Quantitative evaluation of dosimetric uncertainties associated with small electron fields.

INTRODUCTION: Although many studies have investigated small electron fields, there are several dosimetric issues that are not well understood. This includes lack of charged particle equilibrium, lateral scatter, source occlusion and volume averaging of the detectors used in the measurement of the commissioning data. High energy electron beams are also associated with bremsstrahlung production that contributes to dose deposition, which is not well investigated, particularly for small electron fields. The goal of this work has been to investigate dosimetric uncertainties associated with small electron fields using dose measurements with different detectors as well as calculations with eMC dose calculation algorithm. METHODS: Different dosimetric parameters including output factors, depth dose curves and dose profiles from small electron field cutouts were investigated quantitatively. These dosimetric parameters were measured using different detectors that included small ion chambers and diodes for small electron cutouts with diameters ranging from 15-50mm mounted on a 6 × 6cm2 cone with beam energies from 6-20MeV. RESULTS: Large deviations existed between the output factors calculated with the eMC algorithm and measured with small detectors for small electron fields up to 55% for 6MeV. The discrepancy between the calculated and measured doses increased 10%-55% with decreasing electron beam energy from 20 MeV to 6 MeV for 15mm circular field. For electron fields with cutouts 20mm and larger, the measured and calculated doses agreed within 5% for all electron energies from 6-20MeV. For small electron fields, the maximal depth dose shifted upstream and becomes more superficial as the electron beam energy increases from 6-20MeV as measured with small detectors. DISCUSSION: Large dose discrepancies were found between the measured and calculated doses for small electron fields where the eMC underestimated output factors by 55% for small circular electron fields with a diameter of 15 mm, particularly for low energy electron beams. The measured entrance doses and dmax of the depth dose curves did not agree with the corresponding values calculated by eMC. Furthermore, the measured dose profiles showed enhanced dose deposition in the umbra region and outside the small fields, which mostly resulted from dose deposition from the bremsstrahlung produced by high energy electrons that was not accounted for by the eMC algorithm due to inaccurate modeling of the lateral dose deposition from bremsstrahlung. CONCLUSION: Electron small field dosimetry require more consideration of variations in beam quality, lack of charged particle equilibrium, lateral scatter loss and dose deposition from bremsstrahlung produced by energetic electron beams in a comprehensive approach similar to photon small field dosimetry. Furthermore, most of the commercially available electron dose calculation algorithms are commissioned with large electron fields; therefore, vendors should provide tools for the modeling of electron dose calculation algorithms for small electron fields.

Quantitative evaluation of dosimetric uncertainties in electron therapy by measurement and calculation using the electron Monte Carlo dose algorithm in the Eclipse treatment planning system.

In the electron beam radiation therapy, customized blocks are mostly used to shape treatment fields to generate conformal doses. The goal of this study is to investigate quantitatively dosimetric uncertainties associated with heterogeneities, detectors used in the measurement of the beam data commissioning, and modeling of the interactions of high energy electrons with tissue. These uncertainties were investigated both by measurements with different detectors and calculations using electron Monte Carlo algorithm (eMC) in the Eclipse treatment planning system. Dose distributions for different field sizes were calculated using eMC and measured with a multiple-diode-array detector (MapCheck2) for cone sizes ranging from 6 to 25 cm. The dose distributions were calculated using the CT images of the MapCheck2 and water-equivalent phantoms. In the umbra region (<20% isodose line), the eMC underestimated dose by a factor of 3 for high energy electron beams due to lack of consideration of bremsstrahlung emitted laterally that was not accounted by eMC in the low dose region outside the field. In the penumbra (20%-80% isodose line), the eMC overestimated dose (40%) for high energy 20 MeV electrons compared to the measured dose with small diodes in the high gradient dose region. This was mainly due to lack of consideration of volume averaging of the ion chamber used in beam data commissioning which was input to the eMC dose calculation algorithm. Large uncertainties in the CT numbers (25%) resulted from the image artifacts in the CT images of the MapCheck2 phantom due to metal artifacts. The eMC algorithm used the electron and material densities extracted from the CT numbers which resulted large dosimetric uncertainties (10%) in the material densities and corresponding stopping power ratios. The dose calculations with eMC are associated with large uncertainties particularly in penumbra and umbra regions and around heterogeneities which affect the low dose level that cover nearby normal tissue or critical structures.

Quantitative evaluation of the performance of different deformable image registration algorithms in helical, axial, and cone-beam CT images using a mobile phantom.

The goal of this project is to investigate quantitatively the performance of different deformable image registration algorithms (DIR) with helical (HCT), axial (ACT), and cone-beam CT (CBCT). The variations in the CT-number values and lengths of well-known targets moving with controlled motion were evaluated. Four DIR algorithms: Demons, Fast-Demons, Horn-Schunck and Lucas-Kanade were used to register intramodality CT images of a mobile phantom scanned with different imaging techniques. The phantom had three water-equivalent targets inserted in a low-density foam with different lengths (10-40 mm) and moved with adjustable motion amplitudes (0-20 mm) and frequencies (0-0.5 Hz). The variations in the CT-number level, volumes and shapes of these targets were measured from the spread-out of the CT-number distributions. In CBCT, most of the DIR algorithms were able to produce the actual lengths of the mobile targets; however, the CT-number values obtained from the DIR algorithms deviated from the actual CT-number of the targets. In HCT, the DIR algorithms were successful in deforming the images of the mobile targets to the images of the stationary targets producing the CT-number values and lengths of the targets for motion amplitudes <20 mm. Similarly in ACT, all DIR algorithms produced the actual CT-number values and lengths of the stationary targets for low-motion amplitudes <15 mm. The optical flow-based DIR algorithms such as the Horn-Schunck and Lucas-Kanade performed better than the Demons and Fast-Demons that are based on attraction forces particularly at large motion amplitudes. In conclusion, most of the DIR algorithms did not reproduce well the CT-number values and lengths of the targets in images that have artifacts induced by large motion amplitudes. The deviations in the CT-number values and variations in the volume of the mobile targets in the deformed CT images produced by the different DIR algorithms need to be considered carefully in the treatment planning for accurate dose calculation dose coverage of the tumor, and sparing of critical structures.

Quantitative evaluation by measurement and modeling of the variations in dose distributions deposited in mobile targets.

The objective of this study is to quantitatively evaluate variations of dose distributions deposited in mobile target by measurement and modeling. The effects of variation in dose distribution induced by motion on tumor dose coverage and sparing of normal tissues were investigated quantitatively. The dose distributions with motion artifacts were modeled considering different motion patterns that include (a) motion with constant speed and (b) sinusoidal motion. The model predictions of the dose distributions with motion artifacts were verified with measurement where the dose distributions from various plans that included three-dimensional conformal and intensity-modulated fields were measured with a multiple-diode-array detector (MapCheck2), which was mounted on a mobile platform that moves with adjustable motion parameters. For each plan, the dose distributions were then measured with MapCHECK2 using different motion amplitudes from 0-25 mm. In addition, mathematical modeling was developed to predict the variations in the dose distributions and their dependence on the motion parameters that included amplitude, frequency and phase for sinusoidal motions. The dose distributions varied with motion and depended on the motion pattern particularly the sinusoidal motion, which spread out along the direction of motion. Study results showed that in the dose region between isocenter and the 50% isodose line, the dose profile decreased with increase of the motion amplitude. As the range of motion became larger than the field length along the direction of motion, the dose profiles changes overall including the central axis dose and 50% isodose line. If the total dose was delivered over a time much longer than the periodic time of motion, variations in motion frequency and phase do not affect the dose profiles. As a result, the motion dose modeling developed in this study provided quantitative characterization of variation in the dose distributions induced by motion, which can be employed in radiation therapy to quantitatively determine the margins needed for treatment planning considering dose spillage to normal tissue.

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PURPOSE: A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. MATERIALS AND METHODS: The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. RESULTS: Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. CONCLUSION: A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Modeling and measurement of the variations of CT number distributions for mobile targets in cone-beam computed tomographic imaging.

The purpose of this study was to investigate quantitatively by measurement and modeling the variations in CT number distributions of mobile targets in cone-beam CT (CBCT) imaging. CBCT images were acquired for three targets manufactured from homogenous water-equivalent gel that was inserted into a commercial mobile thorax phantom. The phantom moved with a controlled cyclic motion in one-dimension along the superior-inferior direction to simulate patient respiratory motion. Profiles of the CT number distributions of the static and mobile targets were obtained using CBCT images. A mathematical model was developed that predicted the variations in CT number distributions and their dependence on the motion parameters of targets moving in one-dimension using CBCT imaging. The measured CT number distributions for the mobile targets varied considerably, depending on the motion parameters. The extension of the CT number distribution increased linearly with motion amplitude where maximum target elongation reached twice the motion amplitude. The CT number levels of the mobile targets were smeared over a longer distribution; for example, the CT number level for the 20 mm target dropped by nearly 30% at motion amplitude (A) equal to 20 mm in comparison with the CT number distribution of stationary targets. Frequency of motion played an important role in spatial and level variations of the CT number distributions. For example, the level of the CT number profile for the medium target (20 mm) decreased evenly by nearly 50% at A = 20 mm with high motion frequencies. Motion phase did not affect the CT number distributions for prolonged projection acquisition that included several respiratory cycles. The mathematical model of the CT number distributions of mobile targets in CBCT reproduced well the measured CT number distributions and predicted their dependence on the target size and phantom motion parameters such as speed, amplitude, frequency, and phase. The CT number distributions varied considerably with motion in CBCT. A motion model of CT number distribution for mobile targets has been developed in this work that predicted well the variations in the measured CT number profiles and their dependence on motion parameters. The model corrected the CT number distribution retrospective to CT image reconstruction where it used a first-order linear relationship between the number of projections collected in the imaging window of a mobile voxel to obtain the cumulative CT number. This model provides quantitative characterization of motion artifacts on CT number distributions in CBCT that is useful to determine the validity of CT numbers and the accuracy of localization and volume measurement of tumors in diagnostic imaging and interventional applications, such as radiotherapy.

Quantitative assessment by measurement and modeling of mobile target elongation in cone-beam computed tomographic imaging.

The purpose of this study was to assess quantitatively elongation of mobile targets in cone-beam CT (CBCT) imaging by measurement and modeling. A mathematical model was derived that predicts the measured lengths of mobile targets and its dependence on target size and motion patterns in CBCT imaging. Three tissue-equivalent targets of differing sizes were inserted in an artificial thorax phantom to simulate lung lesions. Respiratory motion was mimicked with a mobile phantom that moves in one-dimension along the superior-inferior direction at a respiration frequency of 0.24 Hz for eight different amplitudes in the range 0-40 mm. A mathematical model was derived to quantify the variations in target lengths and its dependence on phantom motion parameters in CBCT. Predictions of the model were verified by measurement of the lengths of mobile targets in CBCT images. The model predicts that target lengths increased linearly with increase in speed and amplitude of phantom motion in CBCT. The measured lengths of mobile targets imaged with CBCT agreed with the calculated lengths within half-slice thickness spatial resolution. The maximal length of a mobile target was independent of the frequency and phase of motion. Elongation of mobile targets was similar in half-fan and full-fan CBCT for similar motion patterns, as long as the targets remained within the imaging view. Mobile targets elongated linearly with phantom speed and motion amplitude in CBCT imaging. The model introduced in this work assessed quantitatively the variation in target lengths induced by motion, which may be a useful tool to consider elongations of mobile targets in CBCT applications in diagnostic imaging and radiotherapy.

Theoretical modeling of mobile target broadening in helical and axial computed tomographic imaging.

PURPOSE: To investigate variations in mobile target length induced by sinusoidal motion in helical (HCT) and axial CT (ACT) imaging. A mathematical model was derived that predicts the measured broadening of the apparent lengths of mobile targets and its dependence on motion parameters, target size, and imaging couch speed in CT images. MATERIALS AND METHODS: Three mobile targets of differing lengths and sizes were constructed of tissue-equivalent gel material and embedded into artificial lung phantom. Respiratory motion was mimicked with a mobile phantom that moves in one-dimension along the superior-inferior direction with sinusoidal motion patterns. A mathematical model was derived to predict quantitatively the variations of apparent lengths for mobile targets and its dependence on phantom and imaging couch motion parameters in HCT and ACT. The model predictions were verified by length measurements of the mobile phantom targets that were imaged with the different motion patterns using CT imaging. RESULTS: The measured lengths of mobile targets enlarged or shrunk depending on the phantom motion parameters that include phantom speed, amplitude, frequency, phase and speed of the imaging couch. The target length variations were significant where some targets doubled lengths or shrunk to less than half of their actual length. The apparent lengths of mobile targets decreased if the target was moving in the same direction as the imaging couch motion and increased if the mobile target was moving opposed to imaging couch in both HCT and ACT. The model predicts well the variations in the mobile target apparent lengths and their dependence on the motion parameters. CONCLUSION: The measured and model variations of apparent lengths of mobile targets are considerable and may affect the accuracy of tumor volumes obtained from HCT and ACT. This mathematical model provides a method to quantitatively assess the length variations of mobile targets and their dependence on motion parameters of the phantom and imaging system which may have potential applications in the fields of diagnostic imaging and radiotherapy.

Correction of image artifacts from treatment couch in cone-beam CT from kV on-board imaging.

PURPOSE: To investigate image artifacts caused by a standard treatment couch on cone-beam CT (CBCT) images from a kV on-board imager and to develop an algorithm based on spatial domain filtering to remove image artifacts in CBCT induced by the treatment couch. METHODS: Image artifacts in CBCT induced by the treatment couch were quantified by scanning a phantom used to quantify CT image performance. This was performed by scanning the phantom setup on a regular treatment couch and in air with the kV on-board imager. An algorithm was developed to filter image artifacts from the treatment couch by processing of cone-beam radiographic projections using two scans: one scan of the phantom and treatment couch and a second scan of the treatment couch only. This algorithm is based on a pixel-by-pixel removal of beam attenuation due to the treatment couch from each projection of the phantom and couch scan. The net couch-filtered projections were then used to reconstruct CBCT. RESULTS: We found that the treatment couch causes considerable image artifacts: CT number uniformity is degraded and varies as much as 15%, and noise in CBCT scans with phantom plus couch (3.5%) is higher than for the phantom in air (1.5%). The spatial domain filtering technique reduces noise by more than 1.5%, improves uniformity by a factor of 2, and removes ringing and streaking artifacts related to the standard treatment couch in CBCT reconstructed from couch-filtered projections. This filtering technique was tested successfully to filter other hardware objects such as a patient immobilization body-fix frame. CONCLUSIONS: The standard treatment couch causes image artifact in CBCT from kV on-board imaging systems. The spatial domain filtering technique developed in this work improves image quality of CBCT by preprocessing the projections prior to CBCT reconstruction. This technique might be useful to filter other hardware objects from CBCT which may contribute to the degradation of image quality.

An algorithm to extract three-dimensional motion by marker tracking in the kV projections from an on-board imager: four-dimensional cone-beam CT and tumor tracking implications.

The purpose of this work is to extract three-dimensional (3D) motion trajectories of internal implanted and external skin-attached markers from kV cone-beam projections and reduce image artifact from patient motion in cone-beam computed tomography (CBCT) from on-board imager. Cone beam radiographic projections were acquired for a mobile phantom and liver patients with internal implanted and external skin-attached markers. An algorithm was developed to automatically find the positions of the markers in the projections. It uses normalized cross-correlation between a template image of a metal seed marker and the projections to find the marker position. From these positions and time-tagged angular views, the marker 3D motion trajectory was obtained over a time interval of nearly one minute, which is the time required for scanning. This marker trajectory was used to remap the pixels of the projections to eliminate motion. Then, the motion-corrected projections were used to reconstruct CBCT. An algorithm was developed to extract 3D motion trajectories of internal and external markers from cone-beam projections using a kV monoscopic on-board imager. This algorithm was tested and validated using a mobile phantom and patients with liver masses that had radio-markers implanted in the tumor and attached to the skin. The extracted motion trajectories were used to investigate motion correlation between internal and external markers in liver patients. Image artifacts from respiratory motion were reduced in CBCT reconstructed from cone-beam projections that were preprocessed to remove motion shifts obtained from marker tracking. With this method, motion-related image artifacts such as blurring and spatial distortion were reduced, and contrast and position resolutions were improved significantly in CBCT reconstructed from motion-corrected projections. Furthermore, correlated internal and external marker 3D-motion tracks obtained from the kV projections might be useful for 4DCBCT, beam gating and tumor motion monitoring or tracking.