The GSF family of voxel phantoms

Feasibility of size-specific organ-dose estimates based on water equivalent diameter for common head CT examinations: a Monte Carlo study

Computed tomography dose index (CTDI) is an unreliable dose estimate outside of the standard CTDI phantom diameters (16 and 32 cm). Size-specific dose estimate (SSDE) for head computed tomography (CT) examination was studied in the American Association of Physicists in Medicine Report 293 to provide SSDE coefficient factors based on water equivalent diameter as size metrics. However, it is limited to one protocol and for a fully irradiated organ. This study aimed to evaluate the dependency of normalized organ dose (ND) on water equivalent diameter as a size metric in three common protocols: routine head, paranasal sinus, and temporal bone. CTDI_wmeasurements were performed for outlined protocols in the Siemens Emotion 16-slice-configuration scanner. Geant4 Application for Tomographic Emission Monte Carlo simulation platform, coupled with ten GSF patient models, was used to estimate organ doses. CT scanner system was modeled. Helical CT scans were simulated using constructor scan parameters and calculated scan lengths of each patient model. Organ doses provided by simulations were normalized to CTDI_vol. The water equivalent diameters (D_w) of patient models were obtained via relationships betweenD_wand both effective diameter for a sample of patients' data.NDs received by fully, partially, and non-directly irradiated organs were then reported as a function ofD_w. For fully irradiated organs, brain (R²> 0.92), eyes (R²> 0.88), and eye lens (R²> 0.89) correlate well withD_w. For the rest of the results, a poor correlation was observed. For partially irradiated organs, the exception was scalp (R²= 0.93) in temporal bone CT. For non-directly irradiated organs, the exception was thyroid (R²> 0.90) and lungs (R²> 0.91) in routine head CT. ND correlates well in routine head CT than other protocols. For the most part, no relationship seems to exist betweenR²and scan percentage coverage. The results have revealed additional factors that may influence the ND andD_wrelationship, which explains the need for more studies in the future to investigate the effect of scan conditions and organ anatomy variation.

A high-resolution pediatric female whole-body numerical model with comparison to a male model

Objective. Numerical models are central in designing and testing novel medical devices and in studying how different anatomical changes may affect physiology. Despite the numerous adult models available, there are only a few whole-body pediatric numerical models with significant limitations. In addition, there is a limited representation of both male and female biological sexes in the available pediatric models despite the fact that sex significantly affects body development, especially in a highly dynamic population. As a result, we developed Athena, a realistic female whole-body pediatric numerical model with high-resolution and anatomical detail.Approach. We segmented different body tissues through Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images of a healthy 3.5 year-old female child using 3D Slicer. We validated the high anatomical accuracy segmentation through two experienced sub-specialty-certified neuro-radiologists and the inter and intra-operator variability of the segmentation results comparing sex differences in organ metrics with physiologic values. Finally, we compared Athena with Martin, a similar male model, showing differences in anatomy, organ metrics, and MRI dosimetric exposure.Main results. We segmented 267 tissue compartments, which included 50 brain tissue labels. The tissue metrics of Athena displayed no deviation from the literature value of healthy children. We show the variability of brain metrics in the male and female models. Finally, we offer an example of computing Specific Absorption Rate and Joule heating in a toddler/preschooler at 7 T MRI.Significance. This study introduces a female realistic high-resolution numerical model using MRI and CT scans of a 3.5 year-old female child, the use of which includes but is not limited to radiofrequency safety studies for medical devices (e.g. an implantable medical device safety in MRI), neurostimulation studies, and radiation dosimetry studies. This model will be open source and available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Organs' absorbed dose and comparison of different methods for effective dose calculation in computed tomography of parathyroid glands

Objective:To estimate organs' absorbed dose from the two-phase CT of parathyroid glands, effective dose (ED) based on three different methods, and compare the dose values with those reported by other published protocols.Methods:Volumetric-computed-tomography-dose-index (CTDIvol), dose-length-product (DLP), and the corresponding scan length during each phase of a parathyroid protocol were recorded, for seventy-six patients. One k-factor, and two different k-factors for the neck and chest area were used to estimate the ED from DLP. A Monte Carlo software, VirtualDoseCT, was also used for the estimation of organs' absorbed dose and ED.Results:Two-phase parathyroid CT resulted in a mean ED of 3.93 mSv, 4.29 mSv and 4.21 mSv according to the one k-factor, two k-factors, and VirtualDoseCT methods, respectively. The two k-factors method resulted in a slight overestimation of 1.9% in total ED compared to VirtualDoseCT. No statistically significant difference was found in ED values between these methods (Wilcoxon test, p>0.05), except for female patients in the pre-contrast phase. The organs inside the SFOV received the following doses: thymus 23.3 mGy, lungs 11.5 mGy, oesophagus 9.2 mGy, thyroid 6.9 mGy, and breast 6.3 mGy. The ED and organs' dose (OD) values were significantly lower in the pre-contrast than in the arterial phase (Wilcoxon test, p<0.001). A statistically significant difference was observed between male and female patients for the pre-contrast phase (Mann-Whitney test, p<0.05), regarding the ED values obtained with the two k-factors method and VirtualDoseCT software.Conclusions:The two k-factors method could be applied for the ED estimation in clinical practice, if appropriate software is not available. An extensive range of ED values derived from the literature, mainly depending on the acquisition protocol parameters and the estimation method.

Voxelisation Algorithms and Data Structures: A Review

Voxel-based data structures, algorithms, frameworks, and interfaces have been used in computer graphics and many other applications for decades. There is a general necessity to seek adequate digital representations, such as voxels, that would secure unified data structures, multi-resolution options, robust validation procedures and flexible algorithms for different 3D tasks. In this review, we evaluate the most common properties and algorithms for voxelisation of 2D and 3D objects. Thus, many voxelisation algorithms and their characteristics are presented targeting points, lines, triangles, surfaces and solids as geometric primitives. For lines, we identify three groups of algorithms, where the first two achieve different voxelisation connectivity, while the third one presents voxelisation of curves. We can say that surface voxelisation is a more desired voxelisation type compared to solid voxelisation, as it can be achieved faster and requires less memory if voxels are stored in a sparse way. At the same time, we evaluate in the paper the available voxel data structures. We split all data structures into static and dynamic grids considering the frequency to update a data structure. Static grids are dominated by SVO-based data structures focusing on memory footprint reduction and attributes preservation, where SVDAG and SSVDAG are the most advanced methods. The state-of-the-art dynamic voxel data structure is NanoVDB which is superior to the rest in terms of speed as well as support for out-of-core processing and data management, which is the key to handling large dynamically changing scenes. Overall, we can say that this is the first review evaluating the available voxelisation algorithms for different geometric primitives as well as voxel data structures.

Dosimetric evaluation of radiopharmaceuticals in kidneys and uterine wall of a woman with early pregnancy using Stabin/Segars representations

MIRD method with the Stabin/Segars anthropomorphic representations were used to calculate the absorbed doses in kidneys and uterine wall of an early-stage pregnant woman when ^99mTc (DTPA), ^99mTc (DMSA) and ^99mTc (MAG3) are used for renal studies. Stabin and Segars anatomical representations are phantoms that are used in Monte Carlo calculations to determine the SAF, that with the pharmaceutical residence time are used to calculate the absorbed dose, from source organs, on target organs. Concerns about the impact on the absorbed dose due to the use of the three ^99mTc-based compounds as well as the use of different phantoms were here treated for the case of a female at early pregnant state. The lowest absorbed dose in the kidneys was obtained with ^99mTc (MAG3), and the relative difference of using Stabin and Segars anthropomorphic representations was 2.5%. For bladder and rest of organs the relative difference 14.63%. The lowest absorbed dose by uterine wall was obtained with ^99mTc(DMSA), however the relative difference of using Stabin and Segars anthropomorphic representations was 12%.

iPhantom: A Framework for Automated Creation of Individualized Computational Phantoms and Its Application to CT Organ Dosimetry

OBJECTIVE

This study aims to develop and validate a novel framework, iPhantom, for automated creation of patient-specific phantoms or "digital-twins (DT)" using patient medical images. The framework is applied to assess radiation dose to radiosensitive organs in CT imaging of individual patients.

METHOD

Given a volume of patient CT images, iPhantom segments selected anchor organs and structures (e.g., liver, bones, pancreas) using a learning-based model developed for multi-organ CT segmentation. Organs which are challenging to segment (e.g., intestines) are incorporated from a matched phantom template, using a diffeomorphic registration model developed for multi-organ phantom-voxels. The resulting digital-twin phantoms are used to assess organ doses during routine CT exams.

RESULT

iPhantom was validated on both with a set of XCAT digital phantoms (n = 50) and an independent clinical dataset (n = 10) with similar accuracy. iPhantom precisely predicted all organ locations yielding Dice Similarity Coefficients (DSC) 0.6 - 1 for anchor organs and DSC of 0.3-0.9 for all other organs. iPhantom showed <10% errors in estimated radiation dose for the majority of organs, which was notably superior to the state-of-the-art baseline method (20-35% dose errors).

CONCLUSION

iPhantom enables automated and accurate creation of patient-specific phantoms and, for the first time, provides sufficient and automated patient-specific dose estimates for CT dosimetry.

SIGNIFICANCE

The new framework brings the creation and application of CHPs (computational human phantoms) to the level of individual CHPs through automation, achieving wide and precise organ localization, paving the way for clinical monitoring, personalized optimization, and large-scale research.

Evaluating Size-Specific Dose Estimate (SSDE) as an estimate of organ doses from routine CT exams derived from Monte Carlo simulations

PURPOSE

Size-specific dose estimate (SSDE) is a metric that adjusts CTDI_vol to account for patient size. While not intended to be an estimate of organ dose, AAPM Report 204 notes the difference between the patient organ dose and SSDE is expected to be 10-20%. The purpose of this work was therefore to evaluate SSDE against estimates of organ dose obtained using Monte Carlo (MC) simulation techniques applied to routine exams across a wide range of patient sizes.

MATERIALS AND METHODS

Size-specific dose estimate was evaluated with respect to organ dose based on three routine protocols taken from Siemens scanners: (a) brain parenchyma dose in routine head exams, (b) lung and breast dose in routine chest exams, and (c) liver, kidney, and spleen dose in routine abdomen/pelvis exams. For each exam, voxelized phantom models were created from existing models or derived from clinical patient scans. For routine head exams, 15 patient models were used which consisted of 10 GSF/ICRP voxelized phantom models and five pediatric voxelized patient models created from CT image data. For all exams, the size metric used was water equivalent diameter (D_w ). For the routine chest exams, data from 161 patients were collected with a D_w range of ~16-44 cm. For the routine abdomen/pelvis exams, data from 107 patients were collected with a range of D_w from ~16 to 44 cm. Image data from these patients were segmented to generate voxelized patient models. For routine head exams, fixed tube current (FTC) was used while tube current modulation (TCM) data for body exams were extracted from raw projection data. The voxelized patient models and tube current information were used in detailed MC simulations for organ dose estimation. Organ doses from MC simulation were normalized by CTDI_vol and parameterized as a function of D_w . For each patient scan, the SSDE was obtained using D_w and CTDI_vol values of each scan, according to AAPM Report 220 for body scans and Report 293 for head scans. For each protocol and each patient, normalized organ doses were compared with SSDE. A one-sided tolerance limit covering 95% (P = 0.95) of the population with 95% confidence (α = 0.05) was used to assess the upper tolerance limit (T_U ) between SSDE and normalized organ dose.

RESULTS

For head exams, the T_U between SSDE and brain parenchyma dose was observed to be 12.5%. For routine chest exams, the T_U between SSDE and lung and breast dose was observed to be 35.6% and 68.3%, respectively. For routine abdomen/pelvis exams, the T_U between SSDE and liver, spleen, and kidney dose was observed to be 30.7%, 33.2%, and 33.0%, respectively.

CONCLUSIONS

The T_U of 20% between SSDE and organ dose was found to be insufficient to cover 95% of the sampled population with 95% confidence for all of the organs and protocols investigated, except for brain parenchyma dose. For the routine body exams, excluding the breasts, a wider threshold difference of ~30-36% would be needed. These results are, however, specific to Siemens scanners.

Monte Carlo-based patient internal dosimetry in fluoroscopy-guided interventional procedures: A review

PURPOSE

This systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.

METHODS

All relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.

RESULTS

Hundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.

CONCLUSION

The continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical.

Development, validation, and pilot MRI safety study of a high-resolution, open source, whole body pediatric numerical simulation model

Numerical body models of children are used for designing medical devices, including but not limited to optical imaging, ultrasound, CT, EEG/MEG, and MRI. These models are used in many clinical and neuroscience research applications, such as radiation safety dosimetric studies and source localization. Although several such adult models have been reported, there are few reports of full-body pediatric models, and those described have several limitations. Some, for example, are either morphed from older children or do not have detailed segmentations. Here, we introduce a 29-month-old male whole-body native numerical model, "MARTIN", that includes 28 head and 86 body tissue compartments, segmented directly from the high spatial resolution MRI and CT images. An advanced auto-segmentation tool was used for the deep-brain structures, whereas 3D Slicer was used to segment the non-brain structures and to refine the segmentation for all of the tissue compartments. Our MARTIN model was developed and validated using three separate approaches, through an iterative process, as follows. First, the calculated volumes, weights, and dimensions of selected structures were adjusted and confirmed to be within 6% of the literature values for the 2-3-year-old age-range. Second, all structural segmentations were adjusted and confirmed by two experienced, sub-specialty certified neuro-radiologists, also through an interactive process. Third, an additional validation was performed with a Bloch simulator to create synthetic MR image from our MARTIN model and compare the image contrast of the resulting synthetic image with that of the original MRI data; this resulted in a "structural resemblance" index of 0.97. Finally, we used our model to perform pilot MRI safety simulations of an Active Implantable Medical Device (AIMD) using a commercially available software platform (Sim4Life), incorporating the latest International Standards Organization guidelines. This model will be made available on the Athinoula A. Martinos Center for Biomedical Imaging website.

Uncertainty analysis in internal dose calculations for cerium considering the uncertainties of biokinetic parameters and S values

Radioactive cerium and other lanthanides can be transported through the aquatic system into foodstuffs and then be incorporated by humans. Information on the uncertainty of reported dose coefficients for exposed members of the public is then needed for risk analysis. In this study, uncertainties of dose coefficients due to the ingestion of the radionuclides 141Ce and 144Ce were estimated. According to the schema of internal dose calculation, a general statistical method based on the propagation of uncertainty was developed. The method takes into account the uncertainties contributed by the biokinetic models and by the so-called S values. These S-values were derived by using Monte Carlo radiation transport simulations with five adult non-reference voxel computational phantoms that have been developed at Helmholtz Zentrum München, Germany. Random and Latin hypercube sampling techniques were applied to sample parameters of biokinetic models and S values. The uncertainty factors, expressed as the square root of the 97.5th and 2.5th percentile ratios, for organ equivalent dose coefficients of 141Ce were found to be in the range of 1.2-5.1 and for 144Ce in the range of 1.2-7.4. The uncertainty factor of the detriment-weighted dose coefficient for 141Ce is 2.5 and for 144Ce 3.9. It is concluded that a general statistical method for calculating the uncertainty of dose coefficients was developed and applied to the lanthanide cerium. The dose uncertainties obtained provide improved dose coefficients for radiation risk analysis of humans. Furthermore, these uncertainties can be used to identify those parameters most important in internal dose calculations by applying sensitivity analyses.

COMPARISON OF EXPERIMENTAL AND NUMERICAL METHODS OF PATIENT DOSE ESTIMATIONS IN CT USING ANTHROPOMORPHIC MODELS

The common methods for patient dose estimations in computed tomography (CT) are thermoluminescence dosemeter (TLD) measurements or the usage of software packages based on Monte Carlo simulations like CT-Expo or the newer CTVoxDos, which uses the ICRP Reference Adult Male (ICRP 110). Organ (OD) and effective doses of a CT protocol of the upper abdomen are compared. Compared to CTVoxDos, ODs inferred by TLD measurement using an anthropomorphic phantom differ by $\mathbf{(19\pm 16)\,\%}$ inside the primary radiation field, $\mathbf{(14\pm 2)\,\%}$ for partially primary irradiated organs and $\mathbf{(34\pm 38)\,\%}$ in the scattered radiation field. ODs estimated by CT-Expo show a mean deviation of $\mathbf{(16\pm 9)\,\%}$ (primary irradiated) and $\mathbf{(28\pm 31)\,\%}$ (scatter irradiated) from ODs estimated by CTVoxDos.

Simple variance reduction in Monte Carlo calculations of specific absorbed fractions: Russian roulette and splitting at the source organ

PURPOSE

To investigate the capabilities of several variance reduction techniques in the calculation of specific absorbed fractions in cases where the source and the target organs are far away and/or the target organs have a small volume.

METHODS

The specific absorbed fractions have been calculated by using the Monte Carlo code PENELOPE and by assuming the thyroid gland as the source organ and the testicles, the urinary bladder, the uterus, and the ovaries as the target ones. A mathematical anthropomorphic phantom, similar to the MIRD-type phantoms, has been considered. Photons with initial energies of 50, 100 and 500 keV were emitted isotropically from the volume of the source organ. Simulations have been carried out by implementing the variance reduction techniques of splitting and Russian roulette at the source organ only and the interaction forcing at the target organs. The influence of the implementation details of those techniques have been investigated and optimal parameters have been determined. All simulations were run with a CPU time of 1.5 · 10⁵ s.

RESULTS

Specific absorbed fractions with relative uncertainties well below 10% have been obtained in most cases, agreeing with those used as reference. The best value for the factor defining the application of the Russian roulette technique was r = 0.3. The best value for the splitting number was between s = 3 and s = 10, depending on the specific energies and target organs.

CONCLUSIONS

The proposed strategy provides an effective method for computing specific absorbed fractions for the most unfavorable situations, with a computing effort that is considerably reduced with respect to other methodologies.

Innovations in Computer Technologies Have Impacted Radiation Dosimetry Through Anatomically Realistic Phantoms and Fast Monte Carlo Simulations

Radiological physics principles have not changed in the past 60 y when computer technologies advanced exponentially. The research field of anatomical modeling for the purpose of radiation dose calculations has experienced an explosion in activity in the past two decades. Such an exciting advancement is due to the feasibility of creating three-dimensional geometric details of the human anatomy from tomographic imaging and of performing Monte Carlo radiation transport simulations on increasingly fast and cheap personal computers. The advent of a new type of high-performance computing hardware in recent years-graphics processing units-has made it feasible to carry out time-consuming Monte Carlo calculations at near real-time speeds. This paper introduces the history of three generations of computational human phantoms (the stylized medical internal radiation dosimetry-type phantoms, the voxelized tomographic phantoms, and the boundary representation deformable phantoms) and new development of the graphics processing unit-based Monte Carlo radiation dose calculations. Examples are given for research projects performed by my students in applying computational phantoms and a new Monte Carlo code, ARCHER, to problems in radiation protection, imaging, and radiotherapy. Finally, the paper discusses challenges and future opportunities for research.

Advances in Computational Human Phantoms and Their Applications in Biomedical Engineering - A Topical Review

Over the past decades, significant improvements have been made in the field of computational human phantoms (CHPs) and their applications in biomedical engineering. Their sophistication has dramatically increased. The very first CHPs were composed of simple geometric volumes, e.g., cylinders and spheres, while current CHPs have a high resolution, cover a substantial range of the patient population, have high anatomical accuracy, are poseable, morphable, and are augmented with various details to perform functionalized computations. Advances in imaging techniques and semi-automated segmentation tools allow fast and personalized development of CHPs. These advances open the door to quickly develop personalized CHPs, inherently including the disease of the patient. Because many of these CHPs are increasingly providing data for regulatory submissions of various medical devices, the validity, anatomical accuracy, and availability to cover the entire patient population is of utmost importance. The article is organized into two main sections: the first section reviews the different modeling techniques used to create CHPs, whereas the second section discusses various applications of CHPs in biomedical engineering. Each topic gives an overview, a brief history, recent developments, and an outlook into the future.

Estimating a size-specific dose for helical head CT examinations using Monte Carlo simulation methods

PURPOSE

Size-specific dose estimates (SSDE) conversion factors have been determined by AAPM Report 204 to adjust CTDI_vol to account for patient size but were limited to body CT examinations. The purpose of this work was to determine conversion factors that could be used for an SSDE for helical, head CT examinations for patients of different sizes.

METHODS

Validated Monte Carlo (MC) simulation methods were used to estimate dose to the center of the scan volume from a routine, helical head examination for a group of patient models representing a range of ages and sizes. Ten GSF/ICRP voxelized phantom models and five pediatric voxelized patient models created from CT image data were used in this study. CT scans were simulated using a Siemens multidetector row CT equivalent source model. Scan parameters were taken from the AAPM Routine Head protocols for a fixed tube current (FTC), helical protocol, and scan lengths were adapted to the anatomy of each patient model. MC simulations were performed using mesh tallies to produce voxelized dose distributions for the entire scan volume of each model. Three tally regions were investigated: (1) a small 0.6 cc volume at the center of the scan volume, (2) 0.8-1.0 cm axial slab at the center of the scan volume, and (3) the entire scan volume. Mean dose to brain parenchyma for all three regions was calculated. Mean bone dose and a mass-weighted average dose, consisting of brain parenchyma and bone, were also calculated for the slab in the central plane and the entire scan volume. All dose measures were then normalized by CTDI_vol for the 16 cm phantom (CTDI_vol,16 ). Conversion factors were determined by calculating the relationship between normalized doses and water equivalent diameter (D_w ).

RESULTS

CTDI_vol,16 -normalized mean brain parenchyma dose values within the 0.6 cc volume, 0.8-1.0 cm central axial slab, and the entire scan volume, when parameterized by D_w , had an exponential relationship with a coefficient of determination (R² ) of 0.86, 0.84, and 0.88, respectively. There was no statistically significant difference between the conversion factors resulting from these three different tally regions. Exponential relationships between CTDI_vol,16 -normalized mean bone doses had R² values of 0.83 and 0.87 for the central slab and for the entire scan volume, respectively. CTDI_vol,16 -normalized mass-weighted average doses had R² values of 0.39 and 0.51 for the central slab and for the entire scan volume, respectively.

CONCLUSIONS

Conversion factors that describe the exponential relationship between CTDI_vol,16 -normalized mean brain dose and a size metric (D_w ) for helical head CT examinations have been reported for two different interpretations of the center of the scan volume. These dose descriptors have been extended to describe the dose to bone in the center of the scan volume as well as a mass-weighted average dose to brain and bone. These may be used, when combined with other efforts, to develop an SSDE dose coefficients for routine, helical head CT examinations.

Estimating lung, breast, and effective dose from low-dose lung cancer screening CT exams with tube current modulation across a range of patient sizes

PURPOSE

The purpose of this study was to estimate the radiation dose to the lung and breast as well as the effective dose from tube current modulated (TCM) lung cancer screening (LCS) scans across a range of patient sizes.

METHODS

Monte Carlo (MC) methods were used to calculate lung, breast, and effective doses from a low-dose LCS protocol for a 64-slice CT that used TCM. Scanning parameters were from the protocols published by AAPM's Alliance for Quality CT. To determine lung, breast, and effective doses from lung cancer screening, eight GSF/ICRP voxelized phantom models with all radiosensitive organs identified were used to estimate lung, breast, and effective doses. Additionally, to extend the limited size range provided by the GSF/ICRP phantom models, 30 voxelized patient models of thoracic anatomy were generated from LCS patient data. For these patient models, lung and breast were semi-automatically segmented. TCM schemes for each of the GSF/ICRP phantom models were generated using a validated method wherein tissue attenuation and scanner limitations were used to determine the TCM output as a function of table position and source angle. TCM schemes for voxelized patient models were extracted from the raw projection data. The water equivalent diameter, Dw, was used as the patient size descriptor. Dw was estimated for the GSF/ICRP models. For the thoracic patient models, Dw was extracted from the DICOM header of the CT localizer radiograph. MC simulations were performed using the TCM scheme for each model. Absolute organ doses were tallied and effective doses were calculated using ICRP 103 tissue weighting factors for the GSF/ICRP models. Metrics of scanner radiation output were determined based on each model's TCM scheme, including CTDIvol , dose length product (DLP), and CTDIvol, Low Att , a previously described regional metric of scanner output covering most of the lungs and breast. All lung and breast doses values were normalized by scan-specific CTDIvol and CTDIvol, Low Att . Effective doses were normalized by scan-specific CTDIvol and DLP. Absolute and normalized doses were reported as a function of Dw.

RESULTS

Lung doses normalized by CTDIvol, Low Att were modeled as an exponential relationship with respect to Dw with coefficients of determination (R2 ) of 0.80. Breast dose normalized by CTDIvol, Low Att was modeled with an exponential relationship to Dw with an R2 of 0.23. For all eight GSF/ICRP phantom models, the effective dose using TCM protocols was below 1.6 mSv. Effective doses showed some size dependence but when normalized by DLP demonstrated a constant behavior.

CONCLUSION

Lung, breast, and effective doses from LCS CT exams with TCM were estimated with respect to patient size. Normalized lung dose can be reasonably estimated with a measure of a patient size such as Dw and regional metric of CTDIvol covering the thorax such as CTDIvol, Low Att , while normalized breast dose can also be estimated with a regional metric of CTDIvol but with a larger degree of variability than observed for lung. Effective dose normalized by DLP can be estimated with a constant multiplier.

Computational phantoms, ICRP/ICRU, and further developments

Phantoms simulating the human body play a central role in radiation dosimetry. The first computational body phantoms were based upon mathematical expressions describing idealised body organs. With the advent of more powerful computers in the 1980s, voxel phantoms have been developed. Being based on three-dimensional images of individuals, they offer a more realistic anatomy. Hence, the International Commission on Radiological Protection (ICRP) decided to construct voxel phantoms representative of the adult Reference Male and Reference Female for the update of organ dose coefficients. Further work on phantom development has focused on phantoms that combine the realism of patient-based voxel phantoms with the flexibility of mathematical phantoms, so-called 'boundary representation' (BREP) phantoms. This phantom type has been chosen for the ICRP family of paediatric reference phantoms. Due to the limited voxel resolution of the adult reference computational phantoms, smaller tissues, such as the lens of the eye, skin, and micron-thick target tissues in the respiratory and alimentary tract regions, could not be segmented properly. In this context, ICRP Committee 2 initiated a research project with the goal of producing replicas of the ICRP Publication 110 phantoms in polygon mesh format, including all source and target regions, even those with micron resolution. BREP phantoms of the fetus and the pregnant female at various stages of gestation complete the phantoms available for radiation protection computations.

Patient-Specific Computational Model and Dosimetry Calculations for PET/CT of a Patient Pregnant with Twins

The radiation dose delivered to pregnant patients during radiologic imaging procedures raises health concerns because the developing embryo and fetus are considered to be highly radiosensitive. To appropriately weigh the diagnostic benefits against the radiation risks, the radiologist needs reasonably accurate and detailed estimates of the fetal dose. Expanding our previously developed series of computational phantoms for pregnant women, we here describe a personalized model for twin pregnancy, based on an actual clinical scan. Methods: The model is based on a standardized hybrid pregnant female and fetus phantom and on a clinical case of a patient who underwent an ¹⁸F-FDG PET/CT scan while expecting twins at 25 weeks' gestation. This model enabled us to produce a realistic physical representation of the pregnant patient and to estimate the maternal and fetal organ doses from the ¹⁸F-FDG and CT components. The Monte Carlo N-Particle Extended general-purpose code was used for radiation transport simulation. Results: The ¹⁸F-FDG doses for the 2 fetuses were 3.78 and 3.99 mGy, and the CT doses were 0.76 and 0.70 mGy, respectively. Therefore, the relative contribution of ¹⁸F-FDG and CT to the total dose to the fetuses was about 84% and 16%, respectively. Meanwhile, for ¹⁸F-FDG, the calculated personalized absorbed dose was about 40%-50% higher than the doses reported by other dosimetry computer software tools. Conclusion: Our approach to constructing personalized computational models allows estimation of a patient-specific radiation dose, even in cases with unusual anatomic features such as a twin pregnancy. Our results also show that, even in twins, the fetal organ doses from both ¹⁸F-FDG and CT present a certain variability linked to the anatomic characteristics. The CT fetal dose is smaller than the ¹⁸F-FDG PET dose.

The dosimetric impact of including the patient table in CT dose estimates

The purpose of this study was to evaluate the dosimetric impact of including the patient table in Monte Carlo CT dose estimates for both spiral scans and scan projection radiographs (SPR). CT scan acquisitions were simulated for a Siemens SOMATOM Force scanner (Siemens Healthineers, Forchheim, Germany) with and without a patient table present. An adult male, an adult female and a pediatric female voxelized phantom were simulated. The simulated scans included tube voltages of 80 and 120 kVp. Spiral scans simulated without a patient table resulted in effective doses that were overestimated by approximately 5% compared to the same simulations performed with the patient table present. Doses in selected individual organs (breast, colon, lung, red bone marrow and stomach) were overestimated by up to 8%. Effective doses from SPR acquired with the x-ray tube stationary at 6 o'clock (posterior-anterior) were overestimated by 14-23% when the patient table was not included, with individual organ dose discrepancies (breast, colon, lung red bone marrow and stomach) all exceeding 13%. The reference entrance skin dose to the back were in this situation overestimated by 6-15%. These results highlight the importance of including the patient table in patient dose estimates for such scan situations.

Estimating patient dose from CT exams that use automatic exposure control: Development and validation of methods to accurately estimate tube current values

PURPOSE

The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturer's AEC system to enable accurate estimates of patient dose.

METHODS

Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x-ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual-topo) as well as the simulated topogram based on image data (sim-topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual-topo and sim-topo).

RESULTS

When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual-topo) and simulated topogram (sim-topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual-topo and sim-topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%.

CONCLUSIONS

Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.

Feasibility of reducing differences in estimated doses in nuclear medicine between a patient-specific and a reference phantom

The feasibility of reducing the differences between patient-specific internal doses and doses estimated using reference phantoms was evaluated. Relatively simple adjustments to a polygon-surface ICRP adult male reference phantom were applied to fit selected individual dimensions using the software Rhinoceros®4.0. We tested this approach on two patient-specific phantoms: the biggest and the smallest phantoms from the Helmholtz Zentrum München library. These phantoms have unrelated anatomy and large differences in body-mass-index. Three models approximating each patient's anatomy were considered: the voxel and the polygon-surface ICRP adult male reference phantoms and the adjusted polygon-surface reference phantom. The Specific Absorbed Fractions (SAFs) for internal photon and electron sources were calculated with the Monte Carlo code EGSnrc. Employing the time-integrated activity coefficients of a radiopharmaceutical (S)-4-(3-¹⁸F-fluoropropyl)-l-glutamic acid and the calculated SAFs, organ absorbed-dose coefficients were computed following the formalism promulgated by the Committee on Medical Internal Radiation Dose. We compared the absorbed-dose coefficients between each patient-specific phantom and other models considered with emphasis on the cross-fire component. The corresponding differences for most organs were notably lower for the adjusted reference models compared to the case when reference models were employed. Overall, the proposed approach provided reliable dose estimates for both tested patient-specific models despite the pronounced differences in their anatomy. To capture the full range of inter-individual anatomic variability more patient-specific phantoms are required. The results of this test study suggest a feasibility of estimating patient-specific doses within a relative uncertainty of 25% or less using adjusted reference models, when only simple phantom scaling is applied.

Realistic phantoms to characterize dosimetry in pediatric CT

BACKGROUND

The estimation of organ doses and effective doses for children receiving CT examinations is of high interest. Newer, more realistic anthropomorphic body models can provide information on individual organ doses and improved estimates of effective dose.

MATERIALS AND METHODS

Previously developed body models representing 50th-percentile individuals at reference ages (newborn, 1, 5, 10 and 15 years) were modified to represent 10th, 25th, 75th and 90th height percentiles for both genders and an expanded range of ages (3, 8 and 13 years). We calculated doses for 80 pediatric reference phantoms from simulated chest-abdomen-pelvis exams on a model of a Philips Brilliance 64 CT scanner. Individual organ and effective doses were normalized to dose-length product (DLP) and fit as a function of body diameter.

RESULTS

We calculated organ and effective doses for 80 reference phantoms and plotted them against body diameter. The data were well fit with an exponential function. We found DLP-normalized organ dose to correlate strongly with body diameter (R2>0.95 for most organs). Similarly, we found a very strong correlation with body diameter for DLP-normalized effective dose (R2>0.99). Our results were compared to other studies and we found average agreement of approximately 10%.

CONCLUSION

We provide organ and effective doses for a total of 80 reference phantoms representing normal-stature children ranging in age and body size. This information will be valuable in replacing the types of vendor-reported doses available. These data will also permit the recording and tracking of individual patient doses. Moreover, this comprehensive dose database will facilitate patient matching and the ability to predict patient-individualized dose prior to examination.

Electromagnetic computation and modeling in MRI

Electromagnetic (EM) computational modeling is used extensively during the development of a Magnetic Resonance Imaging (MRI) scanner, its installation, and use. MRI, which relies on interactions between nuclear magnetic moments and the applied magnetic fields, uses a range of EM tools to optimize all of the magnetic fields required to produce the image. The main field magnet is designed to exacting specifications but challenges in manufacturing, installation, and use require additional tools to maintain target operational performance. The gradient magnetic fields, which provide the primary signal localization mechanism, are designed under another set of complex design trade-offs which include conflicting imaging performance specifications and patient physiology. Gradients are largely impervious to external influences, but are also used to enhance main field operational performance. The radiofrequency (RF) magnetic fields, which are used to elicit the signals fundamental to the MR image, are a challenge to optimize for a host of reasons that include patient safety, image quality, cost optimization, and secondary signal localization capabilities. This review outlines these issues and the EM modeling used to optimize MRI system performance.

The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms

Purpose To develop a method to incorporate the propagation of contrast material into computational anthropomorphic phantoms for estimation of organ dose at computed tomography (CT). Materials and Methods A patient-specific physiologically based pharmacokinetic (PBPK) model of the human cardiovascular system was incorporated into 58 extended cardiac-torso (XCAT) patient phantoms. The PBPK model comprised compartmental models of vessels and organs unique to each XCAT model. For typical injection protocols, the dynamics of the contrast material in the body were described according to a series of patient-specific iodine mass-balance differential equations, the solutions to which provided the contrast material concentration time curves for each compartment. Each organ was assigned to a corresponding time-varying iodinated contrast agent to create the contrast material-enhanced five-dimensional XCAT models, in which the fifth dimension represents the dynamics of contrast material. To validate the accuracy of the models, simulated aortic and hepatic contrast-enhancement results throughout the models were compared with previously published clinical data by using the percentage of discrepancy in the mean, time to 90% peak, peak value, and slope of enhancement in a paired t test at the 95% significance level. Results The PBPK model allowed effective prediction of the time-varying concentration curves of various contrast material administrations in each organ for different patient models. The contrast-enhancement results were in agreement with results of previously published clinical data, with mean percentage, time to 90% peak, peak value, and slope of less than 10% (P > .74), 4%, 7%, and 14% for uniphasic and 12% (P > .56), 4%, 12%, and 14% for biphasic injection protocols, respectively. The exception was hepatic enhancement results calculated for a uniphasic injection protocol for which the discrepancy was less than 25%. Conclusion A technique to model the propagation of contrast material in XCAT human models was developed. The models with added contrast material propagation can be applied to simulate contrast-enhanced CT examinations. ^© RSNA, 2017 Online supplemental material is available for this article.

NUMERICAL ASSESSMENT OF 131I DEPOSITED IN THYROID FOR NON-STANDARD SITUATIONS

At the CIEMAT whole-body counter, a low-energy germanium detector is used for the in vivo assessment of (131)I activity in thyroid, mainly for the individual monitoring programmes of workers. The detector is calibrated with a cylindrical neck phantom made of polymethyl methacrylate that mimics the neck of an adult, containing a vial with a radioactive solution. For an accurate activity assessment, it is necessary to perform the calibration of the detector with phantoms that closely reproduce the anatomy of a real person. Nevertheless, it is not affordable to count on a variety of physical phantoms covering the different anatomical characteristics that could be found over the whole population, including children. An alternative approach to face this situation is offered by the numerical calibration procedure based on Monte Carlo calculations in conjunction with realistic voxel phantoms. A series of computational voxel phantoms of different ages and dimensions have been used in this work to simulate an internal contamination of the thyroid and to estimate the response of the detector for measurements involving individuals whose anatomical characteristics differ from the reference adult man.

A MONTE CARLO STUDY OF SIMULATED MEASUREMENTS OF RADIONUCLIDES IN BONE

When measuring the internally deposited activity in the bone of a subject, the placement of the detector is critical. This study reports the simulated counting efficiencies for three counting geometries, the skull, knee and shin, using 13 different voxel phantoms. It shows that the range of counting efficiencies for a given geometry is large for the studied phantoms, especially at low energies. Skull counting offers higher efficiency for low energies such as the 17 keV compared to knee counting or shin counting, but this advantage disappears when the energy is higher such as at 185 keV. This work also shows that the calibration phantom may greatly impact the accuracy of the activity estimate in bone counting, with uncertainties increasing greatly as the photon energy is reduced. Estimating the activity of a radionuclide in bone from direct counting has large uncertainties, and the dose calculated from a skeleton measurement would need careful analysis and, if possible, supporting data from other bioassay measurements.

Development of computational pregnant female and fetus models and assessment of radiation dose from positron-emitting tracers

PURPOSE

Molecular imaging using PET and hybrid (PET/CT and PET/MR) modalities nowadays plays a pivotal role in the clinical setting for diagnosis and staging, treatment response monitoring, and radiation therapy treatment planning of a wide range of oncologic malignancies. The developing embryo/fetus presents a high sensitivity to ionizing radiation. Therefore, estimation of the radiation dose delivered to the embryo/fetus and pregnant patients from PET examinations to assess potential radiation risks is highly praised.

METHODS

We constructed eight embryo/fetus models at various gestation periods with 25 identified tissues according to reference data recommended by the ICRP publication 89 representing the anatomy of the developing embryo/fetus. The developed embryo/fetus models were integrated into realistic anthropomorphic computational phantoms of the pregnant female and used for estimating, using Monte Carlo calculations, S-values of common positron-emitting radionuclides, organ absorbed dose, and effective dose of a number of positron-emitting labeled radiotracers.

RESULTS

The absorbed dose is nonuniformly distributed in the fetus. The absorbed dose of the kidney and liver of the 8-week-old fetus are about 47.45 % and 44.76 % higher than the average absorbed dose of the fetal total body for all investigated radiotracers. For ¹⁸F-FDG, the fetal effective doses are 2.90E-02, 3.09E-02, 1.79E-02, 1.59E-02, 1.47E-02, 1.40E-02, 1.37E-02, and 1.27E-02 mSv/MBq at the 8th, 10th, 15th, 20th, 25th, 30th, 35th, and 38th weeks of gestation, respectively.

CONCLUSION

The developed pregnant female/fetus models matching the ICRP reference data can be exploited by dedicated software packages for internal and external dose calculations. The generated S-values will be useful to produce new standardized dose estimates to pregnant patients and embryo/fetus from a variety of positron-emitting labeled radiotracers.

New small-intestine modeling method for surface-based computational human phantoms

When converting voxel phantoms to a surface format, the small intestine (SI), which is usually not accurately represented in a voxel phantom due to its complex and irregular shape on one hand and the limited voxel resolutions on the other, cannot be directly converted to a high-quality surface model. Currently, stylized pipe models are used instead, but they are strongly influenced by developer's subjectivity, resulting in unacceptable geometric and dosimetric inconsistencies. In this paper, we propose a new method for the construction of SI models based on the Monte Carlo approach. In the present study, the proposed method was tested by constructing the SI model for the polygon-mesh version of the ICRP reference male phantom currently under development. We believe that the new SI model is anatomically more realistic than the stylized SI models. Furthermore, our simulation results show that the new SI model, for both external and internal photon exposures, leads to dose values that are more similar to those of the original ICRP male voxel phantom than does the previously constructed stylized SI model.

Exposure assessment of one-year-old child to 3G tablet in uplink mode and to 3G femtocell in downlink mode using polynomial chaos decomposition

So far, the assessment of the exposure of children, in the ages 0-2 years old, to relatively new radio-frequency (RF) technologies, such as tablets and femtocells, remains an open issue. This study aims to analyse the exposure of a one year-old child to these two sources, tablets and femtocells, operating in uplink (tablet) and downlink (femtocell) modes, respectively. In detail, a realistic model of an infant has been used to model separately the exposures due to (i) a 3G tablet emitting at the frequency of 1940 MHz (uplink mode) placed close to the body and (ii) a 3G femtocell emitting at 2100 MHz (downlink mode) placed at a distance of at least 1 m from the infant body. For both RF sources, the input power was set to 250 mW. The variability of the exposure due to the variation of the position of the RF sources with respect to the infant body has been studied by stochastic dosimetry, based on polynomial chaos to build surrogate models of both whole-body and tissue specific absorption rate (SAR), which makes it easy and quick to investigate the exposure in a full range of possible positions of the sources. The major outcomes of the study are: (1) the maximum values of the whole-body SAR (WB SAR) have been found to be 9.5 mW kg(-1) in uplink mode and 65 μW kg(-1) in downlink mode, i.e. within the limits of the ICNIRP 1998 Guidelines; (2) in both uplink and downlink mode the highest SAR values were approximately found in the same tissues, i.e. in the skin, eye and penis for the whole-tissue SAR and in the bone, skin and muscle for the peak SAR; (3) the change in the position of both the 3G tablet and the 3G femtocell significantly influences the infant exposure.

Patient-specific dose calculations for pediatric CT of the chest, abdomen and pelvis

BACKGROUND

Organ dose is essential for accurate estimates of patient dose from CT.

OBJECTIVE

To determine organ doses from a broad range of pediatric patients undergoing diagnostic chest-abdomen-pelvis CT and investigate how these relate to patient size.

MATERIALS AND METHODS

We used a previously validated Monte Carlo simulation model of a Philips Brilliance 64 multi-detector CT scanner (Philips Healthcare, Best, The Netherlands) to calculate organ doses for 40 pediatric patients (M:F = 21:19; range 0.6-17 years). Organ volumes and positions were determined from the images using standard segmentation techniques. Non-linear regression was performed to determine the relationship between volume CT dose index (CTDIvol)-normalized organ doses and abdominopelvic diameter. We then compared results with values obtained from independent studies.

RESULTS

We found that CTDIvol-normalized organ dose correlated strongly with exponentially decreasing abdominopelvic diameter (R(2) > 0.8 for most organs). A similar relationship was determined for effective dose when normalized by dose-length product (R(2) = 0.95). Our results agreed with previous studies within 12% using similar scan parameters (e.g., bowtie filter size, beam collimation); however results varied up to 25% when compared to studies using different bowtie filters.

CONCLUSION

Our study determined that organ doses can be estimated from measurements of patient size, namely body diameter, and CTDIvol prior to CT examination. This information provides an improved method for patient dose estimation.

The effect of high-permittivity pads on specific absorption rate in radiofrequency-shimmed dual-transmit cardiovascular magnetic resonance at 3T

BACKGROUND

Dual-channel transmit technology improves the image quality in cardiovascular magnetic resonance (CMR) at 3 T by reducing the degree of radiofrequency (RF) shading over the heart by using RF shimming. Further improvements in image quality have been shown on a dual-transmit system using high permittivity pads. The aim of this study is to investigate the transmit field (B 1 (+)) homogeneity and the specific absorption rate (SAR) using high permittivity pads as a function of the complete range of possible RF-shim settings in order to gauge the efficacy and safety of this approach.

METHODS

Electromagnetic (EM) simulations were performed in five different body models using a dual-transmit RF coil, with and without high permittivity pads. The RF shimming behaviour in terms of B 1 (+) homogeneity and local SAR were determined as a function of different RF-shim settings. Comparative experimental data were obtained in healthy volunteers (n = 33) on either a standard-bore (60 cm diameter) or wide-bore (70 cm diameter) 3 T CMR system.

RESULTS

EM simulations and experimental data showed higher (B 1 (+)) homogeneity and lower SAR for optimized RF-shim settings when using the high permittivity pads. The power distribution between the two channels was also much closer to being equal using the pads. EM simulations showed that for all five body models studied, optimized RF-shim settings corresponded to reduced local SAR using high permittivity pads. However, there are also specific, non-optimal RF-shim settings for which the actual SAR using the pads would be higher (up to ~20 %) than that calculated by the CMR system.

CONCLUSIONS

The combination of active (dual transmit) and passive (high permittivity pads) RF shimming shows great promise for increasing image quality for cardiac imaging at 3 T. Optimized RF-shim settings result in increased B 1 (+) homogeneity and reduced SAR with the high permittivity pads: however, there are non-optimal cases in which SAR might be underestimated, and these merit further investigation.

GMctdospp: Description and validation of a CT dose calculation system

PURPOSE

To develop a Monte Carlo (MC)-based computed tomography (CT) dose estimation method with a graphical user interface with options to define almost arbitrary simulation scenarios, to make calculations sufficiently fast for comfortable handling, and to make the software free of charge for general availability to the scientific community.

METHODS

A framework called GMctdospp was developed to calculate phantom and patient doses with the MC method based on the EGSnrc system. A CT scanner was modeled for testing and was adapted to half-value layer, beam-shaping filter, z-profile, and tube-current modulation (TCM). To validate the implemented variance reduction techniques, depth-dose and cross-profile calculations of a static beam were compared against DOSXYZnrc/EGSnrc. Measurements for beam energies of 80 and 120 kVp at several positions of a CT dose-index (CTDI) standard phantom were compared against calculations of the created CT model. Finally, the efficiency of the adapted code was benchmarked against EGSnrc defaults.

RESULTS

The CT scanner could be modeled accurately. The developed TCM scheme was confirmed by the dose measurement. A comparison of calculations to DOSXYZnrc showed no systematic differences. Measurements in a CTDI phantom could be reproduced within 2% average, with a maximal difference of about 6%. Efficiency improvements of about six orders of magnitude were observed for larger organ structures of a chest-examination protocol in a voxelized phantom. In these cases, simulations took 25 s to achieve a statistical uncertainty of ∼0.5%.

CONCLUSIONS

A fast dose-calculation system for phantoms and patients in a CT examination was developed, successfully validated, and benchmarked. Influences of scan protocols, protection method, and other issues can be easily examined with the developed framework.

Validation of a Monte Carlo model used for simulating tube current modulation in computed tomography over a wide range of phantom conditions/challenges

PURPOSE

Monte Carlo (MC) simulation methods have been widely used in patient dosimetry in computed tomography (CT), including estimating patient organ doses. However, most simulation methods have undergone a limited set of validations, often using homogeneous phantoms with simple geometries. As clinical scanning has become more complex and the use of tube current modulation (TCM) has become pervasive in the clinic, MC simulations should include these techniques in their methodologies and therefore should also be validated using a variety of phantoms with different shapes and material compositions to result in a variety of differently modulated tube current profiles. The purpose of this work is to perform the measurements and simulations to validate a Monte Carlo model under a variety of test conditions where fixed tube current (FTC) and TCM were used.

METHODS

A previously developed MC model for estimating dose from CT scans that models TCM, built using the platform of mcnpx, was used for CT dose quantification. In order to validate the suitability of this model to accurately simulate patient dose from FTC and TCM CT scan, measurements and simulations were compared over a wide range of conditions. Phantoms used for testing range from simple geometries with homogeneous composition (16 and 32 cm computed tomography dose index phantoms) to more complex phantoms including a rectangular homogeneous water equivalent phantom, an elliptical shaped phantom with three sections (where each section was a homogeneous, but different material), and a heterogeneous, complex geometry anthropomorphic phantom. Each phantom requires varying levels of x-, y- and z-modulation. Each phantom was scanned on a multidetector row CT (Sensation 64) scanner under the conditions of both FTC and TCM. Dose measurements were made at various surface and depth positions within each phantom. Simulations using each phantom were performed for FTC, detailed x-y-z TCM, and z-axis-only TCM to obtain dose estimates. This allowed direct comparisons between measured and simulated dose values under each condition of phantom, location, and scan to be made.

RESULTS

For FTC scans, the percent root mean square (RMS) difference between measurements and simulations was within 5% across all phantoms. For TCM scans, the percent RMS of the difference between measured and simulated values when using detailed TCM and z-axis-only TCM simulations was 4.5% and 13.2%, respectively. For the anthropomorphic phantom, the difference between TCM measurements and detailed TCM and z-axis-only TCM simulations was 1.2% and 8.9%, respectively. For FTC measurements and simulations, the percent RMS of the difference was 5.0%.

CONCLUSIONS

This work demonstrated that the Monte Carlo model developed provided good agreement between measured and simulated values under both simple and complex geometries including an anthropomorphic phantom. This work also showed the increased dose differences for z-axis-only TCM simulations, where considerable modulation in the x-y plane was present due to the shape of the rectangular water phantom. Results from this investigation highlight details that need to be included in Monte Carlo simulations of TCM CT scans in order to yield accurate, clinically viable assessments of patient dosimetry.

MIDA: A Multimodal Imaging-Based Detailed Anatomical Model of the Human Head and Neck

Computational modeling and simulations are increasingly being used to complement experimental testing for analysis of safety and efficacy of medical devices. Multiple voxel- and surface-based whole- and partial-body models have been proposed in the literature, typically with spatial resolution in the range of 1-2 mm and with 10-50 different tissue types resolved. We have developed a multimodal imaging-based detailed anatomical model of the human head and neck, named "MIDA". The model was obtained by integrating three different magnetic resonance imaging (MRI) modalities, the parameters of which were tailored to enhance the signals of specific tissues: i) structural T1- and T2-weighted MRIs; a specific heavily T2-weighted MRI slab with high nerve contrast optimized to enhance the structures of the ear and eye; ii) magnetic resonance angiography (MRA) data to image the vasculature, and iii) diffusion tensor imaging (DTI) to obtain information on anisotropy and fiber orientation. The unique multimodal high-resolution approach allowed resolving 153 structures, including several distinct muscles, bones and skull layers, arteries and veins, nerves, as well as salivary glands. The model offers also a detailed characterization of eyes, ears, and deep brain structures. A special automatic atlas-based segmentation procedure was adopted to include a detailed map of the nuclei of the thalamus and midbrain into the head model. The suitability of the model to simulations involving different numerical methods, discretization approaches, as well as DTI-based tensorial electrical conductivity, was examined in a case-study, in which the electric field was generated by transcranial alternating current stimulation. The voxel- and the surface-based versions of the models are freely available to the scientific community.

Fluence-to-effective dose conversion coefficients from a Saudi population based phantom for monoenergetic photon beams from 10 keV to 20 MeV

Fluence-to-dose conversion coefficients are important quantities for radiation protection, derived from Monte Carlo simulations of the radiation particles through a stylised phantom or voxel based phantoms. The voxel phantoms have been developed for many ethnic groups for their accurate reflection of the anatomy. In this study, we used the Monte Carlo code MCNPX to calculate the photon fluence-to-effective dose conversion coefficients with a voxel phantom based on the Saudi Arabian male population. Six irradiation geometries, anterior-posterior (AP), posterior-anterior (PA), left lateral (LLAT), right lateral (RLAT), rotational (ROT) and isotropic (ISO) were simulated for monoenergetic photon beams from 10 keV to 20 MeV. We compared the coefficients with the reference values in ICRP Publication 116. The coefficients in the AP and PA geometries match the reference values to 9% and 12% on average as measured by root mean square while those in the LLAT, RLAT ROT and ISO geometries differ, mostly below, from the reference by 23, 22, 15 and 16%, respectively. The torso of the Saudi phantom is wider than the ICRP reference male phantom and likely to cause more attenuation to the lateral beam. The ICRP reference coefficients serve well for the Saudi male population as conservative estimations for the purpose of radiation protection.

Size-specific dose estimate (SSDE) provides a simple method to calculate organ dose for pediatric CT examinations

PURPOSE

To investigate the correlation of size-specific dose estimate (SSDE) with absorbed organ dose, and to develop a simple methodology for estimating patient organ dose in a pediatric population (5-55 kg).

METHODS

Four physical anthropomorphic phantoms representing a range of pediatric body habitus were scanned with metal oxide semiconductor field effect transistor (MOSFET) dosimeters placed at 23 organ locations to determine absolute organ dose. Phantom absolute organ dose was divided by phantom SSDE to determine correlation between organ dose and SSDE. Organ dose correlation factors (CF(organ)(SSDE)) were then multiplied by patient-specific SSDE to estimate patient organ dose. The [CF(organ)(SSDE)) were used to retrospectively estimate individual organ doses from 352 chest and 241 abdominopelvic pediatric CT examinations, where mean patient weight was 22 kg ± 15 (range 5-55 kg), and mean patient age was 6 yrs ± 5 (range 4 months to 23 yrs). Patient organ dose estimates were compared to published pediatric Monte Carlo study results.

RESULTS

Phantom effective diameters were matched with patient population effective diameters to within 4 cm; thus, showing appropriate scalability of the phantoms across the entire pediatric population in this study. Individual CF(organ)(SSDE) were determined for a total of 23 organs in the chest and abdominopelvic region across nine weight subcategories. For organs fully covered by the scan volume, correlation in the chest (average 1.1; range 0.7-1.4) and abdominopelvic region (average 0.9; range 0.7-1.3) was near unity. For organ/tissue that extended beyond the scan volume (i.e., skin, bone marrow, and bone surface), correlation was determined to be poor (average 0.3; range: 0.1-0.4) for both the chest and abdominopelvic regions, respectively. A means to estimate patient organ dose was demonstrated. Calculated patient organ dose, using patient SSDE and CF(organ)(SSDE), was compared to previously published pediatric patient doses that accounted for patient size in their dose calculation, and was found to agree in the chest to better than an average of 5% (27.6/26.2) and in the abdominopelvic region to better than 2% (73.4/75.0).

CONCLUSIONS

For organs fully covered within the scan volume, the average correlation of SSDE and organ absolute dose was found to be better than ± 10%. In addition, this study provides a complete list of organ dose correlation factors (CF(organ)(SSDE)) for the chest and abdominopelvic regions, and describes a simple methodology to estimate individual pediatric patient organ dose based on patient SSDE.