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Paul J Keall

Publications and source records attributed to Paul J Keall.

At least 19 recordsLinked to original sources
PubMed2007

Tumor and normal tissue motion in the thorax during respiration: Analysis of volumetric and positional variations using 4D CT.

PURPOSE: To investigate temporospatial variations of tumor and normal tissue during respiration in lung cancer patients. METHODS AND MATERIALS: In 14 patients, gross tumor volume (GTV) and normal tissue structures were manually contoured on four-dimensional computed tomography (4D-CT) scans. Structures were evaluated for volume changes, centroid (center of mass) motion, and phase dependence of variations relative to inspiration. Only volumetrically complete structures were used for analysis (lung in 2, heart in 8, all other structures in >10 patients). RESULTS: During respiration, the magnitude of contoured volumes varied up to 62.5% for GTVs, 25.5% for lungs, and 12.6% for hearts. The range of maximum three-dimensional centroid movement for individual patients was 1.3-24.0 mm for GTV, 2.4-7.9 mm for heart, 5.2-12.0 mm for lungs, 0.3-5.5 mm for skin markers, 2.9-10.0 mm for trachea, and 6.6-21.7 mm for diaphragm. During respiration, the centroid positions of normal structures varied relative to the centroid position of the respective GTV by 1.5-8.1 mm for heart, 2.9-9.3 mm for lungs, 1.2-9.2 mm for skin markers, 0.9-7.1 mm for trachea, and 2.7-16.4 mm for diaphragm. CONCLUSION: Using 4D-CT, volumetric changes, positional alterations as well as changes in the position of contoured structures relative to the GTV were observed with large variations between individual patients. Although the interpretation of 4D-CT data has considerable uncertainty because of 4D-CT artifacts, observer variations, and the limited acquisition time, the findings might have a significant impact on treatment planning.

Diaphragm↗
PubMed2006

An analysis of 6-MV versus 18-MV photon energy plans for intensity-modulated radiation therapy (IMRT) of lung cancer.

PURPOSE: To analyse the supposed benefits of low over high photon energies for the radiotherapy of lung cancer. MATERIALS AND METHODS: For 13 patients, 6- and 18-MV IMRT planning was performed using identical planning objectives and dose constraints. Plans were compared according to dose-volume histogram (DVH) analysis including conformity and homogeneity indices (CI and HI) and overall plan quality (composite score CS), considering also magnitude and location of planning target volumes (PTVs). RESULTS: With 6-MV plans, CSs were better in 11/13, HIs in 10/13 and CIs in 6/13 patients compared with 18-MV plans. Six-MV plans resulted in a better normal tissue sparing except for specified dose levels to the thorax and spinal cord. On average differences between 6 and 18 MV both for the PTV and normal tissues were not statistically significant (p>0.05). Considering size and location of the PTVs as well as their relative position to normal tissue, overall no significant differences between 6 and 18 MV were observed. CONCLUSIONS: On average no clinically or statistically significant differences between 6- and 18-MV plans were observed. High photon energies should therefore not be excluded a priori when a dose-calculation algorithm is utilized that accurately accounts for heterogeneities.

Dose-Response Relationship, Radiation↗
PubMed2006

Geometric accuracy of a real-time target tracking system with dynamic multileaf collimator tracking system.

PURPOSE: Dynamically compensating for target motion during radiotherapy will increase treatment accuracy. A laboratory system for real-time target tracking with a dynamic MLC has been developed. In this study, the geometric accuracy limits of this DMLC target tracking system were evaluated. METHODS AND MATERIALS: A motion simulator was programmed to follow patient-derived tumor motion paths, parallel to the leaf motion direction. A target attached to the simulator was optically tracked, and the leaf positions adjusted to continually align the DMLC beam aperture to the target. Analysis of the tracking accuracy was based on video images of the target and beam alignment. The system response time was determined and the tracking error measured. Response time-corrected tracking accuracy was also calculated to investigate the accuracy limits of an improved system. RESULTS: The response time of the system is 160 +/- 2 ms. The geometric precision for tracking patient motion is 0.6 to 1.1 mm (1 sigma) for the 3 patient datasets tested, with tracking errors relative to the original patient motion of 35, 40, and 100%. CONCLUSIONS: A DMLC target tracking system has been developed that can account for detected motion parallel to the leaf motion direction. The tracking error has a negligible systematic component. Reducing the response time will further increase the overall system accuracy.

Calibration↗
PubMed2006

Audio-visual biofeedback for respiratory-gated radiotherapy: impact of audio instruction and audio-visual biofeedback on respiratory-gated radiotherapy.

PURPOSE: Respiratory gating is a commercially available technology for reducing the deleterious effects of motion during imaging and treatment. The efficacy of gating is dependent on the reproducibility within and between respiratory cycles during imaging and treatment. The aim of this study was to determine whether audio-visual biofeedback can improve respiratory reproducibility by decreasing residual motion and therefore increasing the accuracy of gated radiotherapy. METHODS AND MATERIALS: A total of 331 respiratory traces were collected from 24 lung cancer patients. The protocol consisted of five breathing training sessions spaced about a week apart. Within each session the patients initially breathed without any instruction (free breathing), with audio instructions and with audio-visual biofeedback. Residual motion was quantified by the standard deviation of the respiratory signal within the gating window. RESULTS: Audio-visual biofeedback significantly reduced residual motion compared with free breathing and audio instruction. Displacement-based gating has lower residual motion than phase-based gating. Little reduction in residual motion was found for duty cycles less than 30%; for duty cycles above 50% there was a sharp increase in residual motion. CONCLUSIONS: The efficiency and reproducibility of gating can be improved by: incorporating audio-visual biofeedback, using a 30-50% duty cycle, gating during exhalation, and using displacement-based gating.

Adult↗
PubMed2006

Displacement-based binning of time-dependent computed tomography image data sets.

Respiration can cause tumors in the thorax or abdomen to move by as much as 3 cm; this movement can adversely affect the planning and delivery of radiation treatment. Several techniques have been used to compensate for respiratory motion, but all have shortcomings. Manufacturers of computed tomography (CT) equipment have recently used a technique developed for cardiac CT imaging to track respiratory-induced anatomical motion and to sort images according to the phase of the respiratory cycle they represent. Here we propose a method of generating CT images that accounts for respiratory-induced anatomical motion on the basis of displacement, i.e., displacement-binned CT image sets. This technique has shown great promise, however, it is not fully supported by currently used CT image reconstruction software. As an interim solution, we have developed a method for extracting displacement-binned CT image data sets from data sets assembled on the basis of a prospectively determined breathing phase acquired on a multislice helical CT scanner. First, the projection data set acquired from the CT scanner was binned at small phase intervals before reconstruction. The manufacturer's software then generated image sets identified as belonging to particular phases of the respiratory cycle. All images were then individually correlated to the displacement of an external fiducial marker. Next, CT image data sets were resorted on the basis of the displacement and assigned an appropriate phase. Finally, displacement-binned image data sets were transferred to a treatment-planning system for analysis. Although the technique is currently limited by the phase intervals allowed by the CT software, some improvement in image reconstruction was seen, indicating that this technique is useful at least as an interim measure.

Algorithms↗
PubMed2006

The management of respiratory motion in radiation oncology report of AAPM Task Group 76.

This document is the report of a task group of the AAPM and has been prepared primarily to advise medical physicists involved in the external-beam radiation therapy of patients with thoracic, abdominal, and pelvic tumors affected by respiratory motion. This report describes the magnitude of respiratory motion, discusses radiotherapy specific problems caused by respiratory motion, explains techniques that explicitly manage respiratory motion during radiotherapy and gives recommendations in the application of these techniques for patient care, including quality assurance (QA) guidelines for these devices and their use with conformal and intensity modulated radiotherapy. The technologies covered by this report are motion-encompassing methods, respiratory gated techniques, breath-hold techniques, forced shallow-breathing methods, and respiration-synchronized techniques. The main outcome of this report is a clinical process guide for managing respiratory motion. Included in this guide is the recommendation that tumor motion should be measured (when possible) for each patient for whom respiratory motion is a concern. If target motion is greater than 5 mm, a method of respiratory motion management is available, and if the patient can tolerate the procedure, respiratory motion management technology is appropriate. Respiratory motion management is also appropriate when the procedure will increase normal tissue sparing. Respiratory motion management involves further resources, education and the development of and adherence to QA procedures.

Guidelines as Topic↗
PubMed2006

Improving IMRT dose accuracy via deliverable Monte Carlo optimization for the treatment of head and neck cancer patients.

The purpose of this work is to investigate the effect of dose-calculation accuracy on head and neck (H&N) intensity modulated radiation therapy (IMRT) plans by determining the systematic dose-prediction and optimization-convergence errors (DPEs and OCEs), using a superposition/convolution (SC) algorithm. Ten patients with locally advanced H&N squamous cell carcinoma who were treated with simultaneous integrated boost IMRT were selected for this study. The targets consisted of gross target volume (GTV), clinical target volume (CTV), and nodal target volumes (CTV nodes). The critical structures included spinal cord, parotid glands, and brainstem. For all patients, three IMRT plans were created: A: an SC optimized plan (SCopt), B: an SCopt plan recalculated with Monte Carlo [MC(SCopt)], and C: an MC optimized plan (MCopt). For each structure, DPEs and OCEs were estimated as DPE(SC)=D(B)-D(A) and OCE(SC)=D(C)-D(B) where A, B, and C stand for the three different optimized plans as defined above. Deliverable optimization was used for all plans, that is, a leaf-sequencing step was incorporated into the optimization loop at each iteration. The range of DPE(SC) in the GTV D98 varied from -1.9% to -4.9%, while the OCE(SC) ranged from 0.9% to 7.0%. The DPE(SC) in the contralateral parotid D50 reached 8.2%, while the OCE(SC) in the contralateral parotid D50 varied from 0.91% to 6.99%. The DPE(SC) in cord D2 reached -3.0%, while the OCE(SC) reached to -7.0%. The magnitude of the DPE(SC) and OCE(SC) differences demonstrate the importance of using the most accurate available algorithm in the deliverable IMRT optimization process, especially for the estimation of normal structure doses.

Algorithms↗
PubMed2005

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans.

PURPOSE: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. METHODS AND MATERIALS: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errors of sigma = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with Sigma = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for sigma = Sigma = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D(98)), clinical target volume (CTV) D(90), nodes D(90), cord D(2), and parotid D(50) and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. RESULTS: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error sigma exceeded 3 mm. Simulated systematic setup errors with Sigma = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a Sigma = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error. Combined random and systematic dose errors with sigma = Sigma = 3.0 mm resulted in more than 50% of plans having at least a 3% dose error and 38% of the plans having at least a 5% dose error. Evaluation with respect to a 3-mm expanded PTV reduced the observed dose deviations greater than 5% for the sigma = Sigma = 3.0 mm simulations to 5.4% of the plans simulated. CONCLUSIONS: Head-and-neck SIB-IMRT dosimetric accuracy would benefit from methods to reduce patient systematic setup errors. When GTV, CTV, or nodal volumes are used for dose evaluation, plans simulated including the effects of random and systematic errors deviate substantially from the nominal plan. The use of PTVs for dose evaluation in the nominal plan improves agreement with evaluated GTV, CTV, and nodal dose values under simulated setup errors. PTV concepts should be used for SIB-IMRT head-and-neck squamous cell carcinoma patients, although the size of the margins may be less than those used with three-dimensional conformal radiation therapy.

Algorithms↗
PubMed2005

Four-dimensional radiotherapy planning for DMLC-based respiratory motion tracking.

Four-dimensional (4D) radiotherapy is the explicit inclusion of the temporal changes in anatomy during the imaging, planning, and delivery of radiotherapy. Temporal anatomic changes can occur for many reasons, though the focus of the current investigation is respiration motion for lung tumors. The aim of this study was to develop 4D radiotherapy treatment-planning methodology for DMLC-based respiratory motion tracking. A 4D computed tomography (CT) scan consisting of a series of eight 3D CT image sets acquired at different respiratory phases was used for treatment planning. Deformable image registration was performed to map each CT set from the peak-inhale respiration phase to the CT image sets corresponding to subsequent respiration phases. Deformable registration allows the contours defined on the peak-inhale CT to be automatically transferred to the other respiratory phase CT image sets. Treatment planning was simultaneously performed on each of the eight 3D image sets via automated scripts in which the MLC-defined beam aperture conforms to the PTV (which in this case equaled the GTV due to CT scan length limitations) plus a penumbral margin at each respiratory phase. The dose distribution from each respiratory phase CT image set was mapped back to the peak-inhale CT image set for analysis. The treatment intent of 4D planning is that the radiation beam defined by the DMLC tracks the respiration-induced target motion based on a feedback loop including the respiration signal to a real-time MLC controller. Deformation with respiration was observed for the lung tumor and normal tissues. This deformation was verified by examining the mapping of high contrast objects, such as the lungs and cord, between image sets. For the test case, dosimetric reductions for the cord, heart, and lungs were found for 4D planning compared with 3D planning. 4D radiotherapy planning for DMLC-based respiratory motion tracking is feasible and may offer tumor dose escalation and/or a reduction in treatment-related complications. However, 4D planning requires new planning tools, such as deformable registration and automated treatment planning on multiple CT image sets.

Dose-Response Relationship, Radiation↗
PubMed2005

Photon-beam subsource sensitivity to the initial electron-beam parameters.

One limitation to the widespread implementation of Monte Carlo (MC) patient dose-calculation algorithms for radiotherapy is the lack of a general and accurate source model of the accelerator radiation source. Our aim in this work is to investigate the sensitivity of the photon-beam subsource distributions in a MC source model (with target, primary collimator, and flattening filter photon subsources and an electron subsource) for 6- and 18-MV photon beams when the energy and radial distributions of initial electrons striking a linac target change. For this purpose, phase-space data (PSD) was calculated for various mean electron energies striking the target, various normally distributed electron energy spread, and various normally distributed electron radial intensity distributions. All PSD was analyzed in terms of energy, fluence, and energy fluence distributions, which were compared between the different parameter sets. The energy spread was found to have a negligible influence on the subsource distributions. The mean energy and radial intensity significantly changed the target subsource distribution shapes and intensities. For the primary collimator and flattening filter subsources, the distribution shapes of the fluence and energy fluence changed little for different mean electron energies striking the target, however, their relative intensity compared with the target subsource change, which can be accounted for by a scaling factor. This study indicates that adjustments to MC source models can likely be limited to adjusting the target subsource in conjunction with scaling the relative intensity and energy spectrum of the primary collimator, flattening filter, and electron subsources when the energy and radial distributions of the initial electron-beam change.

Algorithms↗
PubMed2004

Monte Carlo-based treatment planning for a spoiler system with experimental validation using plane-parallel ionization chambers.

A beam spoiler is often used to increase the build-up dose near the surface for treatment of superficial treatment areas. Photon-beam spoilers produce a large amount of contaminant electrons, conditions for which standard, commercial treatment-planning system dose-calculation algorithms are inadequate for producing accurate dose calculations. In this study, we implemented a Monte Carlo (MC) dose-calculation algorithm for this spoiler system. With and without a spoiler of 1 cm Lucite, depth doses and transverse profiles in the build-up region were measured for field sizes of 5 x 5 cm2 and 10 x 10 cm2 at the spoiler-to-surface distances (STSDs) of 6, 10 and 15 cm. An Attix chamber and a Markus chamber were used for depth doses, whereas a diode detector was used for transverse profiles. An MC simulation using BEAM/DOSXYZ was used to compare the calculated and the measured data. The MC calculations agreed with the Attix chamber measurements within 2% for all STSDs and field sizes, whereas the Markus data--even with corrections made-showed a discrepancy of about 3.5% with a maximum difference of 7.3% for a field size of 10 x 10 cm2 at an STSD of 6 cm. The MC treatment-planning system was successfully applied to a head-and-neck case using 6 MV photon beams with a beam spoiler.

Algorithms↗
PubMed2004

Monte Carlo computation of dosimetric amorphous silicon electronic portal images.

This study develops and tests a method to compute dosimetric images for an amorphous silicon (a-Si) flat-panel detector so that an accurate quantitative comparison between measured and computed portal images may be made. An EGS4-based Monte Carlo (MC) algorithm is developed to efficiently tally the energy deposition through the use of a virtual detector dose-scoring methodology. The complete geometry of the a-Si imager is utilized in the MC calculation up to the imager rear housing, which is replaced with a uniform thickness material slab. The detector-mounting hardware is modeled as a uniform backscattering material. The amount of backscatter material required to reproduce the measured backscatter is 0.98 g/cm2 of water. A flood-field irradiation, performed in the measurement imaging session, is used to cross-calibrate the computed images with the measured images. Calibrated MC-computed images reproduce measured field-size dependencies of the electronic portal imaging device (EPID) response to within <1%, without the need for optical glare or other empirical corrections. A 10% dose difference between measured and computed images was observed outside the field edge for a 10 x 10 cm2 field that was entirely blocked by the multileaf collimator (MLC). However, this error corresponded with less than 0.15% of the open-field dose. For 10 x 10 cm2 fields produced by 5 and 20 mm dynamically sweeping MLC gaps, more than 98% of the points were found to have a gamma less than one with a 2%, 2 mm criteria. For an intensity modulated radiation therapy (IMRT) patient test field, over 99% of the points were found to have a gamma less than one with a 2%, 2 mm criteria. This study demonstrates that MC can be an effective tool for predicting measured a-Si portal images and may be useful for IMRT EPID-based dosimetry.

Algorithms↗
PubMed2004

Monte Carlo source model for photon beam radiotherapy: photon source characteristics.

A major barrier to widespread clinical implementation of Monte Carlo dose calculation is the difficulty in characterizing the radiation source within a generalized source model. This work aims to develop a generalized three-component source model (target, primary collimator, flattening filter) for 6- and 18-MV photon beams that match full phase-space data (PSD). Subsource by subsource comparison of dose distributions, using either source PSD or the source model as input, allows accurate source characterization and has the potential to ease the commissioning procedure, since it is possible to obtain information about which subsource needs to be tuned. This source model is unique in that, compared to previous source models, it retains additional correlations among PS variables, which improves accuracy at nonstandard source-to-surface distances (SSDs). In our study, three-dimensional (3D) dose calculations were performed for SSDs ranging from 50 to 200 cm and for field sizes from 1 x 1 to 30 x 30 cm2 as well as a 10 x 10 cm2 field 5 cm off axis in each direction. The 3D dose distributions, using either full PSD or the source model as input, were compared in terms of dose-difference and distance-to-agreement. With this model, over 99% of the voxels agreed within +/-1% or 1 mm for the target, within 2% or 2 mm for the primary collimator, and within +/-2.5% or 2 mm for the flattening filter in all cases studied. For the dose distributions, 99% of the dose voxels agreed within 1% or 1 mm when the combined source model-including a charged particle source and the full PSD as input-was used. The accurate and general characterization of each photon source and knowledge of the subsource dose distributions should facilitate source model commissioning procedures by allowing scaling the histogram distributions representing the subsources to be tuned.

Algorithms↗
PubMed2003

Tumor control probability predictions for genetic radiotherapy.

PURPOSE: Genetic radiotherapy, the combination of gene therapy and radiation therapy, for cancer treatment is evolving from laboratory studies to clinical trials. Genetic radiotherapy involves the viral infection of cells that change the sensitivity of transduced cells to radiation. Because there is no patient outcome data for genetic radiotherapy, prospective models are needed to determine the expected benefit of this new modality. Such a prospective model has been developed in this work. METHODS AND MATERIALS: An existing tumor control probability (TCP) calculation model developed for external beam radiotherapy was modified for genetic radiotherapy. Specifically, the (1) transduced fraction and (2) enhancement factor of the transduced cells were included in the model. Parametric studies of the effects of these two variables on TCP for head-and-neck cancer were performed. RESULTS: Using reasonable transduction fraction and enhancement factor values (0.8 and 1.4, respectively), the model predicts an increase in the TCP for genetic radiotherapy over radiotherapy alone by up to 15% for the same radiotherapy dose. The theoretical limit of TCP increase was calculated to be near 70%, which may occur with improved techniques that increase the transduced fraction or because of a strong bystander effect. To maintain existing TCP, dose reductions from 5 Gy (reasonable values) to >30 Gy (ideal case) are predicted for genetic radiotherapy over radiotherapy alone. CONCLUSIONS: Our results indicate that genetic radiotherapy has the potential to significantly improve tumor control over radiotherapy alone.

Combined Modality Therapy↗
PubMed2003

Patient training in respiratory-gated radiotherapy.

Respiratory gating is used to counter the effects of organ motion during radiotherapy for chest tumors. The effects of variations in patient breathing patterns during a single treatment and from day to day are unknown. We evaluated the feasibility of using patient training tools and their effect on the breathing cycle regularity and reproducibility during respiratory-gated radiotherapy. To monitor respiratory patterns, we used a component of a commercially available respiratory-gated radiotherapy system (Real Time Position Management (RPM) System, Varian Oncology Systems, Palo Alto, CA 94304). This passive marker video tracking system consists of reflective markers placed on the patient's chest or abdomen, which are detected by a wall-mounted video camera. Software installed on a PC interfaced to this camera detects the marker motion digitally and records it. The marker position as a function of time serves as the motion signal that may be used to trigger imaging or treatment. The training tools used were audio prompting and visual feedback, with free breathing as a control. The audio prompting method used instructions to "breathe in" or "breathe out" at periodic intervals deduced from patients' own breathing patterns. In the visual feedback method, patients were shown a real-time trace of their abdominal wall motion due to breathing. Using this, they were asked to maintain a constant amplitude of motion. Motion traces of the abdominal wall were recorded for each patient for various maneuvers. Free breathing showed a variable amplitude and frequency. Audio prompting resulted in a reproducible frequency; however, the variability and the magnitude of amplitude increased. Visual feedback gave a better control over the amplitude but showed minor variations in frequency. We concluded that training improves the reproducibility of amplitude and frequency of patient breathing cycles. This may increase the accuracy of respiratory-gated radiation therapy.

Acoustic Stimulation↗
PubMed2003

Radiotherapy dose calculations in the presence of hip prostheses.

The high density and atomic number of hip prostheses for patients undergoing pelvic radiotherapy challenge our ability to accurately calculate dose. A new clinical dose calculation algorithm, Monte Carlo, will allow accurate calculation of the radiation transport both within and beyond hip prostheses. The aim of this research was to investigate, for both phantom and patient geometries, the capability of various dose calculation algorithms to yield accurate treatment plans. Dose distributions in phantom and patient geometries with high atomic number prostheses were calculated using Monte Carlo, superposition, pencil beam, and no-heterogeneity correction algorithms. The phantom dose distributions were analyzed by depth dose and dose profile curves. The patient dose distributions were analyzed by isodose curves, dose-volume histograms (DVHs) and tumor control probability/normal tissue complication probability (TCP/NTCP) calculations. Monte Carlo calculations predicted the dose enhancement and reduction at the proximal and distal prosthesis interfaces respectively, whereas superposition and pencil beam calculations did not. However, further from the prosthesis, the differences between the dose calculation algorithms diminished. Treatment plans calculated with superposition showed similar isodose curves, DVHs, and TCP/NTCP as the Monte Carlo plans, except in the bladder, where Monte Carlo predicted a slightly lower dose. Treatment plans calculated with either the pencil beam method or with no heterogeneity correction differed significantly from the Monte Carlo plans.

Algorithms↗
PubMed2003

Image reconstruction and the effect on dose calculation for hip prostheses.

High atomic number inserts, such as hip prostheses and dental fillings, cause streak artifacts on computed tomography (CT) images when filtered back-projection (FBP) methods are used. These streak artifacts severely degrade our ability to differentiate the tumor volume. Also, incorrect Hounsfield numbers yield incorrect electron density information that may lead to erroneous dose calculations, and, as a result, compromise clinical outcomes. The aim of this research was to evaluate the dosimetric consequences of artifacts during radiotherapy planning of a prostate patient containing a hip prosthesis. The CT numbers corresponding to an iron prosthesis were inserted into the right femoral head of an existing CT image set. This artifact-free image was used as the standard image set. CT projections through the image set formed the sinogram, from which filtered back projection and iterative deblurring methods were used to create reconstructed image sets. These reconstructed image sets contained artifacts. Prostate treatment plans were then calculated using a Monte Carlo system for the standard and reconstructed CT image sets. Close to the prosthesis, the CT numbers between the reconstructed and standard image sets differed substantially. However, because the CT number differences covered only a small area, the dose distributions on the reconstructed and standard image sets were not significantly different. The dose-volume histograms for the prostate, rectum, and bladder were virtually identical. Our results indicate that even though CT image artifacts restrict our ability to differentiate tumors and critical structures, the dose distributions for a prostate plan containing a hip prosthesis, calculated on both artifact-free image sets and image sets containing artifacts, are not significantly different.

Algorithms↗