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on gantries for proton therapy that have a different
geometry and did not use a bow-tie filter. The
performance of an
a priori
scatter correction algorithm
was in this study compared for the first time on CBCT
systems for photon vs. proton therapy gantries.
Material and Methods
The
a priori
scatter correction algorithm used a plan CT
(pCT) and raw CB projections. The projections were
acquired with On-Board Imagers of a Varian photon
therapy Clinac and of a Varian proton therapy ProBeam
system. The projections were initially corrected for beam
hardening followed by reconstruction using the RTK back
projection Feldkamp-Davis-Kress algorithm (rawCBCT).
Manual, rigid and deformable registrations were applied
using Plastimatch on the pCT to the rawCBCT. The
resulting images were forward projected onto the same
angles as the raw CB projections. The two projections sets
were then subtracted from each other, Gaussian and
median filtered, and then subtracted from the raw
projections and finally reconstructed to a scatter
corrected CBCT. To evaluate the algorithm, water
equivalent path length (WEPL) maps were calculated from
anterior to posterior on different reconstructions of the
data sets (CB projections and pCT). Initially we evaluated
CB projections of an Alderson phantom acquired on the
Clinac system before comparing CB projections of the
same CatPhan phantom acquired on both the Clinac and
the ProBeam systems.
Results
In the analysis of the Clinac projections of the Alderson
phantom, the scatter correction resulted in sub-mm mean
WEPL difference from the rigid registration of the pCT,
considerably smaller than what was achieved with the
regular Varian CBCT reconstruction algorithm (Figure 1).
The largest improvement was for the half-fan (below
neck) scans. With the Catphan phantom the rawCBCT was
very similar to the Varian reconstruction, due to a refitting
of beam hardening curve. When comparing
reconstructions of photon to proton gantry CB projections
(Figure 2) we found that the
a priori
scatter correction
improved the mean WEPL difference while preserving
image quality (the number of countable line pairs) for both
gantry types. The photon gantry showed less WEPL
difference, however used a higher pulse current per
acquisition ( 2.00 mAs), compared to the proton gantry
(1.4 mAs). The complete scatter correction is performed
within three minutes on a desktop with NVidia graphics.
Conclusion
We have shown that an
a priori
scatter correction
algorithm for CB projections improves CBCT image quality
on both photon- and proton therapy gantries, potentially
opening for CBCT-based image/dose-guided proton
therapy.
OC-0159 Dual energy CBCT increases soft tissue CNR
ratio and image quality compared to standard CBCT in
IGRT
M. Skaarup
1
, D. Kovacs
1
, M.C. Aznar
1
, J.P. Bangsgaard
1
,
J.S. Rydhög
1
, L.A. Rechner
1
1
The Finsen Center - Rigshospitalet, Clinic of Oncology,
Copenhagen, Denmark
Purpose or Objective
We investigate a method for enhancing soft tissue contrast
to noise ratio (CNR) and clinical image quality of cone-
beam computed tomography (CBCT) by using a dual energy
CBCT protocol.
Material and Methods
Nine patients were scanned using a standard CBCT
protocol of either 100 or 125 kVp and a DE-CBCT protocol
of two separate scans of 80 and 140 kVp respectively.
Other scan parameters were identical and total radiation
dose was kept at a similar level for both protocols. Virtual
monochromatic dual energy (VMDE) images were
reconstructed using a linear mix of the 80 and 140 kVp
scan.
The weight, with which the two images were combined,
was calculated based on known attenuation coefficients of
two basis materials at a specific monochromatic energy. A
linear combination of these can be used to express the
attenuation coefficients of the 80 and 140 kVp scan at that
same monochromatic energy. To find the optimal virtual
reconstruction energy for soft tissue imaging, multiple
reconstructions were done for energies in the range 40-
180 keV.
CNR measurements were performed on both standard
CBCT and VMDE images for a number of different tissue
combinations, e.g. contrast between tumour-fat, tumour-
surrounding tissue, muscle-fat, rectum-surrounding
tissue, parotid-fat, seminal vesicle-surrounding tissue and
lung-heart (see figure 1 for an example). In addition, 5
experienced observers conducted a blinded ranking
between VMDE images (reconstructed at 55, 65, 75 and
100 keV) and the standard CBCT images, i.e. five image
series per patient. For each combination of image series
the observers were asked to compare the images side-by-
side, focusing on soft tissue image quality as well as