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0Cone beam computed tomography (CBCT)
images contain more scatter than a conventional computed tomography (CT)
image and therefore provide inaccurate Hounsfield units (HUs). Consequently,
CBCT images cannot be used directly for dose calculation. The aim of this
study is to enable dose calculations to be performed with the use of CBCT
images taken during radiotherapy and potentially avoid the necessity of
re-planning.
A phantom and prostate cancer patient with
a metallic prosthetic hip replacement were imaged using both CT and CBCT. The
multilevel threshold algorithm was used to categorise pixel values in the
CBCT images into segments of homogeneous HU. The variation in HU with
position in the CBCT images was taken into consideration and the benefit of
using a larger number of materials than typically used in previous work has
been explored. This segmentation method relies upon the operator dividing the
CBCT data into a set of volumes where the variation in the relationship
between pixel values and HUs is small. A field-in-field treatment plan was
generated from the CT of the phantom. An intensity-modulated radiation
therapy plan was generated from CT images of the patient. These plans were
then copied to the segmented CBCT datasets with identical settings and the
doses were recalculated and compared.
In the phantom study, γ evaluation showed
that the percentage of points falling in planning target volume, rectum and
bladder with γ<1 (3%/3 mm) was 100%. In the patient study, increasing the
number of bins to define the material type from seven materials to eight
materials required 50% more operator time to improve the accuracy by 0·01%
using pencil beam and collapsed cone and 0·05% when using Monte Carlo
algorithms.
The segmentation of CBCT images
using the method in this study can be used for dose calculation. For a simple
phantom, 2 values of HU were needed to improve dose calculation accuracy. In
challenging circumstances such as that of a prostate patient with hip
prosthesis, 5 values of HU were found to be needed, giving a reasonable
balance between dose accuracy and operator time.
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OBJECTIVE:
Cone
beam CT (CBCT) images contain more scatter than a conventional CT image and
therefore provide inaccurate Hounsfield units (HUs). Consequently, CBCT
images cannot be used directly for radiotherapy dose calculation. The aim of
this study is to enable dose calculations to be performed with the use of
CBCT images taken during radiotherapy and evaluate the necessity of
replanning.
METHODS:
A
patient with prostate cancer with bilateral metallic prosthetic hip
replacements was imaged using both CT and CBCT. The multilevel threshold
(MLT) algorithm was used to categorize pixel values in the CBCT images into
segments of homogeneous HU. The variation in HU with position in the CBCT
images was taken into consideration. This segmentation method relies on the
operator dividing the CBCT data into a set of volumes where the variation in
the relationship between pixel values and HUs is small. An automated MLT
algorithm was developed to reduce the operator time associated with the
process. An intensity-modulated radiation therapy plan was generated from CT
images of the patient. The plan was then copied to the segmented CBCT (sCBCT)
data sets with identical settings, and the doses were recalculated and
compared.
RESULTS:
Gamma
evaluation showed that the percentage of points in the rectum with γ < 1
(3%/3 mm) were 98.7% and 97.7% in the sCBCT using MLT and the automated MLT
algorithms, respectively. Compared with the planning CT (pCT) plan, the MLT
algorithm showed −0.46% dose difference with 8 h operator time while the automated
MLT algorithm showed −1.3%, which are both considered to be clinically
acceptable, when using collapsed cone algorithm.
CONCLUSION:
The
segmentation of CBCT images using the method in this study can be used for
dose calculation. For a patient with prostate cancer with bilateral hip
prostheses and the associated issues with CT imaging, the MLT algorithms
achieved a sufficient dose calculation accuracy that is clinically
acceptable. The automated MLT algorithm reduced the operator time associated with
implementing the MLT algorithm to achieve clinically acceptable accuracy.
This saved time makes the automated MLT algorithm superior and easier to
implement in the clinical setting.
ADVANCES
IN KNOWLEDGE:
The MLT
algorithm has been extended to the complex example of a patient with
bilateral hip prostheses, which with the introduction of automation is
feasible for use in adaptive radiotherapy, as an alternative to obtaining a
new pCT and reoutlining the structures.
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The
development of magnetic resonance (MR) imaging systems has been extended for
the entire radiotherapy process. However, MR images provide voxel values that
are not directly related to electron densities, thus MR images cannot be used
directly for dose calculation. The aim of this study is to investigate the
feasibility of dose calculations to be performed on MR images and evaluate
the necessity of re-planning.
A
prostate cancer patient was imaged using both MR and computed tomography
(CT). The multilevel threshold (MLT) algorithm was used to categorise voxel
values in the MR images into three segments (air, water and bone) with
homogeneous Hounsfield units (HU). An intensity-modulated radiation therapy
plan was generated from CT images of the patient. The plan was then copied to
the segmented MR datasets and the doses were recalculated using pencil beam
(PB) and collapsed cone (CC) algorithms and Monte Carlo (MC) modelling.
γ
Evaluation showed that the percentage of points in regions of interest with
γ<1 (3%/3 mm) were more than 94% in the segmented MR. Compared with the
planning CT plan, the segmented MR plan resulted in a dose difference of
–0·3, 0·8 and –1·3% when using PB, CC and MC algorithms, respectively.
The
segmentation and conversion of MR images into HU data using the MLT
algorithm, used in this feasibility study, can be used for dose calculation.
This method can be used as a dosimetric assessment tool and can be easily
implemented in the clinic.
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ملخص المشاركة:
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Introduction:
Interfractional organ motion, patient positioning errors and changes in the
size of the rectum and bladder can have deleterious clinical consequences
during prostate radiotherapy, and repositioning of the patient does not take
into account all of these errors. The fast development of Image Guided
Radiotherapy (IGRT) technology, such as cone-beam CT (CBCT), and more
advanced treatment delivery such as Intensity Modulated Radiotherapy (IMRT),
where a highly conformal dose distribution is used, has enhanced the need for
Adaptive Radiotherapy (ART) where the initial plan is adapted based on the
current patient geometry. At present, it is still a challenging task to
accurately delineate the tumour and organs and calculate the dose using CBCT
images directly, due to the sub-optimal cone-beam geometry, which results in
more noise and image artefacts, thus limiting the use of such a technology
for ART.
Objective: The
aim of this study is to utilise CBCT images taken during prostate
radiotherapy treatment to assess the dose being delivered and to determine
ways to quickly and safely adapt the treatment to take account for any
changes.
Materials and Methods:
Hounsfield units (HU) of CBCT images were converted into electron density and
then into HUs used by the clinical CT system, and then imported into the
treatment planning system (Oncentra Masterplan, OMP). This step involved
segmenting CBCT CT numbers into different discrete bins (i.e. air, bone,
water, etc.) in a Solid Water, Multiblock phantom and a prostate cancer
patient with a metallic prosthetic hip replacement. The CBCT images of the
Multiblock phantom were segmented into two bins (water and bone) generating
new images while the CBCT images of the patient, which were taken four days
after the initial treatment delivery, were segmented into a four, five, six,
seven and eight bins image series. These bins represent air, lung, adipose
tissue, water, soft tissue, cartilage tissue, bone and metal implants. For
the phantom case, a conventional prostate plan (field-in-field) was performed
on conventional CT, CBCT and processed images. For the patient case, an IMRT
plan was performed on CT, CBCT and processed images. The impact of the
calculation of dose distribution on processed images was then investigated
using both a Monte Carlo model (EGSnrc) and OMP algorithms (Pencil-beam and
Collapsed Cone). Monte Carlo modelling provides high-quality plans and
examines ways to overcome the limitations of CBCT data to improve the
utilization of this technology for ART. High Performance Computing (HPC) was
used to speed up MC dose calculations. Finally, the Computational Environment
for Radiotherapy Research (CERR) was used to compare the MC and OMP dose
calculations, using DVHs and dose profiles.
Results: The difference between
CBCT and CT plans was significant as expected when CBCT images are used
directly for dose calculation. This is due to scatter and beam hardening
resulting in an increased amount of image artifacts with lower
signal-to-noise ratio. The processed plans agreed with the planning CT plan
better than the CBCT plan even though there was a difference, due to the
specified values of HU, where the image is segmented based on large changes
in gradient. This difference between CT and processed plans decreased as the
number of bins increased i.e. decreased by 0.5% going from 7 to 8 bins CT
ramp compared with CT but it required almost double calculation time.
Conclusions: The
density override technique provides an attractive method for dose calculation
on CBCT images for a homogenous medium such as pelvis region. For
heterogenous medium, much care must be taken as there is a larger variation
in electron density. Such a technique should be robust against CBCT artifacts
and can be easily implemented in clinical practice for ART purposes.
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ملخص المشاركة:
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Objective: Cone beam
CT (CBCT) and magnetic resonance (MR) images play important rules in
radiotherapy process pathway. The aim of this study to enable dose
calculations to be performed with the use of CBCT and MR images.
Methodology: A standard
prostate patient, prostate cancer patients with a single and double metallic
prosthetic hip replacements were imaged using both CT and CBCT. The
multilevel threshold algorithm (MLT) was used to categorise pixel values in
the CBCT images into segments of homogeneous HU. The variation in HU with
position in the CBCT images was taken into consideration. This segmentation
method relies upon the operator dividing the CBCT data into a set of volumes
where the variation in the relationship between pixel values and HUs is
small. A larger number of materials (up to 8) than typically used in previous
works was explored. An automated MLT algorithm was developed to reduce the
operator time associated with the process. Furthermore, the MR images of the
standard prostate case were only segmented into 3 materials, mainly air,
water and bone, using the MLT algorithm. For all cases, doses were calculated
using Monte Carlo codes (EGS/BEAMnrc).
Results: Segmenting
CBCT and MR images of the standard prostate case into 3 materials, air, water
and bone, resulted dose calculations with differences of less than 2%,
compared with pCT plan. For a prostate patient with a hip prosthesis, the
optimal level of operator effort that balances between dose accuracy and
operator time was found when 5 values of HU was used. The automated MLT
algorithm reduced the operator time associated with implementing the MLT
algorithm to achieve clinically acceptable accuracy.
Conclusion: The
segmentation of CBCT and MR images using the method in this study can be used
for dose calculation and achieve a dose accuracy that is comparable to the
pCT-based dose calculation.
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