Transcript NSS-MIC-todd-Poster

Reduced Dose of Proton CT Compared to X-Ray CT in Tissue-Density Variation Sensitivity
T. Satogata, T. Bacarian, S. Peggs, A.G. Ruggiero, and F.A. Dilmanian
Brookhaven National Laboratory, Upton USA
ABSTRACT
Proton therapy has advantages over conventional X-ray therapy in that it produces tighter dose distributions around the tumor due to the sharp range cutoff of the
proton Bragg peak. Because the dose distribution is highly localized, high-precision treatment planning is also required for proton therapy. Traditional treatment
tomography, X-ray computed tomography (XRCT), is inadequate for this planning because the proton stopping power mostly depends on the electron density. A
more natural approach is low-dose proton computed tomography (PCT), where the electron density in the patient or phantom is mapped directly by a proton beam of
higher energy than the therapy energy. We report detailed comparisons of PCT against XRCT based on our Monte Carlo simulations and tomographic
reconstruction techniques. The preliminary simulations of PCT and XRCT used pencil-beam scanning through a 20-cm water cylinder with a 2-cm off-axis water
cylinder of 1% higher density. The PCT Monte Carlo simulations included Bethe-Bloch energy loss and straggling, multiple Coulomb scattering; inelastic nuclear
collisions were neglected. The XRCT simulation used attenuation calculations for each ray, and added statistical noise to the resulting projections according to the
prescribed subject absorbed dose of 4 cGy. Both the PCT and the XRCT simulations used “bow-tie” water phantoms that reduce peripheral dose in XRCT (when
placed between the incident beam and primary phantom), and homogenized the proton tracks and reduced primary phantom dose in PCT (when placed behind the
primary phantom relative to the incident beam). The XRCT simulation measured intensity transmission; the PCT simulation measured both intensity and energy
transmission. The results demonstrated a 7-fold advantage for PCT in image contrast-to-noise ratio for the same mean absorbed dose of 4 cGy to the subject.
These results are in accord with recent reports of experimental and simulated findings from the Paul Scherer Institute (PSI), Switzerland [1,2]
INTRODUCTION
Radiation therapy is used to treat some types of
cancers, and facilities such as the Loma Linda
Proton Treatment Center and Paul Scherer Institute
(PSI) [1] have active clinical proton radiation therapy
programs. The primary objective of any radiation
therapy is to deliver a high dose of radiation to the
tumor, while limiting the radiation dose to healthy
tissue. Protons deliver their radiation dose in a highly
localized region compared to broad-spectrum dosing
from photon (X-ray) therapies. However, treating
many cancers with proton therapy is potentially
suboptimal due to insufficient knowledge of electron
density distribution in the patient, a crucial
requirement for accurate treatment planning. Here
we evaluate simulations of contrast to-noise ratio
(CNR) in proton computed tomography (PCT)
compared to that in X-ray tomography (XRCT) for the
same mean subject dose of 4 cGy. The rationale for
the present work is the large slope of the dose
versus depth curve (solid red in Fig. 1 for
monochromatic protons) at the distal edge of the
Bragg peak, producing large image sensitivity to
density variations. Experimental results from PSI
show that planar proton radiography on simple
phantoms produces an order of magnitude lower
radiation dose than planar x-ray radiography for the
same CNR.
X-Ray and Proton Dose vs Depth in Water
PCT Simulation Geometry
Figure 2: The PCT simulation geometry. A 20 cm
diameter water cylinder (r=1) contains a slightly
denser 2 cm cylindrical “tumor”. The water-density
bow-tie is used to provide a near-constant
penetration depth, maintaing the Bragg edge on the
detector and minimizing dose to the phantom.
phantom is positioned either in front of (for XRCT)
or behind (for PCT, see Fig. 2) the phantom to serve
the following purposes: a) to equalize the radiation
absorbed dose throughout the primary phantom, b)
to equalize the signal in the detector at different
positions of the beam across the phantom, and c)
most importantly for PCT, to produce a square
subject from the combination of the bow-tie
phantom and the phantom, so that the position of
the Bragg peak will be always at the exit end of the
bow-tie phantom at different beam positions when
using a constant incident beam energy of 167 MeV.
The distal bow tie position for PCT also serves to
reduce the total mean dose to the primary phantom.
General imaging parameters. Both PCT and
XRCT beams were pencil beams 1 mm wide
(laterally) and 2 mm high (axially). Computer
tomography projections were acquired in a
translational/rotational geometry, with a 1-mm
translation step and 2o steps over 360o.
Tomographic images were reconstructed using a
standard filtered back-projection method.
Figure 1: Normalized dose vs penetration depth in
water for 2 MeV X-ray photons and 185 MeV
protons. Note the reduced dose and sharp Bragg
edge of the proton dose distribution. Low-energy
photons (60 keV used in present work) produce an
even larger surface dose than that pictured.
In PCT, the proton beam energy can be set so the
falling edge of the Bragg peak lies on a distal
detector plane. Small variations in intercepted tissue
density then cause large changes in detector dose
due to the large slope at the Bragg edge; this
advantage can either be used to reduce the dose for
a given CNR, or improve CNR over that provided by
XRCT for a given subject dose.
SIMULATION METHODS
The phantom: The phantom for both PCT and
XRCT was a water cylinder (density of 1.00 g/ml) of
20 cm diameter which included a paraxial water
cylinder of 2 cm diameter with a density of 1.01 g/ml
positioned 7 cm off axis (Fig. 2). A bow-tie water
Sample Proton Energy/Intensity Transmission
PCT simulation: CT projections for PCT were
generated using in-house Monte Carlo proton
simulations that included Bethe-Bloch energy loss,
energy straggling, and multiple Coulomb scattering.
No inelastic-scattering calculations were included.
The incident beam energy was tuned to position the
center of the Bragg peak at the exit end of the bowtie phantom, i.e., half the Bragg peak counts
reached the detector. The measured parameters
were proportional energy and intensity loss
projections, as shown in Figures 3a and 3b. Each
scan step assumed a separate beam pulse, i.e., it
was registered independently in the detector. No
trajectory reconstruction was used to produce high
spatial resolution, but ~1mm is achievable according
to the results described in [1].
XRCT simulation: The XRCT simulations used a
monochromatic incident 60 keV photon beam. The
simulations were not Monte Carlo, but used
deterministic attenuation calculations to produce CT
projections. Synthetic random noise, consistent with
the desired mean absorbed target dose of 4cGy,
was then added to the individual projections.
Figures 3a and 3b: Proportional proton energy and
intensity transmission projections through a single
angle scan in simulated PCT, using the geometry of
Fig. 2 and an incident 167 MeV p beam of 200
protons per 1mm transverse scan pixel.
RESULTS AND DISCUSSION
PCT and XRCT results are shown in Figures 4a and
4b respectively. The mean subject dose to the
primary phantom in the PCT simulations were about
4 cGy. In the XRCT results, the image noise was
adjusted to be equivalent of that obtained in 4 cGy.
Analysis of thse measurements showed a 7-fold
larger CNR for the PCT image for the same mean
absorbed dose.
The results indicate the potential of PCT in medical
imaging. This method can be used not only in
producing accurate electron-density images for
treatment planning in proton therapy, but also in
imaging brains and other targets in which high image
contrast is required within the limitations of the mean
absorbed radiation dose to the subject.
PCT and XRCT Reconstructed Images
Figures 4a and 4b: PCT and XRCT image
reconstructions from filtered backprojection. Image
reconstruction for the PCT case was performed with
energy transmission profiles as shown in Fig. 3a.
ACKNOWLEDGMENTS
This research was funded by the United States
Department of Energy. We thank Adam Rusek,
Joanne Beebe-Wang, Uwe Schneider, and Eros
Pedroni for invaluable discussions.
REFERENCES
[1] Uwe Schneider and Eros Pedroni, “Proton
Radiography as a Tool for Quality Control in Proton
Therapy”, Med Phys Vol 22 Issue 4, p. 353 (April
1995)
[2] Uwe Schneider and Alexander Tourovsky,
“Range-Uncertainty Imaging for Obtaining Dose
Perturbations in Proton Therapy”, IEEE Trans Nuc
Sci Vol 45 No 5, p. 2309 (October 1998)