOMATIC PLANNING SYSTEM:
COMPARISON WITH DIFFERENT MANUAL PLANNING FOR LIVER SBRT
TREATMENTS
E. Gallio
*
, a ,C. Fiandra
b ,F.R. Giglioli
a ,A. Girardi
b ,T. Rasoarimalala
c ,R. Ragona
b .a
Department of Medical Physics, A.O.U. Città della Salute e della
Scienza, Torino, Italy;
b
Radiotherapy Unit, Department of Oncology, University
of Turin, Torino, Italy;
c
International Center for Theoretical Physics, Trieste, Italy
Introduction:
Version 9.10 of Pinnacle3 TPS (Philips Medical Systems) in-
cludes Auto-Planning (AP) module. The aim of this study was to evaluate
and compare AP plans with different TPS manual ones for liver stereotac-
tic body radiotherapy (SBRT) treatments.
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Abstracts/Physica Medica 32 (2016) e1–e70