Mathematical modelling of scanner-specific bowtie filters for Monte Carlo CT dosimetry

Influence of X-ray spectrum and bowtie filter characterisation on the accuracy of Monte Carlo simulated organ doses: Validation in a whole-body CT scanning mode

PURPOSE

For patient-specific CT dosimetry, Monte Carlo dose simulations require an accurate description of the CT scanner. However, quantitative spectral information and information on the bowtie filter material and shape from the manufacturer is often not available. In this study, the influence of different X-ray spectra and bowtie filter characterisation methods on simulated CT organ doses is studied.

METHODS

Using ImpactMC, organ doses of whole-body CTs were simulated in twenty adult whole-body voxel models, generated from PET/CT examinations previously conducted in these patients. Simulated CT organ doses based on the manufacturer X-ray spectra and bowtie filter data were compared with those obtained using alternative characterisation models, including spectrum generators and experimentally measured dose data. A total of four different X-ray spectra and one bowtie filter model were defined based on these data.

RESULTS

For all X-ray spectra and bowtie filter combinations, estimated CT organ doses are within 6% from those resulting from simulations with the CT characterisation models provided by the manufacturer. While varying the bowtie filter model results in CT organ dose differences smaller than 1%, dose differences up to 6% are observed when X-ray spectra are not based on the quantitative data from the manufacturer.

CONCLUSIONS

Estimated organ doses slightly depend on the applied CT characterisation model. When manufacturer's data are not available, half-value layer and dose measurements provide sufficient input to obtain equivalent X-ray spectra and bowtie filter profiles, respectively.

Effect of technologist and patient attributes on centering for body CT examinations: Influence of cultural and ethnic factors

There are no published data on the effect of patient and technologist gender and ethnicity attributes on off-centering in CT. Therefore, we assessed the impact of patient and technologist variations on off-centering patients undergoing body CT. With institutional review board approval, our retrospective study included 1000 consecutive adult patients (age ranged 22–96 years; 756 males: 244 females) who underwent chest or abdomen CT examinations. We recorded patient (age, gender, nationality, body weight, height,), technologist gender, and scan-related (scanner vendor, body region imaged, scan length, CT dose index volume, dose length product) information. Lateral and anteroposterior (AP) diameters were recorded to calculate effective diameter and size-specific dose estimate (SSDE). Off-centering represented the distance between the anterior-posterior centers of the scan field of view and the patient at the level of carina (for chest CT) and iliac crest (for abdomen CT). About 76% of the patients (760/1000) were off-centered with greater off-centering for chest (22 mm) than for abdomen (15 mm). Although ethnicity or patient gender was not a significant determinant of off-centering, technologist-patient gender mismatch was associated with a significantly greater frequency of off-centering (p<0.001). Off-centering below the gantry isocenter was twice as common as off-centering above the gantry isocenter (p<0.001). The latter occurred more frequently in larger patients and was associated with higher radiation doses than those centered below the isocenter (p<0.001). Technologists’ years of experience and patient factors profoundly affect the presence and extent of off-centering for both chest and abdomen CTs. Larger patients are more often off-centered than smaller patients.

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.

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

PURPOSE

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 H ( L ) curves, dose-related information was calculated for different head and body clinical protocols.

METHODS

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 140 kV. 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 C T D I 100 along the center and peripheral axes of the CTDI phantom served to calibrate the simulated single and accumulated dose distributions.

RESULTS

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 C T D I 100 measurements in head phantoms with nT = 20 mm and 120 kV are 80.6% and 87.8% at central and peripheral axes, respectively. In the body phantoms with n T = 40 mm and 120 kV, 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 D_eq values with the increase of the pitch decreasing the D_eq 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).

CONCLUSIONS

The computation of the pitch-equilibrium dose product, D ̂ eq , evidenced the limitations of the C T D I 100 method to determine the dose delivered by a CT scanner. Therefore, quantities derived from the C T D I 100 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.

A Monte Carlo Platform for Characterization of X-Ray Radiation Dose in CT Imaging

Background

Computed tomography (CT) is currently known as a versatile imaging tool in the clinic used for almost all types of cancers. The major issue of CT is the health risk, belonging to X-ray radiation exposure. Concerning this, Monte Carlo (MC) simulation is recognized as a key computational technique for estimating and optimizing radiation dose. CT simulation with MCNP/MCNPX MC code has an inherent problem due to the lack of a fan-beam shaped source model. This limitation increases the run time and highly decreases the number of photons passing the body or phantom. Recently, a beta version of MCNP code called MCNP-FBSM (Fan-Beam Source Model) has been developed to pave the simulation way of CT imaging procedure, removing the need of the collimator. This is a new code, which needs to be validated in all aspects.

Objective

In this work, we aimed to develop and validate an efficient computational platform based on modified MCNP-FBSM for CT dosimetry purposes.

Material and Methods

In this experimental study, a setup is carried out to measure CTDI₁₀₀ in air and standard dosimetry phantoms. The accuracy of the developed MC CT simulator results has been widely benchmarked through comparison with our measured data, UK's National Health Service's reports (known as ImPACT), manufacturer's data, and other published results.

Results

The minimum and maximum observed mean differences of our simulation results and other above-mentioned data were the 1.5%, and 9.79%, respectively.

Conclusion

The developed FBSM MC computational platform is a beneficial tool for CT dosimetry.

Design of a Monte Carlo model based on dual-source computed tomography (DSCT) scanners for dose and image quality assessment using the Monte Carlo N-Particle (MCNP5) code

The purpose of this work was to develop and validate a Monte Carlo model for a Dual Source Computed Tomography (DSCT) scanner based on the Monte Carlo N-particle radiation transport computer code (MCNP5). The geometry of the Siemens Somatom Definition CT scanner was modeled, taking into consideration the x-ray spectrum, bowtie filter, collimator, and detector system. The accuracy of the simulation from the dosimetry point of view was tested by calculating the Computed Tomography Dose Index (CTDI) values. Furthermore, typical quality assurance phantoms were modeled in order to assess the imaging aspects of the simulation. Simulated projection data were processed, using the MATLAB software, in order to reconstruct slices, using a Filtered Back Projection algorithm. CTDI, image noise, CT-number linearity, spatial and low contrast resolution were calculated using the simulated test phantoms. The results were compared using several published values including IMPACT, NIST and actual measurements. Bowtie filter shapes are in agreement with those theoretically expected. Results show that low contrast and spatial resolution are comparable with expected ones, taking into consideration the relatively limited number of events used for the simulation. The differences between simulated and nominal CT-number values were small. The present attempt to simulate a DSCT scanner could provide a powerful tool for dose assessment and support the training of clinical scientists in the imaging performance characteristics of Computed Tomography scanners.