Volume 42, Issue 9, September 2015
Index of content:
Calibration of radiotherapy ionization chambers using Co-60 is outdated and should be replaced by direct calibration in linear accelerator beams42(2015); http://dx.doi.org/10.1118/1.4922710View Description Hide Description
- RADIATION THERAPY PHYSICS
Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer42(2015); http://dx.doi.org/10.1118/1.4927567View Description Hide DescriptionPurpose:
The aim of this study was to assess whether clinically acceptable segmentations of organs at risk (OARs) in head and neck cancer can be obtained automatically and efficiently using the novel “similarity and truth estimation for propagated segmentations” (STEPS) compared to the traditional “simultaneous truth and performance level estimation” (STAPLE) algorithm.Methods:
First, 6 OARs were contoured by 2 radiation oncologists in a dataset of 100 patients with head and neck cancer on planning computed tomography images. Each image in the dataset was then automatically segmented with STAPLE and STEPS using those manual contours. Dice similarity coefficient (DSC) was then used to compare the accuracy of these automatic methods. Second, in a blind experiment, three separate and distinct trained physicians graded manual and automatic segmentations into one of the following three grades: clinically acceptable as determined by universal delineation guidelines (grade A), reasonably acceptable for clinical practice upon manual editing (grade B), and not acceptable (grade C). Finally, STEPS segmentations graded B were selected and one of the physicians manually edited them to grade A. Editing time was recorded.Results:
Significant improvements in DSC can be seen when using the STEPS algorithm on large structures such as the brainstem, spinal canal, and left/right parotid compared to the STAPLE algorithm (all p < 0.001). In addition, across all three trained physicians, manual and STEPS segmentation grades were not significantly different for the brainstem, spinal canal, parotid (right/left), and optic chiasm (all p > 0.100). In contrast, STEPS segmentation grades were lower for the eyes (p < 0.001). Across all OARs and all physicians, STEPS produced segmentations graded as well as manual contouring at a rate of 83%, giving a lower bound on this rate of 80% with 95% confidence. Reduction in manual interaction time was on average 61% and 93% when automatic segmentations did and did not, respectively, require manual editing.Conclusions:
The STEPS algorithm showed better performance than the STAPLE algorithm in segmenting OARs for radiotherapy of the head and neck. It can automatically produce clinically acceptable segmentation of OARs, with results as relevant as manual contouring for the brainstem, spinal canal, the parotids (left/right), and optic chiasm. A substantial reduction in manual labor was achieved when using STEPS even when manual editing was necessary.
42(2015); http://dx.doi.org/10.1118/1.4927557View Description Hide DescriptionPurpose:
CyberKnife® robotic surgery system has the ability to deliver radiation to a tumor subject to respiratory movements using Synchrony® mode with less than 2 mm tracking accuracy. However, rapid and rough motion tracking causes mechanical tracking errors and puts mechanical stress on the robotic joint, leading to unexpected radiation delivery errors. During clinical treatment, patient respiratory motions are much more complicated, suggesting the need for patient-specific modeling of respiratory motion. The purpose of this study was to propose a novel method that provides a reference respiratory wave to enable smooth tracking for each patient.Methods:
The minimum jerk model, which mathematically derives smoothness by means of jerk, or the third derivative of position and the derivative of acceleration with respect to time that is proportional to the time rate of force changed was introduced to model a patient-specific respiratory motion wave to provide smooth motion tracking using CyberKnife®. To verify that patient-specific minimum jerk respiratory waves were being tracked smoothly by Synchrony® mode, a tracking laser projection from CyberKnife® was optically analyzed every 0.1 s using a webcam and a calibrated grid on a motion phantom whose motion was in accordance with three pattern waves (cosine, typical free-breathing, and minimum jerk theoretical wave models) for the clinically relevant superior–inferior directions from six volunteers assessed on the same node of the same isocentric plan.Results:
Tracking discrepancy from the center of the grid to the beam projection was evaluated. The minimum jerk theoretical wave reduced the maximum-peak amplitude of radial tracking discrepancy compared with that of the waveforms modeled by cosine and typical free-breathing model by 22% and 35%, respectively, and provided smooth tracking for radial direction. Motion tracking constancy as indicated by radial tracking discrepancy affected by respiratory phase was improved in the minimum jerk theoretical model by 7.0% and 13% compared with that of the waveforms modeled by cosine and free-breathing model, respectively.Conclusions:
The minimum jerk theoretical respiratory wave can achieve smooth tracking by CyberKnife® and may provide patient-specific respiratory modeling, which may be useful for respiratory training and coaching, as well as quality assurance of the mechanical CyberKnife® robotic trajectory.
A treatment planning study to assess the feasibility of laser-driven proton therapy using a compact gantry design42(2015); http://dx.doi.org/10.1118/1.4927717View Description Hide DescriptionPurpose:
Laser-driven proton acceleration is suggested as a cost- and space-efficient alternative for future radiation therapy centers, although the properties of these beams are fairly different compared to conventionally accelerated proton beams. The laser-driven proton beam is extremely pulsed containing a very high proton number within ultrashort bunches at low bunch repetition rates of few Hz and the energy spectrum of the protons per bunch is very broad. Moreover, these laser accelerated bunches are subject to shot-to-shot fluctuations. Therefore, the aim of this study was to investigate the feasibility of a compact gantry design for laser-driven proton therapy and to determine limitations to comply with.Methods:
Based on a published gantry beam line design which can filter parabolic spectra from an exponentially decaying broad initial spectrum, a treatment planning study was performed on real patient data sets. All potential parabolic spectra were fed into a treatment planning system and numerous spot scanning proton plans were calculated. To investigate limitations in the fluence per bunch, the proton number of the initial spectrum and the beam width at patient entrance were varied. A scenario where only integer shots are delivered as well as an intensity modulation from shot to shot was studied. The resulting plans were evaluated depending on their dosimetric quality and in terms of required treatment time. In addition, the influence of random shot-to-shot fluctuations on the plan quality was analyzed.Results:
The study showed that clinically relevant dose distributions can be produced with the system under investigation even with integer shots. For small target volumes receiving high doses per fraction, the initial proton number per bunch must remain between 1.4 × 108 and 8.3 × 109 to achieve acceptable delivery times as well as plan qualities. For larger target volumes and standard doses per fraction, the initial proton number is even more restricted to stay between 1.4 × 109 and 2.9 × 109. The lowest delivery time that could be reached for such a case was 16 min for a 10 Hz system. When modulating the intensity from shot to shot, the delivery time can be reduced to 6 min for this scenario. Since the shot-to-shot fluctuations are of random nature, a compensation effect can be observed, especially for higher laser shot numbers. Therefore, a fluctuation of ±30% within the proton number does not translate into a dosimetric deviation of the same size. However, for plans with short delivery times these fluctuations cannot cancel out sufficiently, even for ±10% fluctuations.Conclusions:
Under the analyzed terms, it is feasible to achieve clinically relevant dose distributions with laser-driven proton beams. However, to keep the delivery times of the proton plans comparable to conventional proton plans for typical target volumes, a device is required which can modulate the bunch intensity from shot to shot. From the laser acceleration point of view, the proton number per bunch must be kept under control as well as the reproducibility of the bunches.
42(2015); http://dx.doi.org/10.1118/1.4927789View Description Hide DescriptionPurpose:
Helium ions (4He) may supplement current particle beam therapy strategies as they possess advantages in physical dose distribution over protons. To assess potential clinical advantages, a dose calculation module accounting for relative biological effectiveness (RBE) was developed and integrated into the treatment planning system Hyperion.Methods:
Current knowledge on RBE of 4He together with linear energy transfer considerations motivated an empirical depth-dependent “zonal” RBE model. In the plateau region, a RBE of 1.0 was assumed, followed by an increasing RBE up to 2.8 at the Bragg-peak region, which was then kept constant over the fragmentation tail. To account for a variable proton RBE, the same model concept was also applied to protons with a maximum RBE of 1.6. Both RBE models were added to a previously developed pencil beam algorithm for physical dose calculation and included into the treatment planning system Hyperion. The implementation was validated against Monte Carlo simulations within a water phantom using γ-index evaluation. The potential benefits of 4He based treatment plans were explored in a preliminary treatment planning comparison (against protons) for four treatment sites, i.e., a prostate, a base-of-skull, a pediatric, and a head-and-neck tumor case. Separate treatment plans taking into account physical dose calculation only or using biological modeling were created for protons and 4He.Results:
Comparison of Monte Carlo and Hyperion calculated doses resulted in a γ mean of 0.3, with 3.4% of the values above 1 and γ 1% of 1.5 and better. Treatment plan evaluation showed comparable planning target volume coverage for both particles, with slightly increased coverage for 4He. Organ at risk (OAR) doses were generally reduced using 4He, some by more than to 30%. Improvements of 4He over protons were more pronounced for treatment plans taking biological effects into account. All OAR doses were within tolerances specified in the QUANTEC report.Conclusions:
The biological 4He model proposed above is a first approach matching biological data published so far. The advantage of 4He seems to lie in the reduction of dose to surrounding tissue and to OARs. Nevertheless, additional biological experiments and treatment planning studies with larger patient numbers and more tumor indications are necessary to study the possible benefits of helium ion beam therapy in detail.
42(2015); http://dx.doi.org/10.1118/1.4928145View Description Hide DescriptionPurpose:
A conventional broad beam method is applied to carbon ion radiotherapy at Gunma University Heavy Ion Medical Center. According to this method, accelerated carbon ions are scattered by various beam line devices to form 3D dose distribution. The physical dose per monitor unit (d/MU) at the isocenter, therefore, depends on beam line parameters and should be calibrated by a measurement in clinical practice. This study aims to develop a calculation algorithm for d/MU using beam line parameters.Methods:
Two major factors, the range shifter dependence and the field aperture effect, are measured via PinPoint chamber in a water phantom, which is an identical setup as that used for monitor calibration in clinical practice. An empirical monitor calibration method based on measurement results is developed using a simple algorithm utilizing a linear function and a double Gaussian pencil beam distribution to express the range shifter dependence and the field aperture effect.Results:
The range shifter dependence and the field aperture effect are evaluated to have errors of 0.2% and 0.5%, respectively. The proposed method has successfully estimated d/MU with a difference of less than 1% with respect to the measurement results. Taking the measurement deviation of about 0.3% into account, this result is sufficiently accurate for clinical applications.Conclusions:
An empirical procedure to estimate d/MU with a simple algorithm is established in this research. This procedure allows them to use the beam time for more treatments, quality assurances, and other research endeavors.
A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy a)42(2015); http://dx.doi.org/10.1118/1.4928485View Description Hide DescriptionPurpose:
To develop an automatic segmentation algorithm integrating imaging information from computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI) to delineate target volume in head and neck cancer radiotherapy.Methods:
Eleven patients with unresectable disease at the tonsil or base of tongue who underwent MRI, CT, and PET/CT within two months before the start of radiotherapy or chemoradiotherapy were recruited for the study. For each patient, PET/CT and T1-weighted contrast MRI scans were first registered to the planning CT using deformable and rigid registration, respectively, to resample the PET and magnetic resonance (MR) images to the planning CT space. A binary mask was manually defined to identify the tumor area. The resampled PET and MR images, the planning CT image, and the binary mask were fed into the automatic segmentation algorithm for target delineation. The algorithm was based on a multichannel Gaussian mixture model and solved using an expectation–maximization algorithm with Markov random fields. To evaluate the algorithm, we compared the multichannel autosegmentation with an autosegmentation method using only PET images. The physician-defined gross tumor volume (GTV) was used as the “ground truth” for quantitative evaluation.Results:
The median multichannel segmented GTV of the primary tumor was 15.7 cm3 (range, 6.6–44.3 cm3), while the PET segmented GTV was 10.2 cm3 (range, 2.8–45.1 cm3). The median physician-defined GTV was 22.1 cm3 (range, 4.2–38.4 cm3). The median difference between the multichannel segmented and physician-defined GTVs was −10.7%, not showing a statistically significant difference (p-value = 0.43). However, the median difference between the PET segmented and physician-defined GTVs was −19.2%, showing a statistically significant difference (p-value =0.0037). The median Dice similarity coefficient between the multichannel segmented and physician-defined GTVs was 0.75 (range, 0.55–0.84), and the median sensitivity and positive predictive value between them were 0.76 and 0.81, respectively.Conclusions:
The authors developed an automated multimodality segmentation algorithm for tumor volume delineation and validated this algorithm for head and neck cancer radiotherapy. The multichannel segmented GTV agreed well with the physician-defined GTV. The authors expect that their algorithm will improve the accuracy and consistency in target definition for radiotherapy.
A quantification of the effectiveness of EPID dosimetry and software-based plan verification systems in detecting incidents in radiotherapy42(2015); http://dx.doi.org/10.1118/1.4928601View Description Hide DescriptionPurpose:
Complex treatments in radiation therapy require robust verification in order to prevent errors that can adversely affect the patient. For this purpose, the authors estimate the effectiveness of detecting errors with a “defense in depth” system composed of electronic portal imaging device (EPID) based dosimetry and a software-based system composed of rules-based and Bayesian network verifications.Methods:
The authors analyzed incidents with a high potential severity score, scored as a 3 or 4 on a 4 point scale, recorded in an in-house voluntary incident reporting system, collected from February 2012 to August 2014. The incidents were categorized into different failure modes. The detectability, defined as the number of incidents that are detectable divided total number of incidents, was calculated for each failure mode.Results:
In total, 343 incidents were used in this study. Of the incidents 67% were related to photon external beam therapy (EBRT). The majority of the EBRT incidents were related to patient positioning and only a small number of these could be detected by EPID dosimetry when performed prior to treatment (6%). A large fraction could be detected by in vivo dosimetry performed during the first fraction (74%). Rules-based and Bayesian network verifications were found to be complimentary to EPID dosimetry, able to detect errors related to patient prescriptions and documentation, and errors unrelated to photon EBRT. Combining all of the verification steps together, 91% of all EBRT incidents could be detected.Conclusions:
This study shows that the defense in depth system is potentially able to detect a large majority of incidents. The most effective EPID-based dosimetry verification is in vivo measurements during the first fraction and is complemented by rules-based and Bayesian network plan checking.
42(2015); http://dx.doi.org/10.1118/1.4928141View Description Hide DescriptionPurpose:
Respiratory margins for partial breast irradiation (PBI) have been largely based on geometric observations, which may overestimate the margin required for dosimetric coverage. In this study, dosimetric population-based respiratory margins and margin formulas for external beam partial breast irradiation are determined.Methods:
Volunteer respiratory data and anterior–posterior (AP) dose profiles from clinical treatment plans of 28 3D conformal radiotherapy (3DCRT) PBI patient plans were used to determine population-based respiratory margins. The peak-to-peak amplitudes (A) of realistic respiratory motion data from healthy volunteers were scaled from A = 1 to 10 mm to create respiratory motion probability density functions. Dose profiles were convolved with the respiratory probability density functions to produce blurred dose profiles accounting for respiratory motion. The required margins were found by measuring the distance between the simulated treatment and original dose profiles at the 95% isodose level.Results:
The symmetric dosimetric respiratory margins to cover 90%, 95%, and 100% of the simulated treatment population were 1.5, 2, and 4 mm, respectively. With patient set up at end exhale, the required margins were larger in the anterior direction than the posterior. For respiratory amplitudes less than 5 mm, the population-based margins can be expressed as a fraction of the extent of respiratory motion. The derived formulas in the anterior/posterior directions for 90%, 95%, and 100% simulated population coverage were 0.45A/0.25A, 0.50A/0.30A, and 0.70A/0.40A. The differences in formulas for different population coverage criteria demonstrate that respiratory trace shape and baseline drift characteristics affect individual respiratory margins even for the same average peak-to-peak amplitude.Conclusions:
A methodology for determining population-based respiratory margins using real respiratory motion patterns and dose profiles in the AP direction was described. It was found that the currently used respiratory margin of 5 mm in partial breast irradiation may be overly conservative for many 3DCRT PBI patients. Amplitude alone was found to be insufficient to determine patient-specific margins: individual respiratory trace shape and baseline drift both contributed to the dosimetric target coverage. With respiratory coaching, individualized respiratory margins smaller than the full extent of motion could reduce planning target volumes while ensuring adequate coverage under respiratory motion.
Coverage-based treatment planning to accommodate delineation uncertainties in prostate cancer treatment42(2015); http://dx.doi.org/10.1118/1.4928490View Description Hide DescriptionPurpose:
To compare two coverage-based planning (CP) techniques with fixed margin-based (FM) planning for high-risk prostate cancer treatments, with the exclusive consideration of the dosimetric impact of delineation uncertainties of target structures and normal tissues.Methods:
In this work, 19-patient data sets were involved. To estimate structure dose for each delineated contour under the influence of interobserver contour variability and CT image quality limitations, 1000 alternative structures were simulated by an average-surface-of-standard-deviation model, which utilized the patient-specific information of delineated structure and CT image contrast. An IMRT plan with zero planning-target-volume (PTV) margin on the delineated prostate and seminal vesicles [clinical-target-volume (CTVprostate) and CTVSV] was created and dose degradation due to contour variability was quantified by the dosimetric consequences of 1000 alternative structures. When D 98 failed to achieve a 95% coverage probability objective D 98,95 ≥ 78 Gy (CTVprostate) or D 98,95 ≥ 66 Gy (CTVSV), replanning was performed using three planning techniques: (1) FM (PTVprostate margin = 4,5,6 mm and PTVSV margin = 4,5,7 mm for RL, PA, and SI directions, respectively), (2) CPOM which optimized uniform PTV margins for CTVprostate and CTVSV to meet the D 98,95 objectives, and (3) CPCOP which directly optimized coverage-based objectives for all the structures. These plans were intercompared by computing percentile dose-volume histograms and tumor-control probability/normal tissue complication probability (TCP/NTCP) distributions.Results:
Inherent contour variability resulted in unacceptable CTV coverage for the zero-PTV-margin plans for all patients. For plans designed to accommodate contour variability, 18/19 CP plans were most favored by achieving desirable D 98,95 and TCP/NTCP values. The average improvement of probability of complication free control was 9.3% for CPCOP plans and 3.4% for CPOM plans.Conclusions:
When the delineation uncertainties need to be considered for prostate patients, CP techniques can produce more desirable plans than FM plans for most patients. The relative advantages between CPCOP and CPOM techniques are patient specific.
42(2015); http://dx.doi.org/10.1118/1.4928600View Description Hide DescriptionPurpose:
Magnetic fields are known to alter radiation dose deposition. Before patients receive treatment using an MRI-linear accelerator (MRI-Linac), preclinical studies are needed to understand the biological consequences of magnetic-field-induced dose effects. In the present study, the authors sought to identify a beam energy and magnetic field strength combination suitable for preclinical murine experiments.Methods:
Magnetic field dose effects were simulated in a mouse lung phantom using various beam energies (225 kVp, 350 kVp, 662 keV [Cs-137], 2 MV, and 1.25 MeV [Co-60]) and magnetic field strengths (0.75, 1.5, and 3 T). The resulting dose distributions were compared with those in a simulated human lung phantom irradiated with a 6 or 8 MV beam and orthogonal 1.5 T magnetic field.Results:
In the human lung phantom, the authors observed a dose increase of 45% and 54% at the soft-tissue-to-lung interface and a dose decrease of 41% and 48% at the lung-to-soft-tissue interface for the 6 and 8 MV beams, respectively. In the mouse simulations, the magnetic fields had no measurable effect on the 225 or 350 kVp dose distribution. The dose increases with the Cs-137 beam for the 0.75, 1.5, and 3 T magnetic fields were 9%, 29%, and 42%, respectively. The dose decreases were 9%, 21%, and 37%. For the 2 MV beam, the dose increases were 16%, 33%, and 31% and the dose decreases were 9%, 19%, and 30%. For the Co-60 beam, the dose increases were 19%, 54%, and 44%, and the dose decreases were 19%, 42%, and 40%.Conclusions:
The magnetic field dose effects in the mouse phantom using a Cs-137, 3 T combination or a Co-60, 1.5 or 3 T combination most closely resemble those in simulated human treatments with a 6 MV, 1.5 T MRI-Linac. The effects with a Co-60, 1.5 T combination most closely resemble those in simulated human treatments with an 8 MV, 1.5 T MRI-Linac.
- RADIATION IMAGING PHYSICS
42(2015); http://dx.doi.org/10.1118/1.4927375View Description Hide DescriptionPurpose:
The authors aimed to develop and validate an automated algorithm for epicardial fat volume (EFV) quantification from noncontrast CT.Methods:
The authors developed a hybrid algorithm based on initial segmentation with a multiple-patient CT atlas, followed by automated pericardium delineation using geodesic active contours. A coregistered segmented CT atlas was created from manually segmented CT data and stored offline. The heart and pericardium in test CT data are first initialized by image registration to the CT atlas. The pericardium is then detected by a knowledge-based algorithm, which extracts only the membrane representing the pericardium. From its initial atlas position, the pericardium is modeled by geodesic active contours, which iteratively deform and lock onto the detected pericardium. EFV is automatically computed using standard fat attenuation range.Results:
The authors applied their algorithm on 50 patients undergoing routine coronary calcium assessment by CT. Measurement time was 60 s per-patient. EFV quantified by the algorithm (83.60 ± 32.89 cm3) and expert readers (81.85 ± 34.28 cm3) showed excellent correlation (r = 0.97, p < 0.0001), with no significant differences by comparison of individual data points (p = 0.15). Voxel overlap by Dice coefficient between the algorithm and expert readers was 0.92 (range 0.88–0.95). The mean surface distance and Hausdorff distance in millimeter between manually drawn contours and the automatically obtained contours were 0.6 ± 0.9 mm and 3.9 ± 1.7 mm, respectively. Mean difference between the algorithm and experts was 9.7% ± 7.4%, similar to interobserver variability between 2 readers (8.0% ± 5.3%, p = 0.3).Conclusions:
The authors’ novel automated method based on atlas-initialized active contours accurately and rapidly quantifies EFV from noncontrast CT.
42(2015); http://dx.doi.org/10.1118/1.4927573View Description Hide DescriptionPurpose:
The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules.Methods:
The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithms were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule.Results:
The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%.Conclusions:
The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.
42(2015); http://dx.doi.org/10.1118/1.4927787View Description Hide DescriptionPurpose:
Dual-energy (DE) imaging is a method that suppresses bony anatomy on planar kV images while enhancing soft tissue contrast. This technique has been used specifically in the chest to improve the visualization of small lung tumors. However, DE imaging may also provide quantitative information that has not been previously investigated. In this study, the aim was to establish a theoretical relationship between DE image contrast and tumor thickness and to observe this trend in phantom experiments.Methods:
A phantom consisting cork (used to simulate lung), tissue-equivalent material, and pork ribs was constructed to test for a relationship between DE image contrast and simulated tumor thickness. Fifteen phantom setups were used with various thicknesses of cork and tissue-equivalent material. For each setup, high (120 kVp) and low (60 kVp) energy planar images were acquired and DE images were produced. The image contrast between the simulated tumor and surrounding tissue was then plotted against the known thicknesses and a linear regression was performed.Results:
A linear regression of the contrast data vs simulated tumor thickness resulted in a slope of −0.0454 with an R 2 = 0.9904. The expected uncertainty in the thickness measurements using the regression parameters and DE contrast standard deviation was 0.13 cm.Conclusions:
Phantom data exhibited a linear relationship between DE image contrast and simulated tumor thickness. Future studies will investigate patient-specific parameters so that this method can be used clinically to evaluate tumor thickness from planar kV images. Such an approach may have benefits for both adaptive and heavy ion therapies.
42(2015); http://dx.doi.org/10.1118/1.4927792View Description Hide DescriptionPurpose:
A procedure to obtain the MTF of an image system from a star bar pattern image is presented. The results obtained are compared to the standard analysis of an edge image (as described in the norm IEC 62220-1).Methods:
The images used are artificially generated following a procedure that simulates sampling, blurring, and noise present in a real phantom image. The MTF from a star bar pattern is obtained from the analysis of circular scans over the star pattern image and concentric to it. The radius of the scanning circumference is proportional to the spatial frequency of the curve arising from the scan, and the amplitude of this curve is directly related to the system MTF for that frequency. An oversampling procedure is also followed to minimize the effect of noise in the image. In order to investigate the MTF in a particular direction, the image analysis is restricted to an angular sector centered around that direction.Results:
The MTFs calculated following this procedure show a very good agreement with those obtained following the standard IEC 62220-1 for low noise levels. As the noise increases, however, the star bar method is more accurate than the edge method.Conclusions:
The procedure presented provides a good method to investigate the MTF in any spatial direction. Finally, as the whole star bar pattern image is used for MTF computation, the high signal to noise ratio guarantees a good immunity against noise.
42(2015); http://dx.doi.org/10.1118/1.4927786View Description Hide DescriptionPurpose:
Electronic portal imagers (EPIDs) with high detective quantum efficiencies (DQEs) are sought to facilitate the use of the megavoltage (MV) radiotherapy treatment beam for image guidance. Potential advantages include high quality (treatment) beam’s eye view imaging, and improved cone-beam computed tomography (CBCT) generating images with more accurate electron density maps with immunity to metal artifacts. One approach to increasing detector sensitivity is to couple a thick pixelated scintillator array to an active matrix flat panel imager (AMFPI) incorporating amorphous silicon thin film electronics. Cadmium tungstate (CWO) has many desirable scintillation properties including good light output, a high index of refraction, high optical transparency, and reasonable cost. However, due to the cleave plane inherent in its crystalline structure, the difficulty of cutting and polishing CWO has, in part, limited its study relative to other scintillators such as cesium iodide and bismuth germanate (BGO). The goal of this work was to build and test a focused large-area pixelated “strip” CWO detector.Methods:
A 361 × 52 mm scintillator assembly that contained a total of 28 072 pixels was constructed. The assembly comprised seven subarrays, each 15 mm thick. Six of the subarrays were fabricated from CWO with a pixel pitch of 0.784 mm, while one array was constructed from BGO for comparison. Focusing was achieved by coupling the arrays to the Varian AS1000 AMFPI through a piecewise linear arc-shaped fiber optic plate. Simulation and experimental studies of modulation transfer function (MTF) and DQE were undertaken using a 6 MV beam, and comparisons were made between the performance of the pixelated strip assembly and the most common EPID configuration comprising a 1 mm-thick copper build-up plate attached to a 133 mg/cm2 gadolinium oxysulfide scintillator screen (Cu-GOS). Projection radiographs and CBCT images of phantoms were acquired. The work also introduces the use of a lightweight edge phantom to generate MTF measurements at MV energies and shows its functional equivalence to the more cumbersome slit-based method.Results:
Measured and simulated DQE(0)’s of the pixelated CWO detector were 22% and 26%, respectively. The average measured and simulated ratios of CWO DQE(f) to Cu-GOS DQE(f) across the frequency range of 0.0–0.62 mm−1 were 23 and 29, respectively. 2D and 3D imaging studies confirmed the large dose efficiency improvement and that focus was maintained across the field of view. In the CWO CBCT images, the measured spatial resolution was 7 lp/cm. The contrast-to-noise ratio was dramatically improved reflecting a 22 × sensitivity increase relative to Cu-GOS. The CWO scintillator material showed significantly higher stability and light yield than the BGO material.Conclusions:
An efficient piecewise-focused pixelated strip scintillator for MV imaging is described that offers more than a 20-fold dose efficiency improvement over Cu-GOS.
Low tube voltage dual source computed tomography to reduce contrast media doses in adult abdomen examinations: A phantom study42(2015); http://dx.doi.org/10.1118/1.4927791View Description Hide DescriptionPurpose:
To evaluate the potential of low tube voltage dual source (DS) single energy (SE) and dual energy (DE) computed tomography (CT) to reduce contrast media (CM) dose in adult abdominal examinations of various sizes while maintaining soft tissue and iodine contrast-to-noise ratio (CNR).Methods:
Four abdominal phantoms simulating a body mass index of 16 to 35 kg/m2 with four inserted syringes of 0, 2, 4, and 8 mgI/ml CM were scanned using a 64-slice DS-CT scanner. Six imaging protocols were used; one single source (SS) reference protocol (120 kV, 180 reference mAs), four low kV SE protocols (70 and 80 kV using both SS and DS), and one DE protocol at 80/140 kV. Potential CM reduction with unchanged CNRs relative to the 120 kV protocol was calculated along with the corresponding increase in radiation dose.Results:
The potential contrast media reductions were determined to be approximately 53% for DS 70 kV, 51% for SS 70 kV, 44% for DS 80 kV, 40% for SS 80 kV, and 20% for DE (all differences were significant, P < 0.05). Constant CNR could be achieved by using DS 70 kV for small to medium phantom sizes (16–26 kg/m2) and for all sizes (16–35 kg/m2) when using DS 80 kV and DE. Corresponding radiation doses increased by 60%–107%, 23%–83%, and 6%–12%, respectively.Conclusions:
DS single energy CT can be used to reduce CM dose by 44%–53% with maintained CNR in adult abdominal examinations at the cost of an increased radiation dose. DS dual-energy CT allows reduction of CM dose by 20% at similar radiation dose as compared to a standard 120 kV single source.
Statistical model based iterative reconstruction in clinical CT systems. Part III. Task-based kV/mAs optimization for radiation dose reduction42(2015); http://dx.doi.org/10.1118/1.4927722View Description Hide DescriptionPurpose:
For a given imaging task and patient size, the optimal selection of x-ray tube potential (kV) and tube current-rotation time product (mAs) is pivotal in achieving the maximal radiation dose reduction while maintaining the needed diagnostic performance. Although contrast-to-noise (CNR)-based strategies can be used to optimize kV/mAs for computed tomography (CT) imaging systems employing the linear filtered backprojection (FBP) reconstruction method, a more general framework needs to be developed for systems using the nonlinear statistical model-based iterative reconstruction (MBIR) method. The purpose of this paper is to present such a unified framework for the optimization of kV/mAs selection for both FBP- and MBIR-based CT systems.Methods:
The optimal selection of kV and mAs was formulated as a constrained optimization problem to minimize the objective function, Dose(kV,mAs), under the constraint that the achievable detectability index d′(kV,mAs) is not lower than the prescribed value of for a given imaging task. Since it is difficult to analytically model the dependence of d′ on kV and mAs for the highly nonlinear MBIR method, this constrained optimization problem is solved with comprehensive measurements of Dose(kV,mAs) and d′(kV,mAs) at a variety of kV–mAs combinations, after which the overlay of the dose contours and d′ contours is used to graphically determine the optimal kV–mAs combination to achieve the lowest dose while maintaining the needed detectability for the given imaging task. As an example, d′ for a 17 mm hypoattenuating liver lesion detection task was experimentally measured with an anthropomorphic abdominal phantom at four tube potentials (80, 100, 120, and 140 kV) and fifteen mA levels (25 and 50–700) with a sampling interval of 50 mA at a fixed rotation time of 0.5 s, which corresponded to a dose (CTDI vol) range of [0.6, 70] mGy. Using the proposed method, the optimal kV and mA that minimized dose for the prescribed detectability level of were determined. As another example, the optimal kV and mA for an 8 mm hyperattenuating liver lesion detection task were also measured using the developed framework. Both an in vivo animal and human subject study were used as demonstrations of how the developed framework can be applied to the clinical work flow.Results:
For the first task, the optimal kV and mAs were measured to be 100 and 500, respectively, for FBP, which corresponded to a dose level of 24 mGy. In comparison, the optimal kV and mAs for MBIR were 80 and 150, respectively, which corresponded to a dose level of 4 mGy. The topographies of the iso-d′ map and the iso-CNR map were the same for FBP; thus, the use of d′- and CNR-based optimization methods generated the same results for FBP. However, the topographies of the iso-d′ and iso-CNR map were significantly different in MBIR; the CNR-based method overestimated the performance of MBIR, predicting an overly aggressive dose reduction factor. For the second task, the developed framework generated the following optimization results: for FBP, kV = 140, mA = 350, dose = 37.5 mGy; for MBIR, kV = 120, mA = 250, dose = 18.8 mGy. Again, the CNR-based method overestimated the performance of MBIR. Results of the preliminary in vivo studies were consistent with those of the phantom experiments.Conclusions:
A unified and task-driven kV/mAs optimization framework has been developed in this work. The framework is applicable to both linear and nonlinear CT systems such as those using the MBIR method. As expected, the developed framework can be reduced to the conventional CNR-based kV/mAs optimization frameworks if the system is linear. For MBIR-based nonlinear CT systems, however, the developed task-based kV/mAs optimization framework is needed to achieve the maximal dose reduction while maintaining the desired diagnostic performance.
Compressed-sensing-based content-driven hierarchical reconstruction: Theory and application to C-arm cone-beam tomography42(2015); http://dx.doi.org/10.1118/1.4928144View Description Hide DescriptionPurpose:
This paper addresses the reconstruction of x-ray cone-beam computed tomography (CBCT) for interventional C-arm systems. Subsampling of CBCT is a significant issue with C-arms due to their slow rotation and to the low frame rate of their flat panel x-ray detectors. The aim of this work is to propose a novel method able to handle the subsampling artifacts generally observed with analytical reconstruction, through a content-driven hierarchical reconstruction based on compressed sensing.Methods:
The central idea is to proceed with a hierarchical method where the most salient features (high intensities or gradients) are reconstructed first to reduce the artifacts these features induce. These artifacts are addressed first because their presence contaminates less salient features. Several hierarchical schemes aiming at streak artifacts reduction are introduced for C-arm CBCT: the empirical orthogonal matching pursuit approach with the ℓ0 pseudonorm for reconstructing sparse vessels; a convex variant using homotopy with the ℓ1-norm constraint of compressed sensing, for reconstructing sparse vessels over a nonsparse background; homotopy with total variation (TV); and a novel empirical extension to nonlinear diffusion (NLD). Such principles are implemented with penalized iterative filtered backprojection algorithms. For soft-tissue imaging, the authors compare the use of TV and NLD filters as sparsity constraints, both optimized with the alternating direction method of multipliers, using a threshold for TV and a nonlinear weighting for NLD.Results:
The authors show on simulated data that their approach provides fast convergence to good approximations of the solution of the TV-constrained minimization problem introduced by the compressed sensing theory. Using C-arm CBCT clinical data, the authors show that both TV and NLD can deliver improved image quality by reducing streaks.Conclusions:
A flexible compressed-sensing-based algorithmic approach is proposed that is able to accommodate for a wide range of constraints. It is successfully applied to C-arm CBCT images that may not be so well approximated by piecewise constant functions.
42(2015); http://dx.doi.org/10.1118/1.4928214View Description Hide DescriptionPurpose:
Digital tomosynthesis (DTS) has been shown to be useful for reducing the overlapping of abnormalities with anatomical structures at various depth levels along the posterior–anterior (PA) direction in chest radiography. However, DTS provides crude three-dimensional (3D) images that have poor resolution in the lateral view and can only be displayed with reasonable quality in the PA view. Furthermore, the spillover of high-contrast objects from off-fulcrum planes generates artifacts that may impede the diagnostic use of the DTS images. In this paper, the authors describe and demonstrate the use of a dual-view DTS technique to improve the accuracy of the reconstructed volume image data for more accurate rendition of the anatomy and slice images with improved resolution and reduced artifacts, thus allowing the 3D image data to be viewed in views other than the PA view.Methods:
With the dual-view DTS technique, limited angle scans are performed and projection images are acquired in two orthogonal views: PA and lateral. The dual-view projection data are used together to reconstruct 3D images using the maximum likelihood expectation maximization iterative algorithm. In this study, projection images were simulated or experimentally acquired over 360° using the scanning geometry for cone beam computed tomography (CBCT). While all projections were used to reconstruct CBCT images, selected projections were extracted and used to reconstruct single- and dual-view DTS images for comparison with the CBCT images. For realistic demonstration and comparison, a digital chest phantom derived from clinical CT images was used for the simulation study. An anthropomorphic chest phantom was imaged for the experimental study. The resultant dual-view DTS images were visually compared with the single-view DTS images and CBCT images for the presence of image artifacts and accuracy of CT numbers and anatomy and quantitatively compared with root-mean-square-deviation (RMSD) values computed using the digital chest phantom or the CBCT images as the reference in the simulation and experimental study, respectively. High-contrast wires with vertical, oblique, and horizontal orientations in a PA view plane were also imaged to investigate the spatial resolutions and how the wire signals spread in the PA view and lateral view slice images.Results:
Both the digital phantom images (simulated) and the anthropomorphic phantom images (experimentally generated) demonstrated that the dual-view DTS technique resulted in improved spatial resolution in the depth (PA) direction, more accurate representation of the anatomy, and significantly reduced artifacts. The RMSD values corroborate well with visual observations with substantially lower RMSD values measured for the dual-view DTS images as compared to those measured for the single-view DTS images. The imaging experiment with the high-contrast wires shows that while the vertical and oblique wires could be resolved in the lateral view in both single- and dual-view DTS images, the horizontal wire could only be resolved in the dual-view DTS images. This indicates that with single-view DTS, the wire signals spread liberally to off-fulcrum planes and generated wire shadow there.Conclusions:
The authors have demonstrated both visually and quantitatively that the dual-view DTS technique can be used to achieve more accurate rendition of the anatomy and to obtain slice images with improved resolution and reduced artifacts as compared to the single-view DTS technique, thus allowing the 3D image data to be viewed in views other than the PA view. These advantages could make the dual-view DTS technique useful in situations where better separation of the objects-of-interest from the off-fulcrum structures or more accurate 3D rendition of the anatomy are required while a regular CT examination is undesirable due to radiation dose considerations.