Bowtie Filter Research Articles

Development and verification of a novel system for computed tomography scanner model construction in Monte Carlo simulations

The accuracy of Monte Carlo (MC) simulations in estimating the computed tomography radiation dose is highly dependent on the accuracy of CT scanner model. A system was developed to observe the 3D model intuitively and to calculate the X-ray energy spectrum and the bowtie (BT) filter model more accurately in Monte Carlo N-particle (MCNP). Labview's built-in Open Graphics Library (OpenGL) was used to display basic surfaces, and constructive solid geometry (CSG) method was used to realize Boolean operations. The energy spectrum was calculated by simulating the process of electronic shooting and the BT filter model was accurately modeled based on the calculated shape curve. Physical data from a study was used as an example to illustrate the accuracy of the constructed model. RMSE between the simulation and the measurement results were 0.97% and 0.74% for two filters of different shapes. It can be seen from the comparison results that to obtain an accurate CT scanner model, physical measurements should be taken as the standard. The energy spectrum library should be established based on Monte Carlo simulations with modifiable input files. It is necessary to use the three-segment splicing modeling method to construct the bowtie filter model.

Correction of Bowtie filter induced scatter signals based on air scan data and object scan data

In a cone beam CT system, a bowtie filter brings in additional scatter signals with respect to object induced scatter signals, which can degrade image quality and sometimes result in artifacts. This work aims to improve the image quality of CT scans by analyzing the contribution of bowtie filter induced scatter signals and removing them from projection data. Air calibration is a very useful preprocessing step to eliminate the response variations of detector pixels. Bowtie filter induced scattered x-ray signals of air scans are recorded in air calibration tables and therefore considered as a part of primary signals. However, scattered X-rays behave differently in scanned objects compared to primary x-rays. The difference should be corrected to eliminate the impact of bowtie filter induced scatter signals. A kernel based correction algorithm based on air scan data, named bowtie filter scatter correction algorithm, is applied to estimate and to eliminate the bowtie filter induced scatter signals in object scans. The scatter signals of air scans can be measured with air scans or retrieved from air calibration tables of a CT system, and can be used as input of the correction algorithm to estimate the change of scatter signals caused by the scanned objects in the scan field. Based on the assumption that the scatter signals in the projection data scanned with narrow collimation can be neglected, the difference signals between narrow and broad collimations can be used to estimate bowtie filter induced scatter signals for air scans with the correction of extra-focal radiations (EFRs). The calculated bowtie filter induced scatter signals have been compared with the results of Monte Carlo simulations, and the parameters of correction algorithm have been determined by fitting the measured scatter signal curves of phantom scans with calculated curves. Projection data have been reconstructed using Filtered BackProjection (FBP) method with and without bowtie filter correction to check whether the image quality is improved. Scatter signals can be well approximated with the bowtie filter scatter correction algorithm together with an existing object scatter correction algorithm. After removing the bowtie filter induced scatter signals, the dark bands in reconstructed images in the regions near the edges of scanned objects can be mostly eliminated. The difference signals of air scan data between narrow and broad collimations can be used to estimate the bowtie filter induced scatter for air scans. The proposed bowtie filter scatter correction algorithm using air scan data can be applied to estimate and to remove most of the bowtie filter induced scatter signals in object scans.

Single-material beam hardening correction via an analytical energy response model for diagnostic CT.

Various clinical studies show the potential for a wider quantitative role of diagnostic X-ray computed tomography (CT) beyond size measurements. Currently, the clinical use of attenuation values is, however, limited due to their lack of robustness. This issue can be observed even on the same scanner across patient size and positioning. There are different causes for the lack of robustness in the attenuation values; one possible source of error is beam hardening of the X-ray source spectrum. The conventional and well-established approach to address this issue is a calibration-based single material beam hardening correction (BHC) using a watercylinder. We investigate an alternative approach for single-material BHC with the aim of producing a more robust result for the attenuation values. The underlying hypothesis of this investigation is that calibration-based BHC automatically corrects for scattered radiation in a manner that is suboptimal in terms of bias as soon as the scanned object strongly deviates from the water cylinder used for calibration. The approach we propose performs BHC via an analytical energy response model that is embedded into a correction pipeline that efficiently estimates and subtracts scattered radiation in a patient-specific manner prior to BHC. The estimation of scattered radiation is based on minimizing, in average, the squared difference between our corrected data and the vendor-calibrated data. The used energy response model is considering the spectral effects of the detector response and the prefiltration of the source spectrum, including a beam-shaping bowtie filter. The performance of the correction pipeline is first characterized with computer simulated data. Afterward, it is tested using real 3-D CT data sets of two different phantoms, with various kV settings and phantom positions, assuming a circular data acquisition. The results are compared in the image domain to those from thescanner. For experiments with a water cylinder, the proposed correction pipeline leads to similar results as the vendor. For reconstructions of a QRM liver phantom with extension ring, the proposed correction pipeline achieved a more uniform and stable outcome in the attenuation values of homogeneous materials within the phantom. For example, the root mean squared deviation between centered and off-centered phantom positioning was reduced from 6.6 to 1.8HU in oneprofile. We have introduced a patient-specific approach for single-material BHC in diagnostic CT via the use of an analytical energy response model. This approach shows promising improvements in terms of robustness of attenuation values for large patient sizes. Our results contribute toward improving CT images so as to make CT attenuation values more reliable for use in clinicalpractice.

Dose length product and outcome of CT fluoroscopy-guided interventions using a new 320-detector row CT scanner with deep-learning reconstruction and new bow-tie filter.

To investigate the dose length product (DLP) and outcomes of CT fluoroscopy (CTF)-guided interventions using a novel 320-detector row CT scanner with deep-learning reconstruction (DLR) and a new bow-tie filter (i.e., Aquilion ONE Prism Edition) and compare with a 320-detector row CT system without DLR and the new bow-tie filter (i.e., Aquilion ONE Vision Edition) (Vision). CTF-guided interventions performed using Prism and Vision were retrospectively investigated in terms of the technical success rates, clinical success rates of biopsies, complications, DLPs of total CT scans (total DLPs) from February 2019 to January 2021. The total CT scans included pre-interventional CT scans, CTF scans during the CTF-guided procedure, additional CT scans for additional treatment, CTF scans for additional treatment, and post-interventional CT scans. In this study, 87 and 85 CTF-guided interventions were performed using Vision (Vision group) and Prism (Prism group), respectively. There was no significant difference in the technical success rate (96.6% vs 98.8%, p = 0.621), clinical success rate of biopsies (92.9% vs 93.4%, p = 1.000), and minor (8.0% vs 7.1%, p = 0.807) and major (0% vs 3.5%, p = 0.119) complications between the Prism and Vision groups. The total DLPs for the Prism group were significantly lower than those for the Vision group regardless of the procedure (278 vs 548 mGy*cm, p < 0.001, in the biopsy and 246 vs 667 mGy*cm, p < 0.001, in the drainage and aspiration). CTF-guided interventions on Prism reduce the total DLP without performance degradation of the intervention. The total DLPs of biopsies and drainages/aspirations in the Prism group decreased by 49 and 63%, respectively.

Investigation of image quality of MV and kV CBCT with low-Z beams and high DQE detector.

To investigate cone beam computed tomography (CBCT) image quality using novel combinations of kilovoltage (kV) and megavoltage (MV) beams and detectormaterials. MV and kV CBCT imaging was simulated using the Fastcat hybrid Monte Carlo application. CBCT imaging with various beam energies was investigated: 2.5 and 6 MV photon beams generated with carbon, aluminum, and tungsten targets and a 120 kVp x-ray tube beam based off of a Varian Truebeam on-board imager (OBI). Cadmium tungstate (CWO), gadolinium oxysulfide (GOS), and cesium iodide (CsI) detectors with identical pixel pitch of 0.784 mm were evaluated. Modulation transfer functions (MTF) for all detector/beam combinations were calculated. MV and kV CBCT images for each detector/beam combination of a contrast phantom containing inserts with rib and spongiosa bone, lung, and adipose tissues were simulated with an imaging dose of 7 mGy. Contrast to noise ratio (CNR) of all inserts were compared for all detector/beam combinations. CBCT images of an anthropomorphic head phantom with silver amalgam fillings were also generated. The CWO/120 kVp beam combination resulted in the highest MTF at low frequencies and the CsI detector showed the highest MTF for all other beams and at high frequencies. The CWO/120 kVp beam combination showed the highest CNR for all tissues. The unoptimized CWO/2.5 MV carbon target beam showed the highest CNR of the MV beam/detector combinations with CNR 4% and 17% worse than the optimized Truebeam CsI 120 kVp setup with a bowtie filter and antiscatter grid. Additionally, the CWO 2.5 MV setup showed qualitative reduction of metal artifacts surrounding silver amalgam fillings in an anthropomorphic headphantom. This finding makes a compelling case that further optimization of this CWO carbon target setup could produce CBCT images with similar CNR to current OBI CBCT for equivalent dose with added resilience to metalartifacts.

Real-time estimation of patient-specific dose distributions for medical CT using the deep dose estimation.

With the rising number of computed tomography (CT) examinations and the trend toward personalized medicine, patient-specific dose estimates are becoming more and more important in CT imaging. However, current approaches are often too slow or too inaccurate to be applied routinely. Therefore, we propose the so-called deep dose estimation (DDE) to provide highly accurate patient dose distributions in real time METHODS: To combine accuracy and computational performance, the DDE algorithm uses a deep convolutional neural network to predict patient dose distributions. To do so, a U-net like architecture is trained to reproduce Monte Carlo simulations from a two-channel input consisting of a CT reconstruction and a first-order dose estimate. Here, the corresponding training data were generated using CT simulations based on 45 whole-body patient scans. For each patient, simulations were performed for different anatomies (pelvis, abdomen, thorax, head), different tube voltages (80kV, 100kV, 120kV), different scan trajectories (circle, spiral), and with and without bowtie filtration and tube current modulation. Similar simulations were performed using a second set of eight whole-body CT scans from the Visual Concept Extraction Challenge in Radiology (Visceral) project to generate testing data. Finally, the DDE algorithm was evaluated with respect to the generalization to different scan parameters and the accuracy of organ dose and effective dose estimates based on an external organsegmentation. DDE dose distributions were quantified in terms of the mean absolute percentage error (MAPE) and a gamma analysis with respect to the ground truth Monte Carlo simulation. Both measures indicate that DDE generalizes well to different scan parameters and different anatomical regions with a maximum MAPE of 6.3% and a minimum gamma passing rate of 91%. Evaluating the organ dose values for all organs listed in the International Commission on Radiological Protection (ICRP) recommendation, shows an average error of 3.1% and maximum error of 7.2% (bone surface). The DDE algorithm provides an efficient approach to determine highly accurate dose distributions. Being able to process a whole-body CT scan in about 1.5s, it provides a valuable alternative to Monte Carlo simulations on a graphics processing unit (GPU). Here, the main advantage of DDE is that it can be used on top of any existing Monte Carlo code such that real-time performance can be achieved without major adjustments. Thus, DDE opens up new options not only for dosimetry but also for scan and protocoloptimization.

An Easy-to-use Method for CT Image Simulation with Parameter Optimization Using a Water Phantom

We developed an easy-to-use method to generate computed tomography (CT) images that simulate the images obtained when using an actual scanner. The developed method generates images by simulating the data acquisition and image reconstruction processes of a scanner from a linear attenuation coefficient map of an object numerically generated. This approach is similar to general image simulation methods. However, we introduced adjustable parameters for the CT data acquisition process, for example, parameters related to X-ray attenuation in the anode of the X-ray tube and the bowtie filter. These parameters were optimized in advance by minimizing the difference between the simulated and measured images of a water phantom. To verify the validity of the developed method, a simulated image was generated for a torso phantom and then compared with the measured image of the phantom obtained using the scanner. The simulated and measured images of the torso phantom were in good agreement. The spatial resolution and noise characteristics of these two images were also comparable, further indicating the accuracy of the developed method. In the existing methods, various information/data related to an actual scanner, including difficult-to-acquire ones, were essential for image simulation. In the developed method, instead of determining the difficult-to-acquire information/data, we introduced adjustable parameters. Therefore, the developed method was easier to use than the existing methods.

A comprehensive Monte Carlo study of CT dose metrics proposed by the AAPM Reports 111 and 200.

A Monte Carlo (MC) modeling of single axial and helical CT scan modes has been developed to compute single and accumulated dose distributions. The radiation emission characteristics of an MDCT scanner has been modeled and used to evaluate the dose deposition in infinitely long head and body PMMA phantoms. The simulated accumulated dose distributions determined the approach to equilibrium function, H(L). From these curves, dose-related information was calculated for different head and body clinical protocols. The PENELOPE/penEasy package has been used to model the single axial and helical procedures and the radiation transport of photons and electrons in the phantoms. The bowtie filters, heel effect, focal-spot angle, and fan-beam geometry were incorporated. Head and body protocols with different pitch values were modeled for x-ray spectra corresponding to 80, 100, 120, and 140kV. The analytical formulation for the single dose distributions and experimental measurements of single and accumulated dose distributions were employed to validate the MC results. The experimental dose distributions were measured with OSLDs and a thimble ion chamber inserted into PMMA phantoms. Also, the experimental values of the along the center and peripheral axes of the CTDI phantom served to calibrate the simulated single and accumulated dose distributions. The match of the simulated dose distributions with the reference data supports the correct modeling of the heel effect and the radiation transport in the phantom material reflected in the tails of the dose distributions. The validation of the x-ray source model was done comparing the CTDI ratios between simulated, measured and CTDosimetry data. The average difference of these ratios for head and body protocols between the simulated and measured data was in the range of 13-17% and between simulated and CTDosimetry data varied 10-13%. The distributions of simulated doses and those measured with the thimble ion chamber are compatible within 3%. In this study, it was demonstrated that the efficiencies of the measurements in head phantoms with nT=20mm and 120kV are 80.6% and 87.8% at central and peripheral axes, respectively. In the body phantoms with =40mm and 120kV, the efficiencies are 56.5% and 86.2% at central and peripheral axes, respectively. In general terms, the clinical parameters such as pitch, beam intensity, and voltage affect the Deq values with the increase of the pitch decreasing the Deq and the beam intensity and the voltage increasing its value. The H(L) function does not change with the pitch values, but depends on the phantom axis (central or peripheral). The computation of the pitch-equilibrium dose product, , evidenced the limitations of the method to determine the dose delivered by a CT scanner. Therefore, quantities derived from the propagate this limitation. The developed MC model shows excellent compatibility with both measurements and literature quantities defined by AAPM Reports 111 and 200. These results demonstrate the robustness and versatility of the proposed modeling method.

Validation of a deterministic linear Boltzmann transport equation solver for rapid CT dose computation using physical dose measurements in pediatric phantoms.

The risk of inducing cancer to patients undergoing CT examinations has motivated efforts for CT dose estimation, monitoring, and reduction, especially among pediatric population. The method investigated in this study is Acuros CTD (Varian Medical Systems, Palo Alto, CA), a deterministic linear Boltzmann transport equation (LBTE) solver aimed at generating rapid and reliable dose maps of CT exams. By applying organ contours, organ doses can also be obtained, thus patient-specific organ dose estimates can be provided. This study experimentally validated Acuros against measurements performed on a clinical CT system using a range of physical pediatric anthropomorphic phantoms and acquisition protocols. The study consisted of (1) the acquisition of dose measurements on a clinical CT scanner through thermoluminescent dosimeters (TLDs), and (2) the modeling in the Acuros platform of the measurement set up, which includes the modeling of the CT scanner and of the anthropomorphic phantoms. For the measurements, 1-year-old, 5-year-old, and 10-year-old anthropomorphic phantoms of the CIRS ATOM family were used. TLDs were placed in selected organ locations such as stomach, liver, lungs, and heart. The pediatric phantoms were scanned helically with the GE Discovery 750 HD clinical scanner for several examination protocols. For the simulations in Acuros, scanner-specific input, such as bowtie filters, overrange collimation, and tube current modulation schemes, were modeled. These scanner complexities were implemented by defining discretized X-ray beams whose spectral distribution, defined in Acuros by only six energy bins, varied across fan angle, cone angle, and slice position. The images generated during the CT acquisitions were used to create the geometrical models, by applying thresholding algorithms and assigning materials to the HU values. The TLDs were contoured in the phantom models as sensitive cylindrical volumes at the locations selected for dosimeters placement, to provide dose estimates, in terms of dose per unit photon. To compare measured doses with dose estimates, a calibration factor was derived from the CTDIvol displayed by the scanner, to account for the number of photons emitted by the X-ray tube during the procedure. The differences of the measured and estimated doses, in terms of absolute % errors, were within 13% for 153 TLD locations, with an error of 17% at the stomach for one study with the 10-year-old phantom. Root-mean-squared-errors (RMSE) across all TLD locations for all configurations were in the range of 3%-8%, with Acuros providing dose estimates in a time range of a few seconds up to 2 min. An overall good agreement between measurements and simulations was achieved, with average RMSE of 6% across all cases. The results demonstrate that Acuros can model a specific clinical scanner despite the required discretization in spatial and energy domains. The proposed deterministic tool has the potential to be part of a near real-time individualized dosimetry monitoring system for CT applications, providing patient-specific organ dose estimates.

Use of Tin Filters in Cone Beam CT of Head Region for Streak Artifact Reduction: Phantom Study

<h3>Purpose/Objective(s)</h3> This study attempts to reduce streak artifacts in cone-beam computed tomography (CBCT), which are primarily caused by high-density materials, by mounting tin filters. <h3>Materials/Methods</h3> We utilized four thicknesses of tin filters, such as default (no tins), 0.2 mm, 0.4 mm, and 0.6 mm, in front of the designated full fan bow-tie filter. The scanning protocol included both standard dose head (SDH) and high-quality head (HQH) protocols to evaluate the compensation for the reduction of low-energy photons in SDH protocol. To evaluate the degree of streak artifact reductions, an anthropomorphic phantom with insertions of aluminum and titanium plugs was scanned with above eight protocols. The percent integrity uniformity (PIU) and coefficient of fast Fourier transform (FFT) of a circumference that was twice the rod radius were evaluated. Images of a Catphan 504 phantom were analyzed in terms of noise levels, integral non-uniformities, contrast-to-noise ratios, and low-contrast visibilities. To evaluate the accompanying imaging doses, weighted CT dose indices and point doses using optically stimulated luminescence dosimeters were obtained. <h3>Results</h3> When 0.2 mm, 0.4 mm, and 0.6 mm thickness tin filters were mounted, the average PIUs increased by 13.4%, 18.9%, and 17.8% and by 35.7%, 53.0%, and 72.5% in the vicinity of aluminum and titanium, respectively. Similarly, the coefficients of lower-quarter FFTs changed by -5.2%, -11.5%, and -13.5% and by -0.7%, 2.7%, and -3.6% in the vicinity of aluminum and of titanium, respectively. The other image qualities such as noise levels, integral non-uniformities, contrast-to-noise ratios, and low-contrast visibilities were degraded as thicker tin filters were mounted, although the degree varied. By mounting 0.2 mm, 0.4 mm, and 0.6 mm tin filters, 69.4%, 84.7%, and 92.0% reductions in CT dose index and 52.7%, 70.4%, and 78.2% reductions in average point doses were obtained. <h3>Conclusion</h3> In this phantom study, attachment of a 0.4 mm tin filter with HQH protocols could effectively reduce streak artifacts without degradation of other image quality indices. In addition, the accompanied imaging doses did not increase.

Experimental validation of Fastcat kV and MV cone beam CT (CBCT) simulator.

To experimentally validate the Fastcat cone beam computed tomography (CBCT) simulator against kV and MV CBCT images acquired with a Varian Truebeamlinac. kV and MV CBCT images of a Catphan 504 phantom were acquired using a 100 kVp beam with the on-board imager (OBI) and a 6 MV treatment beam with the electronic portal imaging device (EPID), respectively. The kV Fastcat simulation was performed using detailed models of the x-ray source, bowtie filter, a high resolution voxelized virtual Catphan phantom, anti-scatter grid, and the CsI scintillating detector. Likewise, an MV Fastcat CBCT was simulated with detailed models for the beam energy spectrum, flattening filter, a high-resolution voxelized virtual Catphan phantom, and the gadolinium oxysulfide (GOS) scintillating detector. Experimental and simulated CBCT images of the phantom were compared with respect to HU values, contrast to noise ratio (CNR), and dose linearity. Detector modulation transfer function (MTF) for the two detectors were also experimentally validated. Fastcat's dose calculations were compared to Monte Carlo (MC) dose calculations performed with Topas. For the kV and MV simulations, respectively: Contrast agreed within 14 and 9 HUs and detector MTF agreed within 4.2% and 2.5%. Likewise, CNR had a root mean squared error (RMSE) of 2.6% and 1.4%. Dose agreed within 2.4% and 1.6% of MC values. The kV and MV CBCT images took 71 and 72 s to simulate in Fastcat with 887 and 493 projections, respectively. We present a multienergy experimental validation of a fast and accurate CBCT simulator against a commercial linac. The simulator is open source and all models found in this work can be downloaded from https://github.com/jerichooconnell/fastcat.git.

Effect of computed tomography value error on dose calculation in adaptive radiotherapy with Elekta X-ray volume imaging cone beam computed tomography.

PurposeWe evaluated the effect of changing the scan mode of the Elekta X‐ray volume imaging cone beam computed tomography (CBCT) on the accuracy of dose calculation, which may be affected by computed tomography (CT) value errors in three dimensions.MethodsWe used the electron density phantom and measured the CT values in three dimensions. CT values were compared with planning computed tomography (pCT) values for various materials. The evaluated scan modes were for head and neck (S‐scan), chest (M‐scan), and pelvis (L‐scan) with various collimators and filter systems. To evaluate the effects of the CT value error of the CBCT on dose error, Monte Carlo calculations of dosimetry were performed using pCT and CBCT images.ResultsThe L‐scan had a CT value error of approximately 800 HU at the isocenter compared with the pCT. Furthermore, inhomogeneity in the longitudinal CT value profile was observed in the bone material. The dose error for ±100 HU difference in CT values for the S‐scan and M‐scan was within ±2%. The center of the L‐scan had a CT error of approximately 800 HU and a dose error of approximately 6%. The dose error of the L‐scan occurred in the beam path in the case of both single field and two parallel opposed fields, and the maximum error occurred at the center of the phantom in the case of both the 4‐field box and single‐arc techniques.ConclusionsWe demonstrated the three‐dimensional CT value characteristics of the CBCT by evaluating the CT value error obtained under various imaging conditions. It was found that the L‐scan is considerably affected by not having a unique bowtie filter, and the S‐scan without the bowtie filter causes CT value errors in the longitudinal direction. Moreover, the CBCT dose errors for the 4‐field box and single‐arc irradiation techniques converge to the isocenter.

Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT

Spectral CT utilizes spectral information of X-ray sources to reconstruct energy-resolved X-ray images and has wide medical applications. Compared with conventional energy-integrated CT scanners, however, spectral CT faces serious technical difficulties in hardware, and hence its clinical use has been expensive and limited. The goal of this paper is to present a software solution and an implementation of a framelet-based spectral reconstruction algorithm for multi-slice spiral scanning based on a conventional energy-integrated CT hardware platform. In the present work, we implement the framelet-based spectral reconstruction algorithm using compute unified device architecture (CUDA) with bowtie filtration. The platform CUDA enables fast execution of the program, while the bowtie filter reduces radiation exposure. We also adopt an order-subset technique to accelerate the convergence. The multi-slice spiral scanning geometry with these additional features will make the framelet-based spectral reconstruction algorithm more powerful for clinical applications. The method provides spectral information from just one scan with a standard energy-integrating detector and produces color CT images, spectral curves of the attenuation coefficient at every point inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. The proposed algorithm is tested with a Catphan phantom and real patient data sets for its performance. In experiments with the Catphan 504 phantom, the synthesized color image reveals changes in the level of colors and details and the yellow color in Teflon indicates a special spectral property which is invisible in regular CT reconstruction. In experiments with clinical images, the synthesized color images provide some extra details which are helpful for clinical diagnosis, for example, details about the renal pelvis and lumbar join. The numerical studies indicate that the proposed method provides spectral image information which can reveal fine structures in clinical images and that the algorithm is efficient regarding to the computational time. Thus, the proposed algorithm has a great potential in practical application.

On the potential of ROI imaging in x-ray CT - A comparison of novel dynamic beam attenuators with current technology.

In this work, we explore the potential of region-of-interest (ROI) imaging in x-ray computed tomography (CT). Using two dynamic beam attenuator (DBA) concepts for fluence field modulation (FFM) previously developed, we investigate and evaluate the potential dose savings in comparison with current FFM technology. ROI imaging is a special application of FFM where the bulk of x-ray radiation is propagated toward a certain anatomical target (ROI), specified by the imaging task, while the surrounding tissue is spared from radiation. We introduce a criterion suitable to quantitatively describe the balance between image quality inside an ROI and total radiation dose with respect to a given ROI imaging task. It accounts for the mean image variance at the ROI and the effective patient dose calculated from Monte Carlosimulations. The criterion is further used to compile task-specific DBA trajectories determining the primary x-ray fluence, and eventually used for comparing different FFM techniques, namely the sheet-based dynamic beam attenuator(sbDBA), the z-aligned sbDBA(z-sbDBA), and an adjustable static operation mode of the z-sbDBA. Furthermore, two static bowtie filters and the influence of tube current modulation (TCM) are included in the comparison. Our findings demonstrate by simulations that the presented trajectory optimization method determines reasonable DBA trajectories. The influence of TCM is strongly depending on the imaging task. The narrow bowtie filter allows for dose reductions of about 10% compared to the regular bowtie filter in the considered ROI imaging tasks. The DBAs are shown to realize substantially larger dose reductions. In our cardiac imaging scenario, the DBAs can reduce the effective dose by about 30% (z-sbDBA) or 60% (sbDBA). We can further verify that the noise characteristics are not adversely affected by the DBAs. Our research demonstrates that ROI imaging using the presented DBA concepts is a promising technique toward a more patient- and task-specific CT imaging requiring lower radiation dose. Both the sbDBA and the z-sbDBA are potential technical solutions for realizing ROI imaging in x-ray CT.

PATIENT-SPECIFIC DOSE ESTIMATES IN DYNAMIC COMPUTED TOMOGRAPHY MYOCARDIAL PERFUSION EXAMINATION.

The study aimed to implement realistic source models of a computed tomography (CT) scanner and Monte Carlo simulations to actual patient data and to calculate patient-specific organ and effective dose estimates for patients undergoing dynamic CT myocardial perfusion examinations. Source models including bowtie filter, tube output and x-ray spectra were determined for a dual-source Siemens Somatom Definition Flash scanner. Twenty CT angiography patient datasets were merged with a scaled International Commission on Radiological Protection (ICRP) 110 voxel phantom. Dose simulations were conducted with ImpactMC software. Effective dose estimates varied from 5.0 to 14.6 mSv for the 80 kV spectrum and from 8.9 to 24.7 mSv for the 100 kV spectrum. Significant differences in organ doses and effective doses between patients emphasise the need to use actual patient data merged with matched anthropomorphic anatomy in the dose simulations to achieve a reasonable level of accuracy in the dose estimation procedure.

Usability assessment of cone beam computed tomography with a full-fan mode bowtie filter compared to that with a half-fan mode bowtie filter

Usability assessment of cone beam computed tomography with a full-fan mode bowtie filter compared to that with a half-fan mode bowtie filter

Could a virtual bowtie filter improve image quality? A breast simulation study

ABSTRACT Introduction: During CT scanning, anatomical shapes and body contours cause variation in the transmitted x-ray intensity reaching the detector. This can compromise image quality since the detector has a limited dynamic range. In principle, suitable bowtie filters can reduce transmitted X-rays through thinner parts of the body so that it is uniform at the detector surface.Aim: This study explores the possibility of using mathematical data modelling of transmission data to act as a virtual bowtie filter. The virtual filter is applied after the acquisition of projection data and can be based on body shape. In this study, the virtual bowtie filter is constructed from breast contour information and applied to transmitted x-ray beam profiles produced in egs_cbct Monte Carlo simulations.Methods and materials: The Breastsimulator software was used to generate suitable breast phantoms. Egs_cbct simulated X-ray transport through these phantoms. One simulation included a bowtie filter that accounted for breast shape as a control. Projection images were acquired over 360 degrees without the bowtie filter. We designed a bowtie filter and corrected the transmitted X-ray profiles based on its shape.Results: Image contrast indicated any improvement in image quality. Results indicated that using a virtual bowtie correction method improved image quality as well as a reduction in cupping artefacts.Conclusion: It is a useful method to improve the image quality without the need to incorporate a real bowtie filter during measurements.

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

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. 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 140kVp 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. For the 21.4-cm diameter phantom, NSP and SPR increase linearly with collimator opening for both tube potentials, with the 90kVp 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 32cm, 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. 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.

Reference dataset for benchmarking fetal doses derived from Monte Carlo simulations of CT exams.

Task Group Report 195 of the American Association of Physicists in Medicine contains reference datasets for the direct comparison of results among different Monte Carlo (MC) simulation tools for various aspects of imaging research that employs ionizing radiation. While useful for comparing and validating MC codes, that effort did not provide the information needed to compare absolute dose estimates from CT exams. Therefore, the purpose of this work is to extend those efforts by providing a reference dataset for benchmarking fetal dose derived from MC simulations of clinical CT exams. The reference dataset contains the four necessary elements for validating MC engines for CT dosimetry: (a) physical characteristics of the CT scanner, (b) patient information, (c) exam specifications, and (d) fetal dose results from previously validated and published MC simulations methods in tabular form. Scanner characteristics include non-proprietary descriptions of equivalent source cumulative distribution function (CDF) spectra and bowtie filtration profiles, as well as scanner geometry information. Additionally, for the MCNPX MC engine, normalization factors are provided to convert raw simulation results to absolute dose in mGy. The patient information is based on a set of publicly available fetal dose models and includes de-identified image data; voxelized MC input files with fetus, uterus, and gestational sac identified; and patient size metrics in the form of water equivalent diameter (Dw ) z-axis distributions from a simulated topogram (Dw,topo ) and from the image data (Dw,image ). Exam characteristics include CT scan start and stop angles and table and patient locations, helical pitch, nominal collimation and measured beam width, and gantry rotation time for each simulation. For simulations involving estimating doses from exams using tube current modulation (TCM), a realistic TCM scheme is presented that is estimated based upon a validated method. (d) Absolute and CTDIvol -normalized fetal dose results for both TCM and FTC simulations are given for each patient model under each scan scenario. Equivalent source CDFs and bowtie filtration profiles are available in text files. Image data are available in DICOM format. Voxelized models are represented by a header followed by a list of integers in a text file representing a three-dimensional model of the patient. Size distribution metrics are also given in text files. Results of absolute and normalized fetal dose with associated MC error estimates are presented in tabular form in an Excel spreadsheet. All data are stored on Zenodo and are publicly accessible using the following link: https://zenodo.org/record/3959512. Similar to the work of AAPM Report 195, this work provides a set of reference data for benchmarking fetal dose estimates from clinical CT exams. This provides researchers with an opportunity to compare MC simulation results to a set of published reference data as part of their efforts to validate absolute and normalized fetal dose estimates. This could also be used as a basis for comparison to other non-MC approaches, such as deterministic approaches, or to commercial packages that provide estimates of fetal doses from clinical CT exams.

Accuracy of weighted CTDI in estimating average dose delivered to CTDI phantoms: An experimental study.

The concept of the weighted computed tomography dose index ( ) was proposed in 1995 to represent the average CTDI across an axial section of a cylindrical phantom. The purpose of this work was to experimentally re-examine the validity of the underlying assumptions behind for modern MDCT systems. To enable experimental mapping of in the axial plane, in-house 16 and 32cm cylindrical phantoms were fabricated to allow the pencil chamber to reach any arbitrary axial location within the phantoms. The phantoms were scanned on a clinical MDCT with five beam collimation widths, three bowtie filters, and four kV levels. To evaluate the linearity and rotational invariance assumptions implicitly made when the weighting factors of 1/3 and 2/3 in the formula were originally derived, was measured at different radial and angular locations within the phantom for different collimation, bowtie, and kV combinations. The average CTDI ( ) across the axial plane was calculated from the experimental two-dimensional (2D) dose distribution and was compared with the traditional . For both phantoms under all scan conditions, the axial dose distributions were found to have significant angular dependence, potentially due to the x-ray attenuation by the patient couch or the head holder. The radial dose profiles were also found to significantly deviate from linearity in many cases due to the presence of the bowtie filter. When only the 12 o'clock peripheral and the traditional weighting factors were used to calculate , the average dose was overestimated in the 16cm phantom by up to 8.4% at isocenter and up to 35.3% when the phantom was off-centered by 6cm; in the 32cm phantom at isocenter, the average dose was overestimated by up to 12.8%. Using an average of the four peripheral measurements at the 12, 3, 6, and 9 o'clock locations reduced the error of to within 1.2% in the 16cm phantom. For the 32cm phantom, even by using the average of the peripheral measurements, the traditional underestimated the average dose by up to 4.3% due to aggressive drop-off of the at the phantom periphery. The linearity and rotational-invariance assumptions behind the traditional formalism may not be valid for modern CT systems and thus may not accurately represent the average dose or radiation output within a CTDI phantom. Utilizing data from all four peripheral locations always improves accuracy of in representing the true average dose. For the large (32cm) phantom, nonlinear models and more measurement points are needed if a more precise estimation of the average axial dose is required.