Evaluation of scatter rejection and correction performance of 2D antiscatter grids in cone beam computed tomography

2D antiscatter grid and scatter sampling based CBCT method for online dose calculations during CBCT guided radiation therapy of pelvis

BACKGROUND

Online dose calculations before the delivery of radiation treatments have applications in dose delivery verification, online adaptation of treatment plans, and simulation-free treatment planning. While dose calculations by directly utilizing CBCT images are desired, dosimetric accuracy can be compromised due to relatively lower HU accuracy in CBCT images.

PURPOSE

In this work, we propose a novel CBCT imaging pipeline to enhance the accuracy of CBCT-based dose calculations in the pelvis region. Our approach aims to improve the HU accuracy in CBCT images, thereby improving the overall accuracy of CBCT-based dose calculations prior to radiation treatment delivery.

METHODS

An in-house developed quantitative CBCT pipeline was implemented to address the CBCT raw data contamination problem. The pipeline combines algorithmic data correction strategies and 2D antiscatter grid-based scatter rejection to achieve high CT number accuracy. To evaluate the effect of the quantitative CBCT pipeline on CBCT-based dose calculations, phantoms mimicking pelvis anatomy were scanned using a linac-mounted CBCT system, and a gold standard multidetector CT used for treatment planning (pCT). A total of 20 intensity-modulated treatment plans were generated for five targets, using 6 and 10 MV flattening filter-free beams, and utilizing small and large pelvis phantom images. For each treatment plan, four different dose calculations were performed using pCT images and three CBCT imaging configurations: quantitative CBCT, clinical CBCT protocol, and a high-performance 1D antiscatter grid (1D ASG). Subsequently, dosimetric accuracy was evaluated for both targets and organs at risk as a function of patient size, target location, beam energy, and CBCT imaging configuration.

RESULTS

When compared to the gold-standard pCT, dosimetric errors in quantitative CBCT-based dose calculations were not significant across all phantom sizes, beam energies, and treatment sites. The largest error observed was 0.6% among all dose volume histogram metrics and evaluated dose calculations. In contrast, dosimetric errors reached up to 7% and 97% in clinical CBCT and high-performance ASG CBCT-based treatment plans, respectively. The largest dosimetric errors were observed in bony targets in the large phantom treated with 6 MV beams. The trends of dosimetric errors in organs at risk were similar to those observed in the targets.

CONCLUSIONS

The proposed quantitative CBCT pipeline has the potential to provide comparable dose calculation accuracy to the gold-standard planning CT in photon radiation therapy for the abdomen and pelvis. These robust dose calculations could eliminate the need for density overrides in CBCT images and enable direct utilization of CBCT images for dose delivery monitoring or online treatment plan adaptations before the delivery of radiation treatments.

Feasibility of dual-energy CBCT material decomposition in the human torso with 2D anti-scatter grids and grid-based scatter sampling

BACKGROUND

Dual-energy (DE) imaging techniques in cone-beam computed tomography (CBCT) have potential clinical applications, including material quantification and improved tissue visualization. However, the performance of DE CBCT is limited by the effects of scattered radiation, which restricts its use to small object imaging.

PURPOSE

This study investigates the feasibility of DE CBCT material decomposition by reducing scatter with a 2D anti-scatter grid and a measurement-based scatter correction method. Specifically, the investigation focuses on iodine quantification accuracy and virtual monoenergetic (VME) imaging in phantoms that mimic head, thorax, abdomen, and pelvis anatomies.

METHODS

A 2D anti-scatter grid prototype was utilized with a residual scatter correction method in a linac-mounted CBCT system to investigate the effects of robust scatter suppression in DE CBCT. Scans were acquired at 90 and 140 kVp using phantoms that mimic head, thorax, and abdomen/pelvis anatomies. Iodine vials with varying concentrations were placed in each phantom, and CBCT images were decomposed into iodine and water basis material images. The effect of a 2D anti-scatter grid with and without residual scatter correction on iodine concentration quantification and contrast visualization in VME images was evaluated. To benchmark iodine concentration quantification accuracy, a similar set of experiments and DE processing were also performed with a conventional multidetector CT scanner.

RESULTS

In CBCT images, a 2D grid with or without scatter correction can differentiate iodine and water after DE processing in human torso-sized phantom images. However, iodine quantification errors were up to 10 mg/mL in pelvis phantoms when only the 2D grid was used. Adding scatter correction to 2D-grid CBCT reduced iodine quantification errors below 1.5 mg/mL in pelvis phantoms, comparable to iodine quantification errors in multidetector CT. While a noticeable contrast-to-noise ratio improvement was not observed in VME CBCT images, contrast visualization was substantially better in 40 keV VME images in visual comparisons with 90 and 140 kVp CBCT images across all phantom sizes investigated.

CONCLUSIONS

This study indicates that accurate DE decomposition is potentially feasible in DE CBCT of the human torso if robust scatter suppression is achieved with 2D anti-scatter grids and residual scatter correction. This approach can potentially enable better contrast visualization and tissue and contrast agent quantification in various CBCT applications.

A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy

BACKGROUND

Quantitative accuracy is critical for expanding the role of cone beam CT (CBCT) imaging from target localization to quantitative treatment monitoring and plan adaptations in radiation therapy. Despite advances in CBCT image quality improvement methods, quantitative accuracy gap between CBCT and multi-detector CT (MDCT) remains.

PURPOSE

In this work, a physics-driven approach was investigated that combined robust scatter rejection, raw data correction and iterative image reconstruction to further improve CBCT image quality and quantitative accuracy, referred to as quantitative CBCT (qCBCT).

METHODS

QCBCT approach includes tungsten 2D antiscatter grid hardware, residual scatter correction with grid-based scatter sampling, image lag, and beam hardening correction for offset detector geometry linac-mounted CBCT. Images were reconstructed with iterative image reconstruction to reduce image noise. qCBCT was evaluated using a variety of phantoms to investigate the effect of object size and its composition on image quality, and image quality was benchmarked against clinical CBCT and gold standard MDCT images used for treatment planning.

RESULTS

QCBCT provided statistically significant improvement in CT number accuracy and reduced image artifacts when compared to clinical CBCT images. When compared to gold standard MDCT, mean HU errors in qCBCT and clinical CBCT were 17 ± 9 and 38 ± 29 HU, respectively. Magnitude of phantom size dependent HU variations were comparable between MDCT and qCBCT images. With iterative reconstruction, contrast-to-noise ratio improved by 25% when compared to clinical CBCT protocols.

CONCLUSIONS

Combination of novel scatter suppression techniques and other data correction methods in qCBCT provided CT number accuracy comparable to gold standard MDCT used for treatment planning. This approach may potentially improve CBCT's promise in fulfilling the tasks that demand high quantitative accuracy, such as online dose calculations and treatment response assessment, in image guided radiation therapy.

A simulation study to evaluate the effect of 2D antiscatter grid primary transmission on flat panel detector based CBCT image quality

Purpose. Two-dimensional antiscatter grids' (2D-ASGs) septal shadows and their impact on primary transmission play a critical role in cone-beam computed tomography (CBCT) image noise and artifact characteristics. Therefore, a numerical simulation platform was developed to evaluate the effect of 2D-ASG's primary transmission on image quality, as a function of grid geometry and CBCT system properties.Methods. To study the effect of 2D-ASG's septal shadows on primary transmission and CBCT image quality, two new methods were introduced; one to simulate projection signal gradients in septal shadows, and the other to simulate septal shadow variations due to gantry flex. Signal gradients in septal shadows were simulated by generating a system point spread function that was directly extracted from projection images of 2D-ASG prototypes in experiments. Variations in septal shadows due to gantry flex were simulated by generating oversampled shadow profiles extracted from experiments. Subsequently, the effect of 2D-ASG's septal shadows on primary transmission and image quality was evaluated.Results.For an apparent septal thickness of 0.15 mm, the primary transmission of 2D-ASG varied between 72%-90% for grid pitches 1-3 mm. In low-contrast phantoms, the effect of 2D-ASG's radiopaque footprint on information loss was subtle. At high spatial frequencies, information loss manifested itself as undersampling artifacts, however, its impact on image quality is subtle when compared to quantum noise. Effects of additive electronic noise and gantry flex induced ring artifacts on image quality varied as a function of grid pitch and septal thickness. Such artifacts were substantially less in lower resolution images.Conclusion. The proposed simulation platform allowed successful evaluation of CBCT image quality variations as a function of 2D-ASG primary transmission properties and CBCT system characteristics. This platform can be potentially used for optimizing 2D-ASG design properties based on the imaging task and properties of the CBCT system.

Monte Carlo model of a prototype flat-panel detector for multi-energy applications in radiotherapy

BACKGROUND

The incorporation of multi-energy capabilities into radiotherapy flat-panel detectors offers advantages including enhanced soft tissue visualization by reduction of signal from overlapping anatomy such as bone in 2D image projections; creation of virtual monoenergetic images for 3D contrast enhancement, metal artefact reduction and direct acquisition of relative electron density. A novel dual-layer on-board imager offering dual energy processing capabilities is being designed. As opposed to other dual-energy implementation techniques which require separate acquisition with two different x-ray spectra, the dual-layer detector design enables simultaneous acquisition of high and low energy images with a single exposure. A computational framework is required to optimize the design parameters and evaluate detector performance for specific clinical applications.

PURPOSE

In this study, we report on the development of a Monte Carlo (MC) model of the imager including model validation.

METHODS

The stack-up of the dual-layer imager (DLI) was implemented in GEANT4 Application for Tomographic Emission (GATE). The DLI model has an active area of 43×43 cm2 , with top and bottom Cesium Iodide (CsI) scintillators of 600 and 800 μm thickness, respectively. Measurement of spatial resolution and imaging of dedicated multi-material dual-energy (DE) phantoms were used to validate the model. The modulation transfer function (MTF) of the detector was calculated for a 120 kVp x-ray spectrum using a 0.5 mm thick tantalum edge rotated by 2.5o . For imaging validation, the DE phantom was imaged using a 140 kVp x-ray spectrum. For both validation simulations, corresponding measurements were done using an initial prototype of the imager. Agreement between simulations and measurement was assessed using normalized root mean square error (NRMSE) and 1D profile difference for the MTF and phantom images respectively. Further comparison between measurement and simulation was made using virtual monoenergetic images (VMIs) generated from basis material images derived using precomputed look-up tables.

RESULTS

The MTF of the bottom layer of the dual-layer model shows values decreasing more quickly with spatial frequency, compared to the top layer, due to the thicker bottom scintillator thickness and scatter from the top layer. A comparison with measurement shows NRMSE of 0.013 and 0.015 as well as identical MTF50 of 0.8 mm1 and 1.0 mm1 for the top and bottom layer respectively. For the DE imaging of the DE-phantom, although a maximum deviation of 3.3% is observed for the 10 mm aluminum and Teflon inserts at the top layer, the agreement for all other inserts is less than 2.2% of the measured value at both layers. Material decomposition of simulated scatter-free DE images gives an average accuracy in PMMA and aluminum composition of 4.9% and 10.3% for 11-30 mm PMMA and 1-10 mm aluminum objects respectively. A comparison of decomposed values using scatter containing measured and simulated DE images shows good agreement within statistical uncertainty.

CONCLUSION

Validation using both MTF and phantom imaging shows good agreement between simulation and measurements. With the present configuration of the digital prototype, the model can generate material decomposed images and virtual monoenergetic images.

Evaluation of the feasibility of a multisource CBCT for maxillofacial imaging

Objective. The aim of this study was to investigate the feasibility of improving the image quality and accuracy of cone beam computed tomography (CBCT) by replacing the conventional wide cone angle x-ray tube with a distributed x-ray source array positioned in the axial direction.Approach. The multisource CBCT (ms-CBCT) design was experimentally simulated using a benchtop scanner with a carbon nanotube x-ray tube and a flat-panel detector. The source was collimated and translated in the axial direction to simulate a source array with a reduced cone angle for each beam. An adjacent scatter ratio subtraction (ASRS) method was implemented for residual scatter reduction. Several phantoms were imaged using the ms-CBCT and conventional CBCT configurations under otherwise similar conditions. The Requirements of the ms-CBCT design on the x-ray source and detector were evaluated.Main results. Compared to the conventional CBCT, the ms-CBCT design with 8 sources and ASRS significantly improved the image quality and accuracy, including: (1) reducing the cupping artifact from 15% to 3.5%; (2) reducing the spatial nonuniformity of the CT Hounsfield unit values from 38.0 to 9.2; (3) improving the contrast-to-noise ratio of the low contrast objects (acrylic and low density polyethylene inserts) against the water-equivalent background by ∼20% and (4) reducing the root-mean-square error of the HU values by 70%, from 420.1 to 124.4. The imaging dose and scanning time used by the current clinical CBCT for maxillofacial imaging can be achieved by current source and detector technologies.Significance. The ms-CBCT design significantly reduces the scatter and improves the image quality and accuracy compared to the conventional CBCT.

A correlated sampling-based Monte Carlo simulation for fast CBCT iterative scatter correction

BACKGROUND

In recent years, cone-beam computed tomography (CBCT) has played an important role in medical imaging. However, the applications of CBCT are limited due to the severe scatter contamination. Conventional Monte Carlo (MC) simulation can provide accurate scatter estimation for scatter correction, but the expensive computational cost has always been the bottleneck of MC method in clinical application.

PURPOSE

In this work, an MC simulation method combined with a variance reduction technique called correlated sampling is proposed for fast iterative scatter correction.

METHODS

Correlated sampling exploits correlation between similar simulation systems to reduce the variance of interest quantities. Specifically, conventional MC simulation is first performed on the scatter-contaminated CBCT to generate the initial scatter signal. In the subsequent correction iterations, scatter estimation is then updated by applying correlated MC sampling to the latest corrected CBCT images by reusing the random number sequences of the task-related photons in conventional MC. Afterward, the corrected projections obtained by subtracting the scatter estimation from raw projections are utilized for FDK reconstruction. These steps are repeated until an adequate scatter correction is obtained. The performance of the proposed framework is evaluated by the accuracy of the scatter estimation, the quality of corrected CBCT images and efficiency.

RESULTS

Overall, the difference in mean absolute percentage error between scatter estimation with and without correlated sampling is 0.25% for full-fan case and 0.34% for half-fan case, respectively. In simulation studies, scatter artifacts are substantially eliminated, where the mean absolute error value is reduced from 15 to 2 HU in full-fan case and from 53 to 13 HU in half-fan case. Scatter-to-primary ratio is reduced to 0.02 for full-fan and 0.04 for half-fan, respectively. In phantom study, the contrast-to-noise ratio (CNR) is increased by a factor of 1.63, and the contrast is increased by a factor of 1.77. As for clinical studies, the CNR is improved by 11% and 14% for half-fan and full-fan, respectively. The contrast after correction is increased by 19% for half-fan and 44% for full-fan. Furthermore, root mean square error is also effectively reduced, especially from 78 to 4 HU for full-fan. Experimental results demonstrate that the figure of merit is improved between 23 and 43 folds when using correlated sampling. The proposed method takes less than 25 s for the whole iterative scatter correction process.

CONCLUSIONS

The proposed correlated sampling-based MC simulation method can achieve fast and accurate scatter correction for CBCT, making it suitable for real-time clinical use.

3D-printed large-area focused grid for scatter reduction in cone-beam CT

BACKGROUND

Cone-beam computed tomography (CBCT) systems acquire volumetric data more efficiently than fan-beam or multislice CT, particularly when the anatomy of interest resides within the axial field-of-view of the detector and data can be acquired in one rotation. For such systems, scattered radiation remains a source of image quality degradation leading to increased noise, image artifacts, and CT number inaccuracies.

PURPOSE

Recent advances in metal additive manufacturing allow the production of highly focused antiscatter grids (2D-ASGs) that can be used to reduce scatter intensity, while preserving primary radiation transmission. We present the first implementation of a large-area, 2D-ASG for flat-panel CBCT, including grid-line artifact removal and related improvements in image quality.

METHODS

A 245 × 194 × 10 mm 2D-ASG was manufactured from chrome-cobalt alloy using laser powder-bed fusion (LPBF) (AM-400; Renishaw plc, New Mills Wotton-under-Edge, UK). The 2D-ASG had a square profile with a pitch of 9.09 lines/cm and 10:1 grid-ratio. The nominal 0.1 mm grid septa were focused to a 732 mm x-ray source to optimize primary x-ray transmission and reduce grid-line shadowing at the detector. Powder-bed fusion ensured the structural stability of the ASG with no need for additional interseptal support. The 2D-ASG was coupled to a 0.139-mm element pitch flat-panel detector (DRX 3543, Carestream Health) and proper alignment was confirmed by consistent grid-line shadow thickness across the whole detector array. A 154-mm diameter CBCT image-quality-assurance phantom was imaged using a rotary stage and a ceiling-mounted, x-ray unit (Proteus XR/a, GE Medical Systems, 80kVp, 0.5mAs). Grid-line artifacts were removed using a combination of exposure-dependent gain correction and spatial-frequency, Fourier filtering. Projections were reconstructed using a Parker-weighted, FDK algorithm and voxels were spatially averaged to 357 × 357 × 595 µm to improve the signal-to-noise characteristics of the CBCT reconstruction. Finally, in order to compare image quality with and without scatter, the phantom was scanned again under the same CBCT conditions but with no 2D-ASG. No additional antiscatter (i.e., air-gap, bowtie filtration) strategies were used to evaluate the effects in image quality caused by the 2D-ASG alone.

RESULTS

The large-area, 2D-ASG prototype was successfully designed and manufactured using LPBF. CBCT image-quality improvements using the 2D-ASG included: an overall 14.5% CNR increase across the volume; up to 48.8% CNR increase for low-contrast inserts inside the contrast plate of the QA phantom; and a 65% reduction of cupping artifact in axial profiles of water-filled cross sections of the phantom. Advanced image processing strategies to remove grid line artifacts did not affect the spatial resolution or geometric accuracy of the system.

CONCLUSIONS

LPBF can be used to manufacture highly efficient, 2D-focused ASGs that can be easily coupled to clinical, flat-panel detectors. The implementation of ASGs in CBCT leads to reduced scatter-related artifacts, improved CT number accuracy, and enhanced CNR with no increased equivalent dose to the patient. Further improvements to image quality might be achieved with a combination of scatter-correction algorithms and iterative-reconstruction strategies. Finally, clinical applications where other scatter removal strategies are unfeasible might now achieve superior soft-tissue visualization and quantitative capabilities.

Concurrent kilovoltage CBCT imaging and megavoltage beam delivery: suppression of cross-scatter with 2D antiscatter grids and grid-based scatter sampling

Objective. The concept of using kilovoltage (kV) and megavoltage (MV) beams concurrently has potential applications in cone beam computed tomography (CBCT) guided radiation therapy, such as single breath hold scans, metal artifact reduction, and simultaneous imaging during MV treatment delivery. However, MV cross-scatter generated during MV beam delivery degrades CBCT image quality. To address this, a 2D antiscatter grid and a cross-scatter correction method were investigated in the context of high dose MV treatment delivery.Approach. A 3D printed, tungsten 2D antiscatter grid prototype was utilized in kV CBCT scans to reduce MV cross-scatter fluence during concurrent MV beam delivery. Remaining cross-scatter in projections was corrected by using the 2D grid itself as a cross-scatter intensity sampling device, referred to as grid-based scatter sampling (GSS). To test this approach, kV CBCT acquisitions were performed while delivering 6 and 10 MV beams, mimicking high dose rate treatment delivery scenarios. kV and MV beam deliveries were not synchronized to eliminate MV beam delivery interruption. MV cross-scatter suppression performance of the proposed approach was evaluated in projections and CBCT images of phantoms.Main results. 2D grid reduced the intensity of MV cross-scatter in kV projections by a factor of 3 on the average, when compared to conventional antiscatter grid. Remaining cross scatter as measured by the GSS method was within 7% of measured reference intensity values, and subsequently corrected. CBCT image quality was improved substantially during concurrent kV-MV beam delivery. Median Hounsfield Unit (HU) inaccuracy was up to 182 HU without our methods, and it was reduced to a median 6.5 HU with our 2D grid and scatter correction approach. Our methods provided a factor of 2-6 improvement in contrast-to-noise ratio.Significance. This investigation demonstrates the utility of 2D antiscatter grids and grid-based scatter sampling in suppressing MV cross-scatter. Our approach successfully minimized the effects of MV cross-scatter in concurrent kV CBCT imaging and high dose MV treatment delivery scenarios. Hence, robust MV cross-scatter suppression is potentially feasible without MV beam delivery interruption or compromising kV image acquisition rate.

Megavoltage cross-scatter rejection and correction using 2D antiscatter grids in kilovoltage CBCT imaging

Simultaneous use of kilovoltage (kV) and megavoltage (MV) beams has numerous potential applications in cone beam computed tomography (CBCT)-guided radiotherapy, such as fast MV+kV CBCT for single breath-hold scan, tumor localization with kV CBCT imaging during MV therapy delivery, and metal artifact suppression. However, the introduction of MV beams results in a large MV-cross scatter fluence incident on the kV Flat Panel Detector (FPD), and thus, deteriorating the low contrast visualization and Hounsfield Unit (HU) accuracy. In this work, we introduced a novel and robust method for reducing the effects of MV cross scatter. First, we implemented a 2D antiscatter grid atop the detector which rejects a large section of MV cross scatter. This hardware-based approach, while effective, allows a fraction of MV cross scatter to be transmitted to the FPD, resulting in artifacts and degraded HU accuracy in CBCT images. We thus introduced a data correction step, which aimed to estimate and correct the remaining MV cross scatter. This approach, referred to as Grid-Based Scatter Sampling, utilized 2D antiscatter grid itself to measure and correct remaining MV cross scatter in projections. We investigated the performance of the proposed approach in experiments by simultaneously acquiring kV CBCT and delivering MV beams with a clinical linac. The results show that the proposed method can substantially reduce HU inaccuracy and increase contrast-to-noise ratio (CNR). Our method does not require synchronization of kV and MV beam pulses, reduction of kV frame acquisition rate, or MV dose rate, and therefore, it is more practical to implement in radiation therapy clinical setting.

Mutual Information-Based Non-Local Total Variation Denoiser for Low-Dose Cone-Beam Computed Tomography

Conventional non-local total variation (NLTV) approaches use the weight of a non-local means (NLM) filter, which degrades performance in low-dose cone-beam computed tomography (CBCT) images generated with a low milliampere-seconds (mAs) parameter value because a local patch used to determine the pixel weights comprises noisy-damaged pixels that reduce the similarity between corresponding patches. In this paper, we propose a novel type of NLTV based on a combination of mutual information (MI): MI-NLTV. It is based on a statistical measure for a similarity calculation between the corresponding bins of non-local patches vs. a reference patch. The weight is determined in terms of a statistical measure comprising the MI value between corresponding non-local patches and the reference-patch entropy. The MI-NLTV denoising process is applied to CBCT images generated by the analytical reconstruction algorithm using a ray-driven backprojector (RDB). The MI-NLTV objective function is minimized based on the steepest gradient descent optimization to augment the difference between a real structure and noise, cleaning noisy pixels without significant loss of the fine structure and details that remain in the reconstructed images. The proposed method was evaluated using patient data and actual phantom measurement data acquired with lower mAs. The results show that integrating the RDB further enhances the MI-NLTV denoising-based analytical reconstruction algorithm to achieve a higher CBCT image quality when compared with those generated by NLTV denoising-based approach, with an average of 15.97% higher contrast-to-noise ratio, 2.67% lower root mean square error, 0.12% lower spatial non-uniformity, 1.14% higher correlation, and an average of 18.11% higher detectability index. These quantitative results indicate that the incorporation of MI makes the NLTV more stable and robust than the conventional NLM filter for low-dose CBCT imaging. In addition, achieving clinically acceptable CBCT image quality despite low-mAs projection acquisition can reduce the burden on common online CBCT imaging, improving patient safety throughout the course of radiotherapy.