Virtual Phantom Research Articles

MONTE CARLO ANALYSIS OF FETAL DOSE DISTRIBUTION IN PREGNANCY FOR DIFFERENT FETAL AGES, BEAM LOCATION, BEAM ENERGY, AND FIELD SIZES

Treatment with radiotherapy in pregnant women may occur due to some critical conditions. The dose given during the treatment process is not only received by the patient but can also be absorbed by the fetus which can affect its growth. Moreover, the radiation target is near the fetus such as the lung. This study aims to determine the dose distribution to the fetus with variations in fetal age (trimester 1, 2, and 3), beam energy, field size, and fetal distance to the target location (lung). The entire simulation utilized the Monte Carlo-based software EGSnrc-DOSXYZnrc which produced a 3-dimensional dose distribution on the virtual phantom. The simulated virtual phantom is a box with a size of 40×40×40 cm3 containing several materials, namely water, tissue, and lung. The size of the fetus is varied according to trimesters 1, 2, and 3. The beam is in the form of monoenergetic photons with energies of 3 MeV and 5 MeV emitted from above with a source to surface distance (SSD) of 48 cm. The field size was set at 5×5 cm2 and 8×8 cm2 on the phantom surface. The beam axis was located at a distance of 5 cm and 3 cm from the fetus. The results showed that the four variations performed affected the fetal dose, where the fetal dose increased considerably when the field size was enlarged and the beam axis was closer to the fetal position. The increase in fetal dose is also influenced by the increase in fetal age and beam energy. Meanwhile, the location of the beam below the lung causes an increased dose to the fetus due to the closer position of the beam to the fetus.

A simple algorithm to derive virtual non-contrast electron density from dual-energy computed tomography data for radiotherapy treatment planning.

The use of iodinated contrast-enhancing agents in computed tomography (CT) improves the visualization of relevant structures for radiotherapy treatment planning (RTP). However, it can lead to dose calculation errors by incorrectly converting a CT number to electron density. This study aimed to propose an algorithm for deriving virtual non-contrast (VNC) electron density from dual-energy CT (DECT) data. This algorithm was developed by extending the formula previously developed by Saito, which enables the calculation of the electron density of human tissue through weighted subtraction of CT numbers acquired from DECT scans. To investigate the feasibility of the proposed VNC algorithm, we performed analytical DECT image simulations at 90 and 150kV/Sn on virtual phantoms consisting of various tissue/iodine surrogates with known mass densities and elemental compositions. Two different shapes of phantoms made of water-mimicking surrogates were generated as inputs: a circular phantom (33cm diameter) for calibration and an elliptical phantom (33cm width and 28cm height) for validation. The circular phantom was equipped with inserts of human-tissue-mimicking substitutes, pure water, and iodine-enhanced soft-tissue substitutes (2, 5, 10, and 15mg/mL iodine). The elliptical phantom contained inserts of reference human tissues, iodine-enhanced soft-tissue substitutes (2, 2.5, 5, 7.5, 10, 15, and 20mg/mL iodine), and a 10-mm-diameter core of 4mg/mL iodine surrounded by a blood-mimicking base material. The performance of the proposed algorithm was evaluated by comparing the accuracy of VNC electron densities with those of non-contrast (NC) base materials (water- or blood-mimicking surrogates). The derived algorithm enabled the calculation of VNC electron density in a manner similar to that of unenhanced human tissues by adapting a VNC-specific weighting factor, thereby eliminating the intermediate step of converting CT numbers to electron density. The simulated results showed that the VNC algorithm could almost completely remove the contrast in the electron density image between iodine-enhanced and base materials. The relative deviations of simulated VNC electron density values from the corresponding pre-contrast value were within±0.4% for all tested materials, with a root-mean-square error (RMSE) of 0.2%. Within the limits of the analytical DECT image simulation used in this study, the simple VNC algorithm could effectively provide accurate VNC electron densities for iodine-enhanced materials. This may allow the contrast agent to be used for CT scans during RTP without compromising dose calculation accuracy.

A preliminary study of linear accelerator-based spatially fractionated radiotherapy.

This study aimed to provide quantitative information for implementing Lattice radiotherapy (LRT) using a medical linear accelerator equipped with the Millennium 120 multi-leaf collimator (MLC). The research systematically evaluated the impact of varying vertex diameters and separations on dose distribution, peak-to-valley dose ratio (PVDR), and normal tissue dose. A cylindrical Virtual Water™ phantom was used to create LRT treatments using the Eclipse version 16.0 treatment planning system (Varian, Palo Alto, USA). The plans were optimized employing a 3 × 3 × 3 lattice structure with vertex diameters ranging from 0.5 to 2.0cm and separations from 1.0 to 5.0cm. The prescribed dose was 20.0 Gy to 50% of the vertex volume in a single fraction. Peak-to-valley dose ratio (PVDR) was calculated along three orthogonal axes, and normal tissue dose and monitor units (MU) were analyzed. Additionally, the modulation complexity score (MCS) was calculated for each plan to quantitatively assess treatment plan complexity. The PVDR analysis demonstrated heterogeneous dose distribution, with optimal values below 30% in all directions for 5.0cm separation. PVDR in the superior-inferior direction was consistently lower than in other directions. Normal tissue dose analysis revealed increasing mean dose with larger diameters and separations, while the volume receiving high doses decreased. MU analysis showed significant contributions from collimator angles of 315.0° and 45.0°. MCS values ranged from 0.02 to 0.17 for 0.5cm vertex diameter and 0.08 to 0.20 for larger diameters (1.0-2.0cm) across different separations, respectively. This study demonstrates the technical feasibility of implementing LRT using a medical linear accelerator with Millennium 120 MLC. The findings provide insights into optimizing LRT treatment plans, offering a comprehensive quantitative reference for achieving desired dose heterogeneity while maintaining normal tissue protection.

Use of a virtual phantom to assess the capability of a treatment planning system to perform magnetic resonance image distortion correction.

Treatment Planning Systems (TPS) offer algorithms for distortion correction (DC) of Magnetic Resonance (MR) images, whose performances demand proper evaluation. This work develops a procedure using a virtual phantom to quantitatively assess a TPS DC algorithm. Variations of the digital Brainweb MR study were created by introducing known distortions and Control Points (CPs). A synthetic Computed Tomography (sCT) study was created based upon the MR study. Elements TPS (Brainlab, Munich, Germany) was used to apply DC to the MR images, choosing the sCT as the gold standard. Deviations in the CP locations between the original images, the distorted images and the corrected images were calculated. Structural Similarity Metric (SSIM) tests were applied for further assessment of image corrections. The introduced distortion deviated the CP locations by a median (range) value of 1.8 (0.2-4.4) mm. After DC was applied, these values were reduced to 0.6 (0.1-1.9) mm. Correction of the original image deviated the CP locations by 0.2 (0-1.1) mm. The SSIM comparisons between the original and the distorted images yielded values of 0.23 and 0.67 before and after DC, respectively. The SSIM comparison of the original study, before and after DC, yielded a value of 0.97. The proposed methodology using a virtual phantom with CPs can be used to assess a TPS DC algorithm. Elements TPS effectively reduced MR distorsions below radiosurgery tolerances.

Influence of spatial redistribution of heterogeneities in proton beam characteristics.

The purpose of this study was to investigate the fundamental properties of spot-scanning proton beams and compare them to Monte Carlo (MC) simulations, both with and without CT calibration, using spatially diverse combinations of materials. A heterogeneous phantom was created by spatially distributing titanium, wax, and thermocol to generate six scenarios of heterogeneous combinations. Proton pencil beams ranging in energy from 100 to 226.2MeV were directed perpendicular to each heterogeneous combination, and the exit proton was measured using a Lynx scintillation detector and a Zebra Multi-Layer-Ionization-Chamber for depth dose and spot profile measurements, respectively. The identical measurement configuration was duplicated in the RayStation-TPS. The measured and simulated RayStation-MC beam characteristics were compared. The results showed that at 100MeV, the mean standard deviation of spot size was 5.66±0.27mm, while at 226.2MeV, it rapidly decreased to 3.37±0.07mm. The physical phantom showed a larger perturbation difference between measurement and MC simulation than the virtual phantom. MC overestimates ranges up to 1.5% in virtual phantoms, but underestimates ranges up to 5% in physical phantoms. Range perturbations over 1mm occurred in 35.7% of virtual phantom measurements and in 85.7% of physical phantom measurements. Despite using a CT artefact reduction approach and an accurate Monte-Carlo dose calculation algorithm, perturbations in proton characteristics were still observed. It is essential to be aware of the limits of the TPS in managing such heterogeneous combinations. It is recommended to perform more validation checks on heterogeneous combinations than on individual materials.

Quantification of uncertainties in reference and relative dose measurements, dose calculations, and patient setup in modern external beam radiotherapy.

Uncertainties in the steps of external beam radiotherapy (EBRT) affect patient outcomes. However, few studies have investigated major contributors to these uncertainties. This study investigated factors contributing to reducing uncertainty in delivering a dose to a target volume. The EBRT process was classified into four steps: reference dosimetry, relative dosimetry [percentage depth doses (PDDs) and off-center ratios (OCRs)], dose calculations (PDDs and OCRs in a virtual water phantom), and patient setup using an image-guided radiation therapy system. We evaluated the uncertainties for these steps in conventionally fractionated EBRT for intracranial disease using 4-, 6-, and 10-MV flattened photon beams generated from clinical linear accelerators following the Guide to the Expression of Uncertainty in Measurement and an uncertainty evaluation method with uncorrected deflection. The following were the major contributors to these uncertainties: beam quality conversion factors for reference dosimetry; charge measurements, chamber depth, source-to-surface distance, water evaporation, and field size for relative dosimetry; dose calculation accuracy for the dose calculations; image registration, radiation-imaging isocenter coincidence, variation in radiation isocenter due to gantry and couch rotation, and intrafractional motion for the patient setup. Among the four steps, the relative dosimetry and dose calculation (namely, both penumbral OCRs) steps involved an uncertainty of more than 5% with a coverage factor of 1. In the EBRT process evaluated herein, the uncertainties in the relative dosimetry and dose calculations must be reduced.

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics.

The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this SpecialReport. The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain-relevant assessments via the analysis of relevant imagestatistics. As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10000 DGM-generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Fifty-eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top-ranked submission employed a conditional latent diffusion model, whereas the joint runners-up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID-based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds ofartifacts. This Grand Challenge highlighted the need for domain-specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intendeduse.

The dosimetric accuracy of a commercial model-based dose calculation algorithm in modeling a six-groove direction modulated brachytherapy tandem applicator

Objective.With advancements in high-dose rate brachytherapy, the clinical translation of intensity modulated brachytherapy (IMBT) innovations necessitates utilization of model-based dose calculation algorithms (MBDCA) for accurate and rapid dose calculations. This study uniquely benchmarks a commercial MBDCA, BrachyVision ACUROSTM(BVA), against Monte Carlo (MC) simulations, evaluating dose distributions for a novel IMBT applicator, termed as thesix-grooveDirection Modulated Brachytherapy (DMBT) tandem, expanding beyond previous focus on partially shielded vaginal cylinder applicators, through a novel methodology.Approach.The DMBT tandem applicator, made of a tungsten alloy with six evenly spaced grooves, was simulated using the GEANT4 MC code. Subsequently, two main scenarios were created using the BVA and reproduced by the MC simulations: 'Source at the Center of the Water Phantom (SACWP)' and 'Source at the Middle of the Applicator (SAMA)' for three cubical virtual water phantoms (20 cm)3, (30 cm)3, and (40 cm)3. A track length estimator was utilized for dose calculation and 2D/3D scoring were performed. The difference in isodose surfaces/lines (i.e. coverage) at each voxel,ΔDIsodose Levels/Lines, was thus calculated for relevant normalization points (rref).Results.The coverage was comparable, based on 2D scoring, between the BVA and MC isodose surfaces/lines for the region of clinical relevance, (i.e. within 5 cm radius from the source) withΔDIsodose Lines(rref: 1 cm from the source) falling within 2% for the two scenarios for all phantom sizes. For the phantom (20 cm)3,ΔDIsodose Levels(3D scoring) recorded the range [-3.0% +6.5%] ([-7.4% +7.3%]) for 95% of the voxels of the same scoring volume for the SACWP (SAMA) scenario.Significance.The results indicated that the BVA could render comparable coverage as compared to the MC simulations in the region of clinical relevance for different phantom sizes.ΔDIsodose Linesmay offer an advantageous metric for evaluation of MBDCAs in clinical setting.

Dosimetric evaluation and gradient analysis of various MLC leaf-width effects in external beam radiation therapy: TrueBeam Vs Halcyon

IntroductionThis study investigates dosimetric influence and gradient-analysis of leaf-width of various Multi-leaf-collimators (MLC) from Truebeam and Halcyon linear accelerators. MethodsThe leaf-width effects of Millennium120 and HD120MLC from Truebeam and SX1 and SX2 from Halcyon were studied using virtual phantom in Eclipse16.1.2 TPS. Target structures consist of bore and wave cylinders of equally spaced projected Planning target volume (PTV) of diameters ranging from 1-to-5 cm and 20 cm length. Treatment plans for all PTVs, and four different MLCs configurations from both machines were created utilizing 6MVFFF beam to deliver dose of 50Gy/25# using IMRT and VMAT. Plans were evaluated using plan quality indices including dose conformity, homogeneity, gradient radius, and Monitor-unit (MU). Also, dose gradients were analyzed by estimating distinct integral volume VD% and paired-t-tests were performed to evaluate statistical differences. ResultsAll the plan satisfied the minimum criteria of D95 %≥prescription dose and V107 %≤2cc. Mean conformity and homogeneity indices for SX1MLC(CI = 0.680,HI = 0.022) were found significantly higher and lower than SX2(CI = 0.746,HI = 0.016), Millennium120 (CI = 0.739,HI = 0.012), and HD120MLC(CI = 0.745,HI = 0.017), respectively. However, CI and HI for SX2, Millennium120, and HD120MLC found comparable. Gradient radius enclosing 50 % of isodose observed maximum and minimum for SX1 and HD120MLC, respectively. Plan MUs for Truebeam MLCs were found approximately 25 % higher than Halcyon MLCs. Dose distribution generated using SX2 and Millennium120 found comparable, however p ≤ 0.05 ascertained substantial differences among SX1, Millennium120, and HD120MLC. ConclusionMLC leaf-width influences intensity-modulation and significantly alters dosimetric outcome depending on the magnitude of the leaf-width. HD120MLC does not show much significant advantages over SX2 and Millennium120 except gradient control. Implications for practiceHalcyon SX1MLC produces least effective plan compared to all other MLC types. However, SX2 and Millennium120 can produce plans of comparable quality except plan MUs difference.

Real-time delivered dose assessment in carbon ion therapy of moving targets

Abstract Purpose:
Real-time adaptive particle therapy is being investigated as a means to maximize the treatment delivery accuracy. To react to dosimetric errors, a system for fast and reliable verification of the agreement between planned and delivered doses is essential. This study presents a clinically feasible, real-time 4D-dose reconstruction system, synchronized with the treatment delivery and motion of the patient, which can provide the necessary feedback on the quality of the delivery.
Methods:
A GPU-based analytical dose engine capable of millisecond dose calculation for carbon ion therapy has been developed and interfaced with the next generation of the Dose Delivery System (DDS) in use at Centro Nazionale di Adroterapia Oncologica (CNAO). The system receives the spot parameters and the motion information of the patient during the treatment and performs the reconstruction of the planned and delivered 4Ddoses. After each iso-energy layer, the results are displayed on a graphical user interface by the end of the spill pause of the synchrotron, permitting verification against the reference dose.
The framework has been verified experimentally at CNAO for a lung cancer case based on a virtual phantom 4DCT. The patient’s motion was mimicked by a moving Ionization Chambers (ICs) 2D-array.
Results:
For the investigated static and 4D-optimized treatment delivery cases, real time dose reconstruction was-achieved with an average pencil beam dose calculation speed up to more than one order of magnitude smaller than the spot delivery. The reconstructed doses have been benchmarked against offline log-file based dose reconstruction with the TRiP98 treatment planning system, as well as QA measurements with the ICs 2D-array, where an average gamma-index passing rate (3%/3mm) of 99.8% and 98.3%, respectively, were achieved.
Conclusion:
This work provides the first real-time 4D-dose reconstruction engine for carbon ion therapy. The framework integration with the CNAO DDS paves the way for a swift transition to the clinics.

Feasibility of the analytical dose calculation method for Au-198 brachytherapy

PurposeA dose calculation algorithm Computed Tomography (CT)-based analytical dose calculation method (CTanly), which can correct for subject inhomogeneity and size-dependent scatter doses, was applied to the 198Au seed. In this study, we evaluated the effectiveness of the CTanly method by comparing the gold standard Monte Carlo (MC) method and the conventional TG43 method on two virtual phantoms and patient CT images simulating oral cancer. MethodsAs virtual phantoms, a water phantom and a heterogeneous phantom with soft tissue inserted cubic fat, lung, and bone were used. A 2-mm-thick lead plate was also inserted into the heterogeneous phantom as a dose attenuator. Virtual 198Au seeds and a 2-mm-thick lead plate were placed on the patient CT images. Dose distributions obtained via the TG43 and CTanly methods were compared with those of the MC by gamma analysis with 2%/2-mm thresholds. The computation durations were also compared. ResultsIn the water phantom, dose distributions comparable to those obtained via the MC method were obtained regardless of the algorithm. For the inhomogeneity phantom and patient case, the CTanly method showed an improvement in the gamma passing rate and dose distributions similar to those of the MC method were obtained. The computation time, which was days with the MC method, was reduced to minutes with the CTanly method. ConclusionsThe CTanly method is effective for 198Au seed dose calculations and takes a shorter time to obtain the dose distributions than the MC method.

Internal dosimetry assessment of beta, beta/auger, and alpha decaying radionuclides in targeted radionuclide therapy for prostate cancer: a simulation study

The study employs the Monte Carlo method to calculate the internal dosimetry of beta, beta/Auger and alpha-type decaying radionuclides used in the treatment of prostate cancer. The distributions of dose to the prostate and critical organs were simulated on a virtual phantom using GATE MC software. In GATE simulation, geometric parameters and densities were determined for the prostate as the source organ and the kidneys, liver, testicles, and bladder as critical organs. In the prostate geometry, Lu-177, Ac-225, and Tb-161 with an activity of 370 MBq were identified. Using the DoseActors command, the S values, instant absorbed doses (Gy/s), uncertainties, and total absorbed doses (Gy) were computed and saved as an output file in the TXT format. Dosimetric comparison was made between different TRTs according to the absorbed doses in the source and critical organs. The prostate was found to be the tissue that received the highest instant absorbed dose with 8.397E-03, 1.594E+00 and 1.195E-02 Gy/s for Lu-177, Ac-225 and Tb-161, respectively. The kidney, liver, and testicles were taken lowest instant absorbed doses with 3.888E-08 (mean), 5.679E-08, and 4.302E-07 (mean) Gy/s by Tb-161. Lu-177 gave the lowest instant absorbed doses of 5.731E-07 Gy/s for the bladder. It was found that there was no overdose in any critical organ according to the critical threshold values given to protect the organs from radiation-related toxic effects. However, testicles were additionally evaluated in terms of fertility. Ac-225 and Tb-161 were radionuclides that produced optimal doses for TRT.

Estimation of doses absorbed by the thyroid and salivary glands, eyes, and brains of pediatric dental patients

In addition to the quality of the image, radiological protection of the patient must be considered to ensure an adequate diagnosis in dental radiology, especially in regard to those parts of the patient's body that are close to the radiation beam, such as the thyroid, salivary glands, and brain. In this work, the doses absorbed by the thyroid, salivary glands, eyes and brain of pediatric dental patients undergoing radiographic examinations are estimated using MCNP 6.2 coupled with virtual anthropomorphic phantoms, based on information from dental scenarios with a periapical X-ray unit. The absorbed doses were estimated for five- and 10-year-old male and female children. In the occlusal position, a higher absorbed dose to the thyroid was found for a five-year-old patient, whereas in the molar tube position, the brain was found to receive a higher absorbed dose for five- and 10-year-old patients. The results obtained here, expressed in terms of the absorbed dose, indicate that the beam direction and the use of different image acquisition techniques strongly influence the entrance dose values for the organs of interest in this study.

Time-domain diffuse optical imaging technique for monitoring rheumatoid arthritis disease activity: theoretical development and in silico validation

Objective. Effective early treatment—within 3–5 months of disease onset—significantly improves rheumatoid arthritis (RA) prognosis. Nevertheless, 1 in 3 patients experiences treatment failure which takes 3–6 months to detect with current monitoring techniques. The aim of this work is to develop a method for extracting quantitative features from data obtained with time-domain diffuse optical imaging (TD-DOI), and demonstrate their sensitivity to RA disease activity. Approach. 80 virtual phantoms of the proximal interphalangeal joint—obtained from a realistic tissue distribution derived from magnetic resonance imaging—were created to simulate RA-induced alterations in 5 physiological parameters. TD-DOI images were generated using Monte Carlo simulations, and Poisson noise was added to each image. Subsequently, each image was convolved with an instrument response function (IRF) to mimic experimental measurements. Various spatiotemporal features were extracted from the images (i.e. statistical moments, temporal Fourier components), corrected for IRF effects, and correlated with the disease index (DI) of each phantom. Main results. Spatiotemporal Fourier components of TD-DOI images were highly correlated with DI despite the confounding effects of noise and the IRF. Moreover, lower temporal frequency components ( ⩽ 0.4 GHz) demonstrated greater sensitivity to small changes in disease activity than previously published spatial features extracted from the same images. Significance. Spatiotemporal components of TD-DOI images may be more sensitive to small changes in RA disease activity than previously reported DOI features. TD-DOI may enable earlier detection of RA treatment failure, which would reduce the time needed to identify treatment failure and improve patient prognosis.

Virtual Reality vs Phantom Model: Benefits and Drawbacks of Simulation Training in Neurosurgery.

Traditional neurosurgical education has relied heavily on the Halstedian "see one, do one, teach one" approach which is increasingly perceived as inefficient in contemporary settings marked by a steady decline in surgical caseload. In recent years, simulation training has emerged as an effective and accessible training alternative. To date, however, there is no standardized criterion pertaining to the quality and implementation of simulators in neurosurgical education and training. This research aims to compare the efficacy of virtual reality (VR) and Phantom-based simulation training in the context of neurosurgical skill acquisition, with a focus on middle cerebral artery aneurysm clipping. An immersive VR clipping tool and a haptic clipping simulator incorporating 3-dimensional printing, additive manufacturing, and rheological analyses were developed. Twenty-two participants, comprising 12 medical students, 6 neurosurgical residents, and 4 experienced neurosurgeons, tested and evaluated both simulators for face and content validity. Construct and predictive validity of the simulators were assessed using an objective structured assessment scale for aneurysm clipping, measuring participants' performances and progress. Both modalities were deemed highly advantageous for educational purposes. Objective evaluations, however, revealed measurable differences in usability, efficacy, and transferability of the learned skills with VR excelling in procedural planning and visualization while Phantom simulation being noticeably superior in conveying surgical skills. Simulation training can accelerate the neurosurgical learning curve. The results of this study highlight the importance of establishing standardized criteria for the implementation and assessment of simulation modalities, ensuring consistent quality and efficacy in neurosurgical education.

Pixel-by-pixel correction of beam hardening artifacts by bowtie filter in fan-beam CT

Objective. Beam hardening (BH) artifacts in computed tomography (CT) images originate from the polychromatic nature of x-ray photons. In a CT system with a bowtie filter, residual BH artifacts remain when polynomial fits are used. These artifacts lead to worse visuals, reduced contrast, and inaccurate CT numbers. This work proposes a pixel-by-pixel correction (PPC) method to reduce the residual BH artifacts caused by a bowtie filter. Approach. The energy spectrum for each pixel at the detector after the photons pass through the bowtie filter was calculated. Then, the spectrum was filtered through a series of water slabs with different thicknesses. The polychromatic projection corresponding to the thickness of the water slab for each detector pixel could be obtained. Next, we carried out a water slab experiment with a mono energy E = 69 keV to get the monochromatic projection. The polychromatic and monochromatic projections were then fitted with a 2nd-order polynomial. The proposed method was evaluated on digital phantoms in a virtual CT system and phantoms in a real CT machine. Main results. In the case of a virtual CT system, the standard deviation of the line profile was reduced by 23.8%, 37.3%, and 14.3%, respectively, in the water phantom with different shapes. The difference of the linear attenuation coefficients (LAC) in the central and peripheral areas of an image was reduced from 0.010 to 0.003 cm−1 and 0.007 cm−1 to 0 in the biological tissue phantom and human phantom, respectively. The method was also validated using CT projection data obtained from Activion16 (Canon Medical Systems, Japan). The difference in the LAC in the central and peripheral areas can be reduced by a factor of two. Significance. The proposed PPC method can successfully remove the cupping artifacts in both virtual and authentic CT images. The scanned object’s shapes and materials do not affect the technique.

Breast density quantification in dual-energy mammography using virtual anthropomorphic phantoms.

Breast density is a significant risk factor for breast cancer and can impact the sensitivity of screening mammography. Area-based breast density measurements may not provide an accurate representation of the tissue distribution, therefore volumetric breast density (VBD) measurements are preferred. Dual-energy mammography enables volumetric measurements without additional assumptions about breast shape. In this work we evaluated the performance of a dual-energy decomposition technique for determining VBD by applying it to virtual anthropomorphic phantoms. The dual-energy decomposition formalism was used to quantify VBD on simulated dual-energy images of anthropomorphic virtual phantoms with known tissue distributions. We simulated 150 phantoms with volumes ranging from 50 to 709mL and VBD ranging from 15% to 60%. Using these results, we validated a correction for the presence of skin and assessed the method's intrinsic bias and variability. As a proof of concept, the method was applied to 14 sets of clinical dual-energy images, and the resulting breast densities were compared to magnetic resonance imaging (MRI) measurements. Virtual phantom VBD measurements exhibited a strong correlation (Pearson's ) with nominal values. The proposed skin correction eliminated the variability due to breast size and reduced the bias in VBD to a constant value of -2%. Disagreement between clinical VBD measurements using MRI and dual-energy mammography was under 10%, and the difference in the distributions was statistically non-significant. VBD measurements in both modalities had a moderate correlation (Spearman's =0.68). Our results in virtual phantoms indicate that the material decomposition method can produce accurate VBD measurements if the presence of a third material (skin) is considered. The results from our proof of concept showed agreement between MRI and dual-energy mammography VBD. Assessment of VBD using dual-energy images could provide complementary information in dual-energy mammography and tomosynthesis examinations.

Weighted CTDI Equation for 3D Rotational Angiography: A Monte Carlo Study

This study aims to verify the weighted Computed Tomography Dose Index (CTDIw) coefficients of 3D rotational angiography (3DRA) procedure using Monte Carlo simulation. The Monte Carlo simulation EGSnrc usercode was employed for 3D dose simulations of the rotational angiography procedure. A virtual phantom resembles the head CTDI phantom was constructed, with a diameter of 16 cm and a density resembling polymethyl methacrylate (1.13 g/cm3). A series of virtual phantoms consisting of 5 images with ionization chamber detectors at the center position, 12 o'clock, 9 o'clock, 6 o'clock, and 3 o'clock were acquired. Simulations were performed with photon sources of 70 and 109 kVp for 200-degree x-ray tube rotation. The field of view was divided into narrow, wide, and full beam with diameters of 1.7 cm; 4.9 cm; and 8.6 cm, respectively. The simulated doses at the ionization chamber were processed into weighting factor for weighted CTDI and compared with direct measurements. The dose ratio between peripheral and center positions for 360° CBCT and 200° 3DRA was 1:1 and 1:3 in this study. The weighting factors for 3DRA were determined as CTDIcenter = ¼ and CTDIperiphery = ¾. The measured average percentage difference of CTDIw between our weighted factor and conventional CTDIw was 1.75 % (-3.99 % to 6.08 %). The x-ray tube position of 3DRA impacted the accuracy of weighting factor of CTDIw, with implications for the proposed weighting factor (Wcenter = ¼ and Wperiphery = ¾) when using a 3DRA machine.

The sensitivity of radiobiological models in carbon ion radiotherapy (CIRT) and its consequences on the clinical treatment plan: Differences between LEM and MKM models.

Carbon ion radiotherapy (CIRT) relies on relative biological effectiveness (RBE)-weighted dose calculations. Japanese clinics predominantly use the microdosimetric kinetic model (MKM), while European centers utilize the local effect model (LEM). Despite both models estimating RBE-distributions in tissue, their physical and mathematical assumptions differ, leading to significant disparities in RBE-weighted doses. Several European clinics adopted Japanese treatment schedules, necessitating adjustments in dose prescriptions and organ at risk (OAR) constraints. In the context of these two clinically used standards for RBE-weighted dose estimation, the objective of this study was to highlight specific scenarios for which the translations between models diverge, as shortcomings between them can influence clinical decisions. Our aim was to discuss planning strategies minimizing those discrepancies, ultimately striving for more accurate and robust treatments. Evaluations were conducted in a virtual water phantom and patient CT-geometry, optimizing LEM RBE-weighted dose first and recomputing MKM thereafter. Dose-averaged linear energy transfer (LETd) distributions were also assessed. Results demonstrate how various parameters influence LEM/MKM translation. Similar LEM-dose distributions lead to markedly different MKM-dose distributions and variations in LETd. Generally, a homogeneous LEM RBE-weighted dose aligns with lower MKM values in most of the target volume. Nevertheless, paradoxical MKM hotspots may emerge (at the end of the range), potentially influencing clinical outcomes. Therefore, translation between models requires great caution. Understanding the relationship between these two clinical standards enables combining European and Japanese based experiences. The implementation of optimal planning strategies ensures the safety and acceptability of the clinical plan for both models and therefore enhances plan robustness from the RBE-weighted dose and LETd distribution point of view. This study emphasizes the importance of optimal planning strategies and the need for comprehensive CIRT plan quality assessment tools. In situations where simultaneous LEM and MKM computation capabilities are lacking, it can provide guidance in plan design, ultimately contributing to enhanced CIRT outcomes.

Optimizing dual-energy CT technique for iodine-based contrast-to-noise ratio, a theoretical study.

Dual-energy CT (DECT) systems provide valuable material-specific information by simultaneously acquiring two spectral measurements, resulting in superior image quality and contrast-to-noise ratio (CNR) while reducing radiation exposure and contrast agent usage. The selection of DECT scan parameters, including x-ray tube settings and fluence, is critical for the stability of the reconstruction process and hence the overall imagequality. The goal of this study is to propose a systematic theoretical method for determining the optimal DECT parameters for minimal noise and maximum CNR in virtual monochromatic images (VMIs) for fixed subject size and total radiationdose. The noise propagation in the process of projection based material estimation from DECT measurements is analyzed. The main components of the study are the mean pixel variances for the sinogram and monochromatic image and the CNR, which were shown to depend on the Jacobian matrix of the sinograms-to-DECT measurementsmap. Analytic estimates for the mean sinogram and monochromatic image pixel variances and the CNR as functions of tube potentials, fluence, and VMI energy are derived, and then used in a virtual phantom experiment as an objective function for optimizing the tube settings and VMI energy to minimize the image noise and maximize theCNR. It was shown that DECT measurements corresponding to kV settings that maximize the square of Jacobian determinant values over a domain of interest lead to improved stability of basis material reconstructions. Instances of non-uniqueness in DECT were addressed, focusing on scenarios where the Jacobian determinant becomes zero within the domain of interest despite significant spectral separation. The presence of non-uniqueness can lead to singular solutions during the inversion of sinograms-to-DECT measurements, underscoring the importance of considering uniqueness properties in parameter selection. Additionally, the optimal VMI energy and tube potentials for maximal CNR was determined. When the x-ray beam filter material was fixed at 2 mm of aluminum and the photon fluence for low and high kV scans were considered equal, the tube potential pair of 60/120 kV led to the maximal iodine CNR in the VMI at 53keV. Optimizing DECT scan parameters to maximize the CNR can be done in a systematic way. Also, choosing the parameters that maximize the Jacobian determinant over the set of expected line integrals leads to more stable reconstructions due to the reduced amplification of the measurement noise. Since the values of the Jacobian determinant depend strongly on the imaging task, careful consideration of all of the relevant factors is needed when implementing the proposedframework.