Multi-GPU Acceleration of Branchless Distance Driven Projection and Backprojection for Clinical Helical CT.

Model-based image reconstruction (MBIR) techniques have the potential to generate high quality images from noisy measurements and a small number of projections which can reduce the x-ray dose in patients. These MBIR techniques rely on projection and backprojection to refine an image estimate. One of the widely used projectors for these modern MBIR based technique is called branchless distance driven (DD) projection and backprojection. While this method produces superior quality images, the computational cost of iterative updates keeps it from being ubiquitous in clinical applications. In this paper, we provide several new parallelization ideas for concurrent execution of the DD projectors in multi-GPU systems using CUDA programming tools. We have introduced some novel schemes for dividing the projection data and image voxels over multiple GPUs to avoid runtime overhead and inter-device synchronization issues. We have also reduced the complexity of overlap calculation of the algorithm by eliminating the common projection plane and directly projecting the detector boundaries onto image voxel boundaries. To reduce the time required for calculating the overlap between the detector edges and image voxel boundaries, we have proposed a pre-accumulation technique to accumulate image intensities in perpendicular 2D image slabs (from a 3D image) before projection and after backprojection to ensure our DD kernels run faster in parallel GPU threads. For the implementation of our iterative MBIR technique we use a parallel multi-GPU version of the alternating minimization (AM) algorithm with penalized likelihood update. The time performance using our proposed reconstruction method with Siemens Sensation 16 patient scan data shows an average of 24 times speedup using a single TITAN X GPU and 74 times speedup using 3 TITAN X GPUs in parallel for combined projection and backprojection.

MB-DECTNet: a model-based unrolling network for accurate 3D dual-energy CT reconstruction from clinically acquired helical scans.

Objective.Over the past several decades, dual-energy CT (DECT) imaging has seen significant advancements due to its ability to distinguish between materials. DECT statistical iterative reconstruction (SIR) has exhibited potential for noise reduction and enhanced accuracy. However, its slow convergence and substantial computational demands render the elapsed time for 3D DECT SIR often clinically unacceptable. The objective of this study is to accelerate 3D DECT SIR while maintaining subpercentage or near-subpercentage accuracy.Approach.We incorporate DECT SIR into a deep-learning model-based unrolling network for 3D DECT reconstruction (MB-DECTNet), which can be trained end-to-end. This deep learning-based approach is designed to learn shortcuts between initial conditions and the stationary points of iterative algorithms while preserving the unbiased estimation property of model-based algorithms. MB-DECTNet comprises multiple stacked update blocks, each containing a data consistency layer (DC) and a spatial mixer layer, with the DC layer functioning as a one-step update from any traditional iterative algorithm.Main results.The quantitative results indicate that our proposed MB-DECTNet surpasses both the traditional image-domain technique (MB-DECTNet reduces average bias by a factor of 10) and a pure deep learning method (MB-DECTNet reduces average bias by a factor of 8.8), offering the potential for accurate attenuation coefficient estimation, akin to traditional statistical algorithms, but with considerably reduced computational costs. This approach achieves 0.13% bias and 1.92% mean absolute error and reconstructs a full image of a head in less than 12 min. Additionally, we show that the MB-DECTNet output can serve as an initializer for DECT SIR, leading to further improvements in results.Significance.This study presents a model-based deep unrolling network for accurate 3D DECT reconstruction, achieving subpercentage error in estimating virtual monoenergetic images for a full head at 60 and 150 keV in 30 min, representing a 40-fold speedup compared to traditional approaches. These findings have significant implications for accelerating DECT SIR and making it more clinically feasible.

Motion-compensated scheme for sequential scanned statistical iterative dual-energy CT reconstruction.

Objective.Dual-energy computed tomography (DECT) has been widely used to reconstruct numerous types of images due its ability to better discriminate tissue properties. Sequential scanning is a popular dual-energy data acquisition method as it requires no specialized hardware. However, patient motion between two sequential scans may lead to severe motion artifacts in DECT statistical iterative reconstructions (SIR) images. The objective is to reduce the motion artifacts in such reconstructions.Approach.We propose a motion-compensation scheme that incorporates a deformation vector field into any DECT SIR. The deformation vector field is estimated via the multi-modality symmetric deformable registration method. The precalculated registration mapping and its inverse or adjoint are then embedded into each iteration of the iterative DECT algorithm.Main results.Results from a simulated and clinical case show that the proposed framework is capable of reducing motion artifacts in DECT SIRs. Percentage mean square errors in regions of interest in the simulated and clinical cases were reduced from 4.6% to 0.5% and 6.8% to 0.8%, respectively. A perturbation analysis was then performed to determine errors in approximating the continuous deformation by using the deformation field and interpolation. Our findings show that errors in our method are mostly propagated through the target image and amplified by the inverse matrix of the combination of the Fisher information and Hessian of the penalty term.Significance.We have proposed a novel motion-compensation scheme to incorporate a 3D registration method into the joint statistical iterative DECT algorithm in order to reduce motion artifacts caused by inter-scan motion, and successfully demonstrate that interscan motion corrections can be integrated into the DECT SIR process, enabling accurate imaging of radiological quantities on conventional SECT scanners, without significant loss of either computational efficiency or accuracy.

Impact of flat panel-imager veiling glare on scatter-estimation accuracy and image quality of a commercial on-board cone-beam CT imaging system.

PURPOSE: The purposes of this study is to measure the low frequency drop (LFD) of the modulation transfer function (MTF), associated with the long tails of the detector point spread function (PSF) of an on-board flat panel imager and study its impact on cone-beam CT (CBCT) image quality and scatter measurement accuracy. METHODS: Two different experimental methods were used to characterize LFD and its associated PSF of a Varian OBI flat-panel detector system: the edge response function (ERF) method and the disk transfer function (DTF) method. PSF was estimated by fitting parametric models to these measurements for four values of the applied voltage (kVp). The resultant PSF was used to demonstrate the effect of LFD on image contrast and CT number accuracy in CBCT images reconstructed from synthetic datasets, as well as, accuracy of scatter measurements with the beam-stop method. RESULTS: The MTFs derived from the measured ERF data revealed LFDs varying from 8% (at 60 kVp) to 10.5% (at 120 kVp), while the intensity of the long PSF tails was found to increase with increasing kVp. The veiling glare line spread functions derived from the ERF and DTF methods were in excellent agreement. Uncorrected veiling glare reduced contrast and the image intensity in CBCT reconstruction, near the phantom periphery (by 67 Hounsfield units in a 20 cm-in-diameter water phantom) and (to a smaller degree) near inhomogeneities. Use of the bow-tie filter mitigated these effects. Veiling glare also resulted in about 10%-15% overestimation of the scatter-to-primary ratio when measured with the beam-stop or beam-stop array method. CONCLUSIONS: The long tails of the detector PSF were found to have a modest dependence of beam spectrum, which is reflected on the MTF curve LFD. Our findings show that uncorrected veiling glare can affect quantitative accuracy and contrast in CBCT imaging, based on flat panel imager. In addition, it results in overestimation of the scatter-to-primary ratio, measured with the beam-stop methods.

Fast patient-specific Monte Carlo brachytherapy dose calculations via the correlated sampling variance reduction technique.

PURPOSE: To demonstrate potential of correlated sampling Monte Carlo (CMC) simulation to improve the calculation efficiency for permanent seed brachytherapy (PSB) implants without loss of accuracy. METHODS: CMC was implemented within an in-house MC code family (PTRAN) and used to compute 3D dose distributions for two patient cases: a clinical PSB postimplant prostate CT imaging study and a simulated post lumpectomy breast PSB implant planned on a screening dedicated breast cone-beam CT patient exam. CMC tallies the dose difference, ΔD, between highly correlated histories in homogeneous and heterogeneous geometries. The heterogeneous geometry histories were derived from photon collisions sampled in a geometrically identical but purely homogeneous medium geometry, by altering their particle weights to correct for bias. The prostate case consisted of 78 Model-6711 (125)I seeds. The breast case consisted of 87 Model-200 (103)Pd seeds embedded around a simulated lumpectomy cavity. Systematic and random errors in CMC were unfolded using low-uncertainty uncorrelated MC (UMC) as the benchmark. CMC efficiency gains, relative to UMC, were computed for all voxels, and the mean was classified in regions that received minimum doses greater than 20%, 50%, and 90% of D(90), as well as for various anatomical regions. RESULTS: Systematic errors in CMC relative to UMC were less than 0.6% for 99% of the voxels and 0.04% for 100% of the voxels for the prostate and breast cases, respectively. For a 1 × 1 × 1 mm(3) dose grid, efficiency gains were realized in all structures with 38.1- and 59.8-fold average gains within the prostate and breast clinical target volumes (CTVs), respectively. Greater than 99% of the voxels within the prostate and breast CTVs experienced an efficiency gain. Additionally, it was shown that efficiency losses were confined to low dose regions while the largest gains were located where little difference exists between the homogeneous and heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 × 1 × 1 mm(3)) and breast (0.67 × 0.67 × 0.8 mm(3)) CTVs, respectively. CONCLUSIONS: CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.

Dose calculation for photon-emitting brachytherapy sources with average energy higher than 50 keV: report of the AAPM and ESTRO.

PURPOSE: Recommendations of the American Association of Physicists in Medicine (AAPM) and the European Society for Radiotherapy and Oncology (ESTRO) on dose calculations for high-energy (average energy higher than 50 keV) photon-emitting brachytherapy sources are presented, including the physical characteristics of specific (192)Ir, (137)Cs, and (60)Co source models. METHODS: This report has been prepared by the High Energy Brachytherapy Source Dosimetry (HEBD) Working Group. This report includes considerations in the application of the TG-43U1 formalism to high-energy photon-emitting sources with particular attention to phantom size effects, interpolation accuracy dependence on dose calculation grid size, and dosimetry parameter dependence on source active length. RESULTS: Consensus datasets for commercially available high-energy photon sources are provided, along with recommended methods for evaluating these datasets. Recommendations on dosimetry characterization methods, mainly using experimental procedures and Monte Carlo, are established and discussed. Also included are methodological recommendations on detector choice, detector energy response characterization and phantom materials, and measurement specification methodology. Uncertainty analyses are discussed and recommendations for high-energy sources without consensus datasets are given. CONCLUSIONS: Recommended consensus datasets for high-energy sources have been derived for sources that were commercially available as of January 2010. Data are presented according to the AAPM TG-43U1 formalism, with modified interpolation and extrapolation techniques of the AAPM TG-43U1S1 report for the 2D anisotropy function and radial dose function.

Report of the Task Group 186 on model-based dose calculation methods in brachytherapy beyond the TG-43 formalism: current status and recommendations for clinical implementation.

The charge of Task Group 186 (TG-186) is to provide guidance for early adopters of model-based dose calculation algorithms (MBDCAs) for brachytherapy (BT) dose calculations to ensure practice uniformity. Contrary to external beam radiotherapy, heterogeneity correction algorithms have only recently been made available to the BT community. Yet, BT dose calculation accuracy is highly dependent on scatter conditions and photoelectric effect cross-sections relative to water. In specific situations, differences between the current water-based BT dose calculation formalism (TG-43) and MBDCAs can lead to differences in calculated doses exceeding a factor of 10. MBDCAs raise three major issues that are not addressed by current guidance documents: (1) MBDCA calculated doses are sensitive to the dose specification medium, resulting in energy-dependent differences between dose calculated to water in a homogeneous water geometry (TG-43), dose calculated to the local medium in the heterogeneous medium, and the intermediate scenario of dose calculated to a small volume of water in the heterogeneous medium. (2) MBDCA doses are sensitive to voxel-by-voxel interaction cross sections. Neither conventional single-energy CT nor ICRU∕ICRP tissue composition compilations provide useful guidance for the task of assigning interaction cross sections to each voxel. (3) Since each patient-source-applicator combination is unique, having reference data for each possible combination to benchmark MBDCAs is an impractical strategy. Hence, a new commissioning process is required. TG-186 addresses in detail the above issues through the literature review and provides explicit recommendations based on the current state of knowledge. TG-43-based dose prescription and dose calculation remain in effect, with MBDCA dose reporting performed in parallel when available. In using MBDCAs, it is recommended that the radiation transport should be performed in the heterogeneous medium and, at minimum, the dose to the local medium be reported along with the TG-43 calculated doses. Assignments of voxel-by-voxel cross sections represent a particular challenge. Electron density information is readily extracted from CT imaging, but cannot be used to distinguish between different materials having the same density. Therefore, a recommendation is made to use a number of standardized materials to maintain uniformity across institutions. Sensitivity analysis shows that this recommendation offers increased accuracy over TG-43. MBDCA commissioning will share commonalities with current TG-43-based systems, but in addition there will be algorithm-specific tasks. Two levels of commissioning are recommended: reproducing TG-43 dose parameters and testing the advanced capabilities of MBDCAs. For validation of heterogeneity and scatter conditions, MBDCAs should mimic the 3D dose distributions from reference virtual geometries. Potential changes in BT dose prescriptions and MBDCA limitations are discussed. When data required for full MBDCA implementation are insufficient, interim recommendations are made and potential areas of research are identified. Application of TG-186 guidance should retain practice uniformity in transitioning from the TG-43 to the MBDCA approach.

Towards subpercentage uncertainty proton stopping-power mapping via dual-energy CT: Direct experimental validation and uncertainty analysis of a statistical iterative image reconstruction method.

PURPOSE: To assess the potential of a joint dual-energy computerized tomography (CT) reconstruction process (statistical image reconstruction method built on a basis vector model (JSIR-BVM)) implemented on a 16-slice commercial CT scanner to measure high spatial resolution stopping-power ratio (SPR) maps with uncertainties of less than 1%. METHODS: JSIR-BVM was used to reconstruct images of effective electron density and mean excitation energy from dual-energy CT (DECT) sinograms for 10 high-purity samples of known density and atomic composition inserted into head and body phantoms. The measured DECT data consisted of 90 and 140 kVp axial sinograms serially acquired on a Philips Brilliance Big Bore CT scanner without beam-hardening corrections. The corresponding SPRs were subsequently measured directly via ion chamber measurements on a MEVION S250 superconducting synchrocyclotron and evaluated theoretically from the known sample compositions and densities. Deviations of JSIR-BVM SPR values from their theoretically calculated and directly measured ground-truth values were evaluated for our JSIR-BVM method and our implementation of the Hünemohr-Saito (H-S) DECT image-domain decomposition technique for SPR imaging. A thorough uncertainty analysis was then performed for five different scenarios (comparison of JSIR-BVM stopping-power ratio/stopping power (SPR/SP) to International Commission on Radiation Measurements and Units benchmarks; comparison of JSIR-BVM SPR to measured benchmarks; and uncertainties in JSIR-BVM SPR/SP maps for patients of unknown composition) per the Joint Committee for Guides in Metrology and the Guide to Expression of Uncertainty in Measurement, including the impact of uncertainties in measured photon spectra, sample composition and density, photon cross section and I-value models, and random measurement uncertainty. Estimated SPR uncertainty for three main tissue groups in patients of unknown composition and the weighted proportion of each tissue type for three proton treatment sites were then used to derive a composite range uncertainty for our method. RESULTS: Mean JSIR-BVM SPR estimates deviated by less than 1% from their theoretical and directly measured ground-truth values for most inserts and phantom geometries except for high-density Delrin and Teflon samples with SPR error relative to proton measurements of 1.1% and -1.0% (head phantom) and 1.1% and -1.1% (body phantom). The overall root-mean-square (RMS) deviations over all samples were 0.39% and 0.52% (head phantom) and 0.43% and 0.57% (body phantom) relative to theoretical and directly measured ground-truth SPRs, respectively. The corresponding RMS (maximum) errors for the image-domain decomposition method were 2.68% and 2.73% (4.68% and 4.99%) for the head phantom and 0.71% and 0.87% (1.37% and 1.66%) for the body phantom. Compared to H-S SPR maps, JSIR-BVM yielded 30% sharper and twofold sharper images for soft tissues and bone-like surrogates, respectively, while reducing noise by factors of 6 and 3, respectively. The uncertainty (coverage factor k = 1) of the DECT-to-benchmark values comparison ranged from 0.5% to 1.5% and is dominated by scanning-beam photon-spectra uncertainties. An analysis of the SPR uncertainty for patients of unknown composition showed a JSIR-BVM uncertainty of 0.65%, 1.21%, and 0.77% for soft-, lung-, and bony-tissue groups which led to a composite range uncertainty of 0.6-0.9%. CONCLUSIONS: Observed JSIR-BVM SPR estimation errors were all less than 50% of the estimated k = 1 total uncertainty of our benchmarking experiment, demonstrating that JSIR-BVM high spatial resolution, low-noise SPR mapping is feasible and is robust to variations in the geometry of the scanned object. In contrast, the much larger H-S SPR estimation errors are dominated by imaging noise and residual beam-hardening artifacts. While the uncertainties characteristic of our current JSIR-BVM implementation can be as large as 1.5%, achieving < 1% total uncertainty is feasible by improving the accuracy of scanner-specific scatter-profile and photon-spectrum estimates. With its robustness to beam-hardening artifact, image noise, and variations in phantom size and geometry, JSIR-BVM has the potential to achieve high spatial-resolution SPR mapping with subpercentage accuracy and estimated uncertainty in the clinical setting.

Estimation of CT cone-beam geometry using a novel method insensitive to phantom fabrication inaccuracy: implications for isocenter localization accuracy.

PURPOSE: Mechanical instabilities that occur during gantry rotation of on-board cone-beam computed tomography (CBCT) imaging systems limit the efficacy of image-guided radiotherapy. Various methods for calibrating the CBCT geometry and correcting errors have been proposed, including some that utilize dedicated fiducial phantoms. The purpose of this work was to investigate the role of phantom fabrication imprecision on the accuracy of a particular CT cone-beam geometry estimate and to test a new method to mitigate errors in beam geometry arising from imperfectly fabricated phantoms. METHODS: The authors implemented a fiducial phantom-based beam geometry estimation following the one described by Cho et al. [Med Phys 32(4), 968-983 (2005)]. The algorithm utilizes as input projection images of the phantom at various gantry angles and provides a full nine parameter beam geometry characterization of the source and detector position and detector orientation versus gantry angle. A method was developed for recalculating the beam geometry in a coordinate system with origin at the source trajectory center and aligned with the axis of gantry rotation, thus making the beam geometry estimation independent of the placement of the phantom. A second CBCT scan with the phantom rotated 180 degrees about its long axis was averaged with the first scan to mitigate errors from phantom imprecision. Computer simulations were performed to assess the effect of 2D fiducial marker positional error on the projections due to image discretization, as well as 3D fiducial marker position error due to phantom fabrication imprecision. Experimental CBCT images of a fiducial phantom were obtained and the algorithm used to measure beam geometry for a Varian Trilogy with an on-board CBCT. RESULTS: Both simulations and experimental results reveal large sinusoidal oscillations in the calculated beam geometry parameters with gantry angle due to displacement of the phantom from CBCT isocenter and misalignment with the gantry axis, which are eliminated by recalculating the beam geometry in the source coordinate system. Simulations and experiments also reveal an additional source of oscillations arising from fiducial marker position error due to phantom fabrication imprecision that are mitigated by averaging the results with those of a second CBCT scan with phantom rotated. With a typical fiducial marker position error of 0.020 mm (0.001 in.), source and detector position are found in simulations to be within 250 microm of the true values, and detector and gantry angles less than 0.2 degrees. Detector offsets are within 100 microm of the known value. Experimental results verify the efficacy of the second scan in mitigating beam geometry errors, as well as large apparent source/detector isocenter offsets arising from phantom fabrication imprecision. CONCLUSIONS: The authors have developed and validated a novel fiducial phantom-based CBCT beam geometry estimation algorithm that does not require precise positioning of the phantom at machine isocenter and is insensitive to positional imprecision of fiducial markers within the phantom due to fabrication errors. The method can accurately locate source and detector isocenters even when using an imprecise phantom, which is very important for measurement of isocenter coincidence of the therapy and on-board imaging systems.

Reconstruction of brachytherapy seed positions and orientations from cone-beam CT x-ray projections via a novel iterative forward projection matching method.

PURPOSE: To generalize and experimentally validate a novel algorithm for reconstructing the 3D pose (position and orientation) of implanted brachytherapy seeds from a set of a few measured 2D cone-beam CT (CBCT) x-ray projections. METHODS: The iterative forward projection matching (IFPM) algorithm was generalized to reconstruct the 3D pose, as well as the centroid, of brachytherapy seeds from three to ten measured 2D projections. The gIFPM algorithm finds the set of seed poses that minimizes the sum-of-squared-difference of the pixel-by-pixel intensities between computed and measured autosegmented radiographic projections of the implant. Numerical simulations of clinically realistic brachytherapy seed configurations were performed to demonstrate the proof of principle. An in-house machined brachytherapy phantom, which supports precise specification of seed position and orientation at known values for simulated implant geometries, was used to experimentally validate this algorithm. The phantom was scanned on an ACUITY CBCT digital simulator over a full 660 sinogram projections. Three to ten x-ray images were selected from the full set of CBCT sinogram projections and postprocessed to create binary seed-only images. RESULTS: In the numerical simulations, seed reconstruction position and orientation errors were approximately 0.6 mm and 5 degrees, respectively. The physical phantom measurements demonstrated an absolute positional accuracy of (0.78 +/- 0.57) mm or less. The theta and phi angle errors were found to be (5.7 +/- 4.9) degrees and (6.0 +/- 4.1) degrees, respectively, or less when using three projections; with six projections, results were slightly better. The mean registration error was better than 1 mm/6 degrees compared to the measured seed projections. Each test trial converged in 10-20 iterations with computation time of 12-18 min/iteration on a 1 GHz processor. CONCLUSIONS: This work describes a novel, accurate, and completely automatic method for reconstructing seed orientations, as well as centroids, from a small number of radiographic projections, in support of intraoperative planning and adaptive replanning. Unlike standard back-projection methods, gIFPM avoids the need to match corresponding seed images on the projections. This algorithm also successfully reconstructs overlapping clustered and highly migrated seeds in the implant. The accuracy of better than 1 mm and 6 degrees demonstrates that gIFPM has the potential to support 2D Task Group 43 calculations in clinical practice.

Localizing intracavitary brachytherapy applicators from cone-beam CT x-ray projections via a novel iterative forward projection matching algorithm.

PURPOSE: To present a novel method for reconstructing the 3D pose (position and orientation) of radio-opaque applicators of known but arbitrary shape from a small set of 2D x-ray projections in support of intraoperative brachytherapy planning. METHODS: The generalized iterative forward projection matching (gIFPM) algorithm finds the six degree-of-freedom pose of an arbitrary rigid object by minimizing the sum-of-squared-intensity differences (SSQD) between the computed and experimentally acquired autosegmented projection of the objects. Starting with an initial estimate of the object's pose, gIFPM iteratively refines the pose parameters (3D position and three Euler angles) until the SSQD converges. The object, here specialized to a Fletcher-Weeks intracavitary brachytherapy (ICB) applicator, is represented by a fine mesh of discrete points derived from complex combinatorial geometric models of the actual applicators. Three pairs of computed and measured projection images with known imaging geometry are used. Projection images of an intrauterine tandem and colpostats were acquired from an ACUITY cone-beam CT digital simulator. An image postprocessing step was performed to create blurred binary applicators only images. To quantify gIFPM accuracy, the reconstructed 3D pose of the applicator model was forward projected and overlaid with the measured images and empirically calculated the nearest-neighbor applicator positional difference for each image pair. RESULTS: In the numerical simulations, the tandem and colpostats positions (x,y,z) and orientations (alpha, beta, gamma) were estimated with accuracies of 0.6 mm and 2 degrees, respectively. For experimentally acquired images of actual applicators, the residual 2D registration error was less than 1.8 mm for each image pair, corresponding to about 1 mm positioning accuracy at isocenter, with a total computation time of less than 1.5 min on a 1 GHz processor. CONCLUSIONS: This work describes a novel, accurate, fast, and completely automatic method to localize radio-opaque applicators of arbitrary shape from measured 2D x-ray projections. The results demonstrate approximately 1 mm accuracy while compared against the measured applicator projections. No lateral film is needed. By localizing the applicator internal structure as well as radioactive sources, the effect of intra-applicator and interapplicator attenuation can be included in the resultant dose calculations. Further validation tests using clinically acquired tandem and colpostats images will be performed for the accurate and robust applicator/sources localization in ICB patients.

Bow-tie wobble artifact: effect of source assembly motion on cone-beam CT.

PURPOSE: To investigate the cause of a bow-tie wobble artifact (BWA) discovered on Varian OBI CBCT images and to develop practical correction strategies. METHOD AND MATERIALS: The dependence of the BWA on phantom geometry, phantom position, specific system, and reconstruction algorithm was investigated. Simulations were conducted to study the dependence of the BWA on scatter and beam hardening corrections. Geometric calibration was performed to rule out other gantry-angle dependent mechanical non-idealities as BWA causes. Air scans were acquired with ball-bearing markers to study the motions of the x-ray head assembly as functions of gantry angle. Based on measurements, we developed hypothesis regarding the BWA cause. Simulations were performed to validate our hypothesis. Two correction strategies were implemented: a measurement-based method, which acquires gantry-dependent normalization projections (NPs); and a model-based method that involves numerically shifting the single-angle NP to compensate for the previously-measured bow-tie-filter (BTF) motion. RESULTS: The BWA has a diameter of approximately 15 cm, is centered at the isocenter, and is reproducible independent of phantom, position, system, reconstruction, and standard corrections, but only when the BTF is used. Measurements identified a 2D sinusoidal gantry-angle-dependent motion of the x-ray head assembly, and it was the BTF motion (>3 mm amplitude projected onto the detector) resulting an intensity mismatch between the all-angle CBCT projections and a single-angle NP that caused the BWA. Both correction strategies were demonstrated effective. CONCLUSIONS: A geometric mismatch between the BTF modulation patterns on CBCT projections and on the NP causes the BWA. The BTF wobble requires additional degrees of freedom in CBCT geometric calibration to characterize.

Noise-resolution tradeoffs in x-ray CT imaging: a comparison of penalized alternating minimization and filtered backprojection algorithms.

PURPOSE: In comparison with conventional filtered backprojection (FBP) algorithms for x-ray computed tomography (CT) image reconstruction, statistical algorithms directly incorporate the random nature of the data and do not assume CT data are linear, noiseless functions of the attenuation line integral. Thus, it has been hypothesized that statistical image reconstruction may support a more favorable tradeoff than FBP between image noise and spatial resolution in dose-limited applications. The purpose of this study is to evaluate the noise-resolution tradeoff for the alternating minimization (AM) algorithm regularized using a nonquadratic penalty function. METHODS: Idealized monoenergetic CT projection data with Poisson noise were simulated for two phantoms with inserts of varying contrast (7%-238%) and distance from the field-of-view (FOV) center (2-6.5 cm). Images were reconstructed for the simulated projection data by the FBP algorithm and two penalty function parameter values of the penalized AM algorithm. Each algorithm was run with a range of smoothing strengths to allow quantification of the noise-resolution tradeoff curve. Image noise is quantified as the standard deviation in the water background around each contrast insert. Modulation transfer functions (MTFs) were calculated from six-parameter model fits to oversampled edge-spread functions defined by the circular contrast-insert edges as a metric of local resolution. The integral of the MTF up to 0.5 1p/mm was adopted as a single-parameter measure of local spatial resolution. RESULTS: The penalized AM algorithm noise-resolution tradeoff curve was always more favorable than that of the FBP algorithm. While resolution and noise are found to vary as a function of distance from the FOV center differently for the two algorithms, the ratio of noises when matching the resolution metric is relatively uniform over the image. The ratio of AM-to-FBP image variances, a predictor of dose-reduction potential, was strongly dependent on the shape of the AM's nonquadratic penalty function and was also strongly influenced by the contrast of the insert for which resolution is quantified. Dose-reduction potential, reported here as the fraction (%) of FBP dose necessary for AM to reconstruct an image with comparable noise and resolution, for one penalty parameter value of the AM algorithm was found to vary from 70% to 50% for low-contrast and high-contrast structures, respectively, and from 70% to 10% for the second AM penalty parameter value. However, the second penalty, AM-700, was found to suffer from poor low-contrast resolution when matching the high-contrast resolution metric with FBP. CONCLUSIONS: The results of this simulation study imply that penalized AM has the potential to reconstruct images with similar noise and resolution using a fraction (10%-70%) of the FBP dose. However, this dose-reduction potential depends strongly on the AM penalty parameter and the contrast magnitude of the structures of interest. In addition, the authors' results imply that the advantage of AM can be maximized by optimizing the nonquadratic penalty function to the specific imaging task of interest. Future work will extend the methods used here to quantify noise and resolution in images reconstructed from real CT data.

Impact of bowtie filter and detector collimation on multislice CT scatter profiles: A simulation study.

PURPOSE: To investigate via Monte Carlo simulations, the impact of scan subject size, antiscatter grid (ASG), collimator size, and bowtie filter on the distribution of scatter radiation in a typical realistically modeled third generation 16 slice diagnostic computed tomography (CT) scanner. METHODS: Full radiation transport was simulated with Geant4 in a realistic CT scanner geometric model, including the imaging phantom, bowtie filter (BTF), collimators and detector assembly, except for the ASGs. An analytical method was employed to quantify the probable transmission through the ASG of each photon intersecting the detector array. Normalized scatter profiles (NSP) and scatter-to-primary-ratio (SPR) profiles were simulated for 90 and 140 kVp beams for different size phantoms and slice thicknesses. The impact of CT scatter on the reconstructed attenuation coefficient factor was also studied as were the modulating effects of phantom- and patient-tissue heterogeneities on scatter profiles. A method to characterize the relative spatial frequency content of sinogram signals was developed to assess the latter. RESULTS: For the 21.4-cm diameter phantom, NSP and SPR increase linearly with collimator opening for both tube potentials, with the 90 kVp scan exhibiting slightly larger NSP and SPR. The BTF modestly modulates scatter under the phantom center, reducing the prominent off-axis lobes by factors of 1.1-1.3. The ASG reduces scatter on the central axis NSP threefold, and reduces scatter at the detectors outside the phantom shadow by factors of 25 to 500. For the phantoms with diameters of 27 and 32 cm, the scatter increases roughly three- and fourfold, respectively, demonstrating that scatter monotonically increases with phantom size, despite deployment of the ASG and BTF. In the absence of a scan subject, the ASG reduces the signal profile arising photons scattered by the BTF. Without ASG, the in-air scatter profile is relatively flat compared to the scatter profile when the ASG is present. For both 90 and 140 kVp photon spectra, the calculated attenuation coefficient decreases linearly with increasing collimation size. For both homogeneous and heterogeneous objects, NSPs are dominated by low spatial frequency content compared to the primary signal. However, the SPR, which quantifies the local magnitude of nonlinear detector response and is dominated by the high frequency content of the primary profile, can contribute strongly to high-spatial frequency streaking artifacts near high-density structures in reconstructed image artifacts. CONCLUSION: Public-domain Monte Carlo codes, Geant-4 in particular, is a feasible method for characterizing CT detector response to scattered- and off-focal radiation. Our study demonstrates that the ASG substantially reduces the scatter radiation and reshapes scatter-radiation profiles and affects the accuracy with which the detector array can measure narrow-beam attenuation due its inability to distinguish between true uncollided primary and narrow-angle coherently scattered photons. Hence, incorporating the impact of detector array collimation into the forward-projection signal formation models used by iterative reconstruction algorithms is necessary to use CT for accurately characterizing material properties. While tissue heterogeneities exercise a modest influence on local NPS shape and magnitude, they do not add significant high spatial frequency content.

Monte Carlo evaluation of scatter mitigation strategies in cone-beam CT.

PURPOSE: To investigate the efficacy of two widely used scatter mitigation methods: antiscatter grids (ASGs) and beam modulating with bowtie filters (BTFs), in combination with subtractive scatter correction or zeroth order normalization phantom calibration, for improving image noise, contrast, contrast-to-noise ratio (CNR), and image uniformity for on-board cone-beam CT (CBCT) imaging systems used for image-guided radiation therapy. METHODS: PTRAN Monte Carlo CBCT x-ray projections of head and pelvic phantoms were calculated for combinations of beam-modulation and scatter rejection methods and images were reconstructed by in-house developed software. In addition, a simple one-dimensional analytic model was developed to predict scatter-to-primary ratio (SPR) and CNR as a function of cylindrical phantom thickness, ASG transmission, and beam modulation with bow-tie filters. RESULTS: ASGs were found to have slightly negative or no effect on head phantom image CNR and to modestly improve CNR (10%-20%) in pelvic phantom images. However, scatter subtraction and norm-phantom calibration perform better when applied on data acquired with ASGs. Scatter subtraction improves CT number accuracy, but increases noise, and in high SPR/low primary-photon transmission scenarios can dramatically reduce CNR and introduce streaking artifacts. The BTF is found to reduce SPR and image noise, resulting in a better trade-off between CNR and imaging dose, but introduces a circular band artifact. CONCLUSIONS: Our study shows that ASGs have a modest positive impact in pelvic scans and negative in head scans, scatter subtraction improves the HU accuracy but reduces CNR, while BTF has a clearly positive effect.

Clinical application and validation of an iterative forward projection matching algorithm for permanent brachytherapy seed localization from conebeam-CT x-ray projections.

PURPOSE: To experimentally validate a new algorithm for reconstructing the 3D positions of implanted brachytherapy seeds from postoperatively acquired 2D conebeam-CT (CBCT) projection images. METHODS: The iterative forward projection matching (IFPM) algorithm finds the 3D seed geometry that minimizes the sum of the squared intensity differences between computed projections of an initial estimate of the seed configuration and radiographic projections of the implant. In-house machined phantoms, containing arrays of 12 and 72 seeds, respectively, are used to validate this method. Also, four 103Pd postimplant patients are scanned using an ACUITY digital simulator. Three to ten x-ray images are selected from the CBCT projection set and processed to create binary seed-only images. To quantify IFPM accuracy, the reconstructed seed positions are forward projected and overlaid on the measured seed images to find the nearest-neighbor distance between measured and computed seed positions for each image pair. Also, the estimated 3D seed coordinates are compared to known seed positions in the phantom and clinically obtained VariSeed planning coordinates for the patient data. RESULTS: For the phantom study, seed localization error is (0.58 +/- 0.33) mm. For all four patient cases, the mean registration error is better than 1 mm while compared against the measured seed projections. IFPM converges in 20-28 iterations, with a computation time of about 1.9-2.8 min/ iteration on a 1 GHz processor. CONCLUSIONS: The IFPM algorithm avoids the need to match corresponding seeds in each projection as required by standard back-projection methods. The authors' results demonstrate approximately 1 mm accuracy in reconstructing the 3D positions of brachytherapy seeds from the measured 2D projections. This algorithm also successfully localizes overlapping clustered and highly migrated seeds in the implant.

Feasibility of proton FLASH irradiation using a synchrocyclotron for preclinical studies.

PURPOSE: It has been recently shown that radiotherapy at ultrahigh dose rates (>40 Gy/s, FLASH) has a potential advantage in sparing healthy organs compared to that at conventional dose rates. The purpose of this work is to show the feasibility of proton FLASH irradiation using a gantry-mounted synchrocyclotron as a first step toward implementing an experimental setup for preclinical studies. METHODS: A clinical Mevion HYPERSCAN® synchrocyclotron was modified to deliver ultrahigh dose rates. Pulse widths of protons with 230 MeV energy were manipulated from 1 to 20 µs to deliver in conventional and ultrahigh dose rate. A boron carbide absorber was placed in the beam for range modulation. A Faraday cup was used to determine the number of protons per pulse at various dose rates. Dose rate was determined by the dose measured with a plane-parallel ionization chamber with respect to the actual delivery time. The integral depth dose (IDD) was measured with a Bragg ionization chamber. Monte Carlo simulation was performed in TOPAS as the secondary check for the measurements. RESULTS: Maximum protons charge per pulse, measured with the Faraday cup, was 54.6 pC at 20 µs pulse width. The measured IDD agreed well with the Monte Carlo simulation. The average dose rate measured using the ionization chamber showed 101 Gy/s at the entrance and 216 Gy/s at the Bragg peak with a full width at half maximum field size of 1.2 cm. CONCLUSIONS: It is feasible to deliver protons at 100 and 200 Gy/s average dose rate at the plateau and the Bragg peak, respectively, in a small ~1 cm2 field using a gantry-mounted synchrocyclotron.

Optimal densitometry wavelengths that maximize radiochromic film sensitivity while minimizing OD growth and temperature sensitivity artifacts.

It is well known that optical density (OD) of the radiochromic film (RCF) continues to grow after exposure at rates that have a complex dependence on dose, temperature, and densitometry wavelength. Dose rate and fractionation artifacts associated with variations in OD growth may limit the accuracy achievable by RCF dosimetry in brachytherapy and external beam applications, particularly at low doses (<5 Gy) and low dose rates (<10 cGy/h) where OD growth and sensitivity effects are large. To identify densitometry wavelengths that minimize OD growth artifacts and enhance RCF sensitivity at low doses, we have investigated Model MD-55-2 RCF response as a function of densitometry wavelength, irradiation-to-densitometry time interval, dose and temperature. Using a Perkin Elmer spectrophotometer, the absorption spectrum in the 500-700 nm range was measured for doses ranging from 1-100 Gy, over post-irradiation times from 1 h to 60 days. An empirical model with time-independent, fast and slow growth components was used to fit single exposure data and the dependence of the resulting best-fit parameters on dose and densitometry wavelength was investigated. RCF OD variation with temperature in the range 22-40 degrees was measured. Wavelengths in the 660-690 nm range were found to minimize the dose-dependence of OD post-exposure growth. Densitometry wavelengths in the range of 670-680 nm enhance RCF sensitivity and show small variations in OD with temperature in the range from 22-40 degrees. Compared to 633 nm light, 675 nm densitometry reduces OD growth at 1 Gy from 70% to 10% over a period of nearly 1174.0 h relative to the initial OD measured at 1.7 h post-irradiation. In addition, RCF sensitivity is nearly doubled at this wavelength for all dose levels.

Concurrent chemoradiation for cervical cancer: Comparison of LDR and HDR brachytherapy.

PURPOSE: To compare clinical outcomes between low-dose-rate (LDR) brachytherapy and high-dose-rate (HDR) brachytherapy for cervical cancer patients. METHODS AND MATERIALS: All consecutive newly diagnosed cervical cancer patients undergoing pretreatment 18-fluorodeoxyglucose positron emission tomography imaging and treated with curative-intent definitive chemoradiation from 1997 to 2016 at a U.S. academic center were included. Brachytherapy boost was LDR or HDR 2D treatment planning from 1997 to 2005 and HDR with MR-based 3D planning from 2005 to 2016. Local control (LC), cancer-specific survival (CSS), and late bowel/bladder complications were evaluated. RESULTS: Tumor stages were International Federation of Gynecology and Obstetrics IB1-IIB (n = 457; 75%) and III-IVA (n = 152; 25%). Brachytherapy was LDR for 104 patients and HDR for 505 patients. Concurrent weekly cisplatin was administered to 536 patients (88%). With median followup of 9.4 years, there was no difference in LC (p = 0.24) or CSS (p = 0.50) between LDR and HDR brachytherapy. Cox multivariable regression showed that only International Federation of Gynecology and Obstetrics stage III-IVA (HR=2.4, p = 0.004) was associated with worse LC. A propensity-matched cohort (90 LDR vs. 90 HDR) was created, and the 5-year LC rates were 88% LDR and 82% HDR, p = 0.26; 5-year CSS rates were 66% LDR and 58% HDR, p = 0.19; 5-year grade ≥3 bowel/bladder toxicities were 23% LDR and 16% HDR, p = 0.44. For all patients, the 5-year late toxicity in stage III-IVA patients was higher with LDR 47% vs. HDR 15%, p = 0.03, with no difference in LC, 86% and 75%, respectively (p = 0.09). CONCLUSIONS: There was no difference in LC with either LDR or HDR brachytherapy. The late complication rate was reduced with HDR and 3D-planned brachytherapy compared to LDR and 2D-planned brachytherapy.

Experimental implementation of a joint statistical image reconstruction method for proton stopping power mapping from dual-energy CT data.

PURPOSE: To experimentally commission a dual-energy CT (DECT) joint statistical image reconstruction (JSIR) method, which is built on a linear basis vector model (BVM) of material characterization, for proton stopping power ratio (SPR) estimation. METHODS: The JSIR-BVM method builds on the relationship between the energy-dependent photon attenuation coefficients and the proton stopping power via a pair of BVM component weights. The two BVM component images are simultaneously reconstructed from the acquired DECT sinograms and then used to predict the electron density and mean excitation energy (I-value), which are required by the Bethe equation for SPR computation. A post-reconstruction image-based DECT method, which utilizes the two separate CT images reconstructed via the scanner's software, was implemented for comparison. The DECT measurement data were acquired on a Philips Brilliance scanner at 90 and 140 kVp for two phantoms of different sizes. Each phantom contains 12 different soft and bony tissue surrogates with known compositions. The SPR estimation results were compared to the reference values computed from the known compositions. The difference of the computed water equivalent path lengths (WEPL) across the phantoms between the two methods was also compared. RESULTS: The overall root-mean-square (RMS) of SPR estimation error of the JSIR-BVM method are 0.33% and 0.37% for the head- and body-sized phantoms, respectively, and all SPR estimates of the test samples are within 0.7% of the reference ground truth. The image-based method achieves overall RMS errors of 2.35% and 2.50% for the head- and body-sized phantoms, respectively. The JSIR-BVM method also reduces the pixel-wise random variation by 4-fold to 6-fold within homogeneous regions compared to the image-based method. The average differences between the JSIR-BVM method and the image-based method are 0.54% and 1.02% for the head- and body-sized phantoms, respectively. CONCLUSION: By taking advantage of an accurate polychromatic CT data model and a model-based DECT statistical reconstruction algorithm, the JSIR-BVM method accounts for both systematic bias and random noise in the acquired DECT measurement data. Therefore, the JSIR-BVM method achieves good accuracy and precision on proton SPR estimation for various tissue surrogates and object sizes. In contrast, the experimentally achievable accuracy of the image-based method may be limited by the uncertainties in the image formation process. The result suggests that the JSIR-BVM method has the potential for more accurate SPR prediction compared to post-reconstruction image-based methods in clinical settings.