Patient-specific radiation dose and cancer risk estimation in CT: part I. development and validation of a Monte Carlo program

An inventory of patient-image based risk/dose, image quality and body habitus/size metrics for adult abdomino-pelvic CT protocol optimisation

PURPOSE

Patient-specific protocol optimisation in abdomino-pelvic Computed Tomography (CT) requires measurement of body habitus/size (BH), sensitivity-specificity (surrogates image quality (IQ) metrics) and risk (surrogates often dose quantities) (RD). This work provides an updated inventory of metrics available for each of these three categories of optimisation variables derivable directly from patient measurements or images. We consider objective IQ metrics mostly in the spatial domain (i.e., those related directly to sharpness, contrast, noise quantity/texture and perceived detectability as these are used by radiologists to assess the acceptability or otherwise of patient images in practice).

MATERIALS AND METHODS

The search engine used was PubMed with the search period being 2010-2024. The key words used were: 'comput* tomography', 'CT', 'abdom*', 'dose', 'risk', 'SSDE', 'image quality', 'water equivalent diameter', 'size', 'body composition', 'habit*', 'BMI', 'obes*', 'overweight'. Since BH is critical for patient specific optimisation, articles correlating RD vs BH, and IQ vs BH were reviewed.

RESULTS

The inventory includes 11 BH, 12 IQ and 6 RD metrics. 25 RD vs BH correlation studies and 9 IQ vs BH correlation studies were identified. 7 articles in the latter group correlated metrics from all three categories concurrently.

CONCLUSIONS

Protocol optimisation should be fine-tuned to the level of the individual patient and particular clinical query. This would require a judicious choice of metrics from each of the three categories. It is suggested that, for increased utility in clinical practice, more future optimisation studies be clinical task based and involve the three categories of metrics concurrently.

Introducing fitting models for estimating age-specific dose and effective dose in paediatric patients undergoing head, chest and abdomen-pelvis imaging protocols: a patient study

INTRODUCTION

Concerns regarding the adverse consequences of radiation have increased due to the expanded application of computed tomography (CT) in medical practice. Certain studies have indicated that the radiation dosage depends on the anatomical region, the imaging technique employed and patient-specific variables. The aim of this study is to present fitting models for the estimation of age-specific dose estimates (ASDE), in the same direction of size-specific dose estimates, and effective doses based on patient age, gender and the type of CT examination used in paediatric head, chest and abdomen-pelvis imaging.

METHODS

A total of 583 paediatric patients were included in the study. Radiometric data were gathered from DICOM files. The patients were categorised into five distinct groups (under 15 years of age), and the effective dose, organ dose and ASDE were computed for the CT examinations involving the head, chest and abdomen-pelvis. Finally, the best fitting models were presented for estimation of ASDE and effective doses based on patient age, gender and the type of examination.

RESULTS

The ASDE in head, chest, and abdomen-pelvis CT examinations increases with increasing age. As age increases, the effective dose in head and abdomen-pelvis CT scans decreased. However, for chest scans, the effective dose initially showed a decreasing trend until the first year of life; after that, it increases in correlation with age.

CONCLUSIONS

Based on the presented fitting model for the ASDE, these CT scan quantities depend on factors such as patient age and the type of CT examination. For the effective dose, the gender was also included in the fitting model. By utilising the information about the scan type, region and age, it becomes feasible to estimate the ASDE and effective dose using the models provided in this study.

Accuracy of patient-specific CT organ doses from Monte Carlo simulations: influence of CT-based voxel models

Monte Carlo simulations using patient CT images as input are the gold standard to perform patient-specific dosimetry. However, in standard clinical practice patient's CT images are limited to the reconstructed CT scan range. In this study, organ dose calculations were performed with ImpactMC for chest and cardiac CT using whole-body and anatomy-specific voxel models to estimate the accuracy of CT organ doses based on the latter model. When the 3D patient model is limited to the CT scan range, CT organ doses from Monte Carlo simulations are the most accurate for organs entirely in the field of view. For these organs only the radiation dose related to scatter from the rest of the body is not incorporated. For organs lying partially outside the field of view organ doses are overestimated by not accounting for the non-irradiated tissue mass. This overestimation depends strongly on the amount of the organ volume located outside the field of view. To get a more accurate estimation of the radiation dose to these organs, the ICRP reference organ masses and densities could form a solution. Except for the breast, good agreement in dose was found for most organs. Voxel models generated from clinical CT examinations do not include the overscan in the z-direction. The availability of whole-body voxel models allowed to study this influence as well. As expected, overscan induces slightly higher organ doses.

Assessing and improving radiation safety in cardiac catheterization: a study from Cairo University Hospital

BACKGROUND

Catheter laboratories are high-radiation exposure environments, especially during X-ray procedures like percutaneous transluminal coronary angioplasty and electrophysiological studies. Radiation exposure poses risks of stochastic (e.g., cancer) and deterministic (e.g., skin changes) effects. This study assessed radiation safety and health practices in a cardiac catheterization unit to optimize radiation safety. A cross-sectional study in Cairo University Hospital (March-September 2019) evaluated 700 patients and healthcare workers. Real-time radiation measurements, educational lectures, and radiation protection measures were implemented in three phases. Data on radiation exposure, procedures, and compliance were collected and analyzed.

RESULTS

The total procedure time and fluoroscopy time per cardiologist did not significantly differ between phases, but there was a statistically significant reduction in the mean total cumulative radiation doses between Phase I and Phase III for cardiologists (P = 0.013). Among nurses and technicians, there was no significant difference in radiation doses between the two phases. Significant correlations were found between operators' radiation doses, procedure time, and fluoroscopy time. Patients' radiation doses decreased significantly from Phase I to Phase III, with correlations between dose, procedure time, and gender. Compliance with radiation protection measures was suboptimal.

CONCLUSIONS

Compliance with radiation safety standards in the cardiac catheterization unit at the Cairo University Hospital needs improvement. The study highlights the importance of adhering to radiation safety principles and optimizing protective measures to reduce radiation exposure for both patients and healthcare personnel. Despite low compliance, significant reductions in radiation doses were achieved with increased awareness and adherence to specific protection measures. Future efforts should focus on enhancing radiation safety protocols and organ-specific radiation impact assessments.

Effect of tin spectral filtration on organ and effective dose in CT colonography and CT lung cancer screening

BACKGROUND

Studies of tin spectral filtration have demonstrated potential in reducing radiation dose while maintaining image quality for unenhanced computed tomography (CT) scans. The extent of dose reduction, however, was commonly measured using the change in the scanner's reported CTDIvol . This method does not account for how tin filtration affects patient organ and effective dose.

PURPOSE

To investigate the effect of tin filtration on patient organ and effective dose for CT Lung Cancer Screening (LCS) and CT Colonography (CTC).

METHODS

A previously-developed Monte Carlo program was adapted to model a 96-row CT scanner (Somatom Force, Siemens Healthineers) with tin filtration capabilities at 100 kV (100Sn) and 150 kV (150Sn). The program was then validated using experimental CTDIvol measurements at all available kV (70-150 kV) and tin-filtered kV options (100Sn and 150Sn). After validation, the program simulated LCS scans of the chest and CTC scan of the abdomen-pelvis for a population of 53 computational patient models from the extended cardiac-torso family. Each scan was performed using three different spectra: 120 kV, 100Sn, and 150Sn. CTDIvol -normalized organ doses and DLP-normalized effective doses, commonly referred to as dose conversion factors, were compared between the different spectra.

RESULTS

For all LCS and CTC scans, CTDIvol -normalized organ doses and DLP-normalized effective doses increased with increasing beam hardness (120 kV, 100Sn, 150 Sn). For LCS, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 9%, with organ dose increases of 8% to lung, 5% to breast, 15% to thyroid, and 3% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 20%, with organ dose increases of 16%, 18%, 26%, and 12% to these same organs, respectively. For CTC, relative for 120 kV, conversion factors for 100Sn produced a median increase in effective dose of 12%, with organ dose increases of 9% to colon, 10% to liver, 11% to stomach, and 4% to skin. Conversion factors for 150Sn produced a median increase in effective dose of 21%, with organ dose increases of 16%, 17%, 19%, and 10% to these same organs, respectively.

CONCLUSIONS

Results show that dose conversion factors are greater when using tin filtration and should be considered when evaluating tin's potential for dose reduction.

Voxel model of a rabbit: assessment of absorbed doses in organs after CT examination performed by two different protocols

The objective of this work was to assess absorbed doses in organs and tissues of a rabbit, following computed tomography (CT) examinations, using a dedicated 3D voxel model. Absorbed doses in relevant organs were calculated using the MCNP5 Monte Carlo software. Calculations were perfomed for two standard CT protocols, using tube voltages of 110 kVp and 130 kVp. Absorbed doses were calculated in 11 organs and tissues, i.e., skin, bones, brain, muscles, heart, lungs, liver, spleen, kidney, testicles, and fat tissue. The doses ranged from 15.3 to 28.3 mGy, and from 40.2 to 74.3 mGy, in the two investigated protocols. The organs that received the highest dose were bones and kidneys. In contrast, brain and spleen were organs that received the smallest doses. Doses in organs which are stretched along the body did not change significantly with distance. On the other hand, doses in organs which are localized in the body showed maximums and minimums. Using the voxel model, it is possible to calculate the dose distribution in the rabbit's body after CT scans, and study the potential biological effects of CT doses in certain organs. The voxel model presented in this work can be used to calculated doses in all radiation experiments in which rabbits are used as experimental animals.

A scanner-specific framework for simulating CT images with tube current modulation

Although tube current modulation (TCM) is routinely implemented in modern computed tomography (CT) scans, no existing CT simulator is capable of generating realistic images with TCM. The goal of this study was to develop such a framework to (1) facilitate patient-specific optimization of TCM parameters and (2) enable future virtual imaging trials (VITs) with more clinically realistic image quality and x-ray flux distributions. The framework was created by developing a TCM module and integrating it with an existing CT simulator (DukeSim). The developed module utilizes scanner-calibrated TCM parameters and two localizer radiographs to compute the mAs for each simulated CT projection. This simulation pipeline was validated in two parts. First, DukeSim was validated in the context of a commercial scanner with TCM (SOMATOM Force, Siemens Healthineers) by imaging a physical CT phantom (Mercury, Sun Nuclear) and its computational analogue. Second, the TCM module was validated by imaging a computational anthropomorphic phantom (ATOM, CIRS) using DukeSim with real and module-generated TCM profiles. The validation demonstrated DukeSim's realism in terms of noise magnitude, noise texture, spatial resolution, and image contrast (with average differences of 0.38%, 6.31%, 0.43%, and -9 HU, respectively). It also demonstrated the TCM module's realism in terms of projection-level mAs and resulting noise magnitude (2.86% and -2.60%, respectively). Finally, the framework was applied to a pilot VIT simulating images of three computational anthropomorphic phantoms (XCAT, with body mass indices (BMIs) of 24.3, 28.2, and 33.0) under five different TCM settings. The optimal TCM for each phantom was characterized based on various criteria, such as minimizing mAs or maximizing image quality. 'Very Weak' TCM minimized noise for the 24.3 BMI phantom, while 'Very Strong' TCM minimized noise for the 33.0 BMI phantom. This illustrates the utility of the developed framework for future optimization studies of TCM parameters and, more broadly, large-scale VITs with scanner-specific TCM.

Patient-Informed Organ Dose Estimation in Clinical CT: Implementation and Effective Dose Assessment in 1048 Clinical Patients

OBJECTIVE. The purpose of this study is to comprehensively implement a patient-informed organ dose monitoring framework for clinical CT and compare the effective dose (ED) according to the patient-informed organ dose with ED according to the dose-length product (DLP) in 1048 patients. MATERIALS AND METHODS. Organ doses for a given examination are computed by matching the topogram to a computational phantom from a library of anthropomorphic phantoms and scaling the fixed tube current dose coefficients by the examination volume CT dose index (CTDIvol) and the tube-current modulation using a previously validated convolution-based technique. In this study, the library was expanded to 58 adult, 56 pediatric, five pregnant, and 12 International Commission on Radiological Protection (ICRP) reference models, and the technique was extended to include multiple protocols, a bias correction, and uncertainty estimates. The method was implemented in a clinical monitoring system to estimate organ dose and organ dose-based ED for 647 abdomen-pelvis and 401 chest examinations, which were compared with DLP-based ED using a t test. RESULTS. For the majority of the organs, the maximum errors in organ dose estimation were 18% and 8%, averaged across all protocols, without and with bias correction, respectively. For the patient examinations, DLP-based ED was significantly different from organ dose-based ED by as much as 190.9% and 234.7% for chest and abdomen-pelvis scans, respectively (mean, 9.0% and 24.3%). The differences were statistically significant (p < .001) and exhibited overestimation for larger-sized patients and underestimation for smaller-sized patients. CONCLUSION. A patient-informed organ dose estimation framework was comprehensively implemented applicable to clinical imaging of adult, pediatric, and pregnant patients. Compared with organ dose-based ED, DLP-based ED may overestimate effective dose for larger-sized patients and underestimate it for smaller-sized patients.

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

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

AUTOMATIC BRAIN DOSE ESTIMATION IN COMPUTED TOMOGRAPHY USING PATIENT DICOM IMAGES

This study aims to develop an Automatic Brain Dose Estimation (ABDE) methodology for head computed tomography examinations. The ABDE is to be applied first to an anthropomorphic Alderson phantom to obtain a Correction factor (Cf) between the ABDE and the direct absorbed brain dose using dosemeters positioned within the anthropomorphic phantom. Then, in order to estimate the correct brain dose for patient, the Cf was multiplied by the mean ABDE values for each patient. Results were compared to those registered with a mathematical simulation phantom using CT-Expo V 2.4 software. Results showed no significant difference between the correct ABDE values and the CT-Expo values with a mean percent difference of 2.54 ± 0.01%. In conclusion, ABDE yields a correct estimation of brain dose, taking into account the size and attenuation of the irradiated region. Thus, it is clinically recommended for accurate patient brain dose assessment.

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities.

A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing

PURPOSE

One technical barrier to patient-specific computed tomography (CT) dosimetry has been the lack of computational tools for the automatic patient-specific multi-organ segmentation of CT images and rapid organ dose quantification. When previous CT images are available for the same body region of the patient, the ability to obtain patient-specific organ doses for CT - in a similar manner as radiation therapy treatment planning - will open the door to personalized and prospective CT scan protocols. This study aims to demonstrate the feasibility of combining deep-learning algorithms for automatic segmentation of multiple radiosensitive organs from CT images with the GPU-based Monte Carlo rapid organ dose calculation.

METHODS

A deep convolutional neural network (CNN) based on the U-Net for organ segmentation is developed and trained to automatically delineate multiple radiosensitive organs from CT images. Two databases are used: The lung CT segmentation challenge 2017 (LCTSC) dataset that contains 60 thoracic CT scan patients, each consisting of five segmented organs, and the Pancreas-CT (PCT) dataset, which contains 43 abdominal CT scan patients each consisting of eight segmented organs. A fivefold cross-validation method is performed on both sets of data. Dice similarity coefficients (DSCs) are used to evaluate the segmentation performance against the ground truth. A GPU-based Monte Carlo dose code, ARCHER, is used to calculate patient-specific CT organ doses. The proposed method is evaluated in terms of relative dose errors (RDEs). To demonstrate the potential improvement of the new method, organ dose results are compared against those obtained for population-average patient phantoms used in an off-line dose reporting software, VirtualDose, at Massachusetts General Hospital.

RESULTS

The median DSCs are found to be 0.97 (right lung), 0.96 (left lung), 0.92 (heart), 0.86 (spinal cord), 0.76 (esophagus) for the LCTSC dataset, along with 0.96 (spleen), 0.96 (liver), 0.95 (left kidney), 0.90 (stomach), 0.87 (gall bladder), 0.80 (pancreas), 0.75 (esophagus), and 0.61 (duodenum) for the PCT dataset. Comparing with organ dose results from population-averaged phantoms, the new patient-specific method achieved smaller absolute RDEs (mean ± standard deviation) for all organs: 1.8% ± 1.4% (vs 16.0% ± 11.8%) for the lung, 0.8% ± 0.7% (vs 34.0% ± 31.1%) for the heart, 1.6% ± 1.7% (vs 45.7% ± 29.3%) for the esophagus, 0.6% ± 1.2% (vs 15.8% ± 12.7%) for the spleen, 1.2% ± 1.0% (vs 18.1% ± 15.7%) for the pancreas, 0.9% ± 0.6% (vs 20.0% ± 15.2%) for the left kidney, 1.7% ± 3.1% (vs 19.1% ± 9.8%) for the gallbladder, 0.3% ± 0.3% (vs 24.2% ± 18.7%) for the liver, and 1.6% ± 1.7% (vs 19.3% ± 13.6%) for the stomach. The trained automatic segmentation tool takes <5 s per patient for all 103 patients in the dataset. The Monte Carlo radiation dose calculations performed in parallel to the segmentation process using the GPU-accelerated ARCHER code take <4 s per patient to achieve <0.5% statistical uncertainty in all organ doses for all 103 patients in the database.

CONCLUSION

This work shows the feasibility to perform combined automatic patient-specific multi-organ segmentation of CT images and rapid GPU-based Monte Carlo dose quantification with clinically acceptable accuracy and efficiency.

Estimating patient water equivalent diameter from CT localizer images - A longitudinal and multi-institutional study of the stability of calibration parameters

PURPOSE

Water equivalent diameter (WED) is a robust patient-size descriptor. Localizer-based WED estimation is less sensitive to truncation errors resulting from limited field of view, and produces WED estimates at different locations within one localizer radiograph, prior to the initiation of axial scans. This method is considered difficult to implement by the clinical community due to the necessary calibration between localizer pixel values (LPV) and attenuation, and the unknown stability of calibration results across scanners and over time. We investigated the stability of calibration results across 25 computed tomography (CT) scanners from three medical centers, and their stability over 3 ∼ 29 months for 14 of those scanners.

METHODS

Localizer and axial images of ACR and body computed tomography dose index phantoms were acquired, using routine clinical techniques (120 kV and lateral localizers) on each of the 25 CT scanners: 8 GE scanners (CT750HD, VCT, and Revolution), 8 Siemens scanners (Definition AS, Force, Flash, and Edge), 5 Canon scanners (Aquilion-One, Aquilion-Prime80, and Aquilion-64), and 4 Philips scanners (iCT 256, iQon, and Ingenuity). By associating axial images with the corresponding localizer lines, the relationship between the scaled water equivalent area (WEA) and averaged LPV were established through regression analysis.

RESULTS

Linear relationships between the scaled WEA and the averaged LPV were observed in all 25 CT scanners ( R 2 > 0.999 ). Calibration parameters were similar for CT scanners from the same vendor: the coefficients of variation (COV) were ≤ 1% in all four vendor groups for the calibration slope, and < 7% for the intercept. By analyzing the deviation of WED resulted from errors in the calibration slope or intercept alone, we derived the tolerance ranges for the slope or intercept for a given WED error level. The variation of slope and intercept from different CT scanners of the same vendor introduced <±2.5% error in the estimated WED for subjects of 20 and 30-cm WED. The calibration parameters remained stable over time, with the maximum deviations all within the boundary values that introduce ±2.5% error in the estimated WED for subjects of 20 and 30-cm WED.

CONCLUSIONS

The stability in calibration results among CT scanners of the same vendor and over time demonstrated the feasibility of implementing WED estimation for routine clinical use.

Assessment of uncertainties associated with Monte Carlo-based personalized dosimetry in clinical CT examinations

The clinical value of x-ray computed tomography (CT) has skyrocketed in the last decade while at the same time being the main source of medical exposure to the population. Concerns regarding the potential health hazards associated with the use of ionizing radiation were raised and an appropriate estimation of absorbed dose to patients is highly desired. In this work, we aim to validate our developed Monte Carlo CT simulator using in-phantom dose measurements and further assess the impact of personalized scan-related parameters on dosimetric calculations. We developed a Monte Carlo-based CT simulator for personalized organ level dose calculations, in which the CT source model, patient-specific computational model and personalized scanning protocol were integrated. The CT simulator was benchmarked using an ionization chamber and standard CT Dose Index phantom while the dosimetry methodology was validated through experimental measurements using thermoluminescent dosimeters (TLDs) embedded within an anthropomorphic phantom. Patient-specific scan protocols extracted from CT raw data and DICOM image metadata, respectively, were fed as input into the CT simulator to calculate individualized dose profiles. Thereby, the dosimetric uncertainties associated with using different protocol-related parameters were investigated. The absolute absorbed dose difference between measurements and simulations using the ionization chamber was less than 3%. In the case of the anthropomorphic phantom, the absolute absorbed dose difference between simulations and TLD measurements ranged from  -8.3% to 22%, with a mean absolute difference of 14% while the uncertainties of protocol-related input parameters introduced an extra absolute error of 15% to the simulated results compared with TLD measurements. The developed methodology can be employed for accurate estimation of organ level dose from clinical CT examinations. The validated methodology can be further developed to produce an accurate MC simulation model with a reduced computational burden.

SHAPE ESTIMATION OF BOWTIE FILTERS BASED ON THE LUMINESCENCE FROM POLYETHYLENE TEREPHTHALATE RESIN BY X-RAY IRRADIATION

In this study, we devised a novel method estimating the bowtie filter shapes by imaging luminescence from a polyethylene terephthalate (PET) resin with X-ray irradiation in a computed tomography (CT) scanner. The luminescence distribution of the PET resin corresponding to the thickness of bowtie filter was imaged using a charge-coupled device camera. On the assumption that the material of bowtie filter is aluminium (Al), the shape of bowtie filters was estimated from the correlation between Al attenuation curves and the angular-dependent luminance attenuation profiles according to the thickness of bowtie filters. Dose simulations based on the estimated bowtie filter shapes were performed using head and body PMMA phantoms with 16 and 32 cm in diameter. The simulated values of head and body weighted CT dose index (CTDIw) based on bowtie filter shape by the luminescence imaging method agreed within ~9% with the measured values by a dosemeter.

A real-time Monte Carlo tool for individualized dose estimations in clinical CT

The increasing awareness of the adverse effects associated with radiation exposure in computed tomography (CT) has necessesitated the quantification of dose delivered to patients for better risk assessment in the clinic. The current methods for dose quantification used in the clinic are approximations, lacking realistic models for the irradiation conditions utilized in the scan and the anatomy of the patient being imaged, which limits their relevance for a particular patient. The established gold-standard technique for individualized dose quantification uses Monte Carlo (MC) simulations to obtain patient-specific estimates of organ dose in anatomically realistic computational phantoms to provide patient-specific estimates of organ dose. Although accurate, MC simulations are computationally expensive, which limits their utility for time-constrained applications in the clinic. To overcome these shortcomings, a real-time GPU-based MC tool based on FDA's MC-GPU framework was developed for patient and scanner-specific dosimetry in the clinic. The tool was validated against (1) AAPM's TG-195 reference datasets and (2) physical measurements of dose acquired using TLD chips in adult and pediatric anthropomorphic phantoms. To demonstrate its utility towards providing individualized dose estimates, it was integrated with an automatic segmentation method for generating patient-specific models, which were then used to estimate patient- and scanner-specific organ doses for a select population of 50 adult patients using a clinically relevant CT protocol. The organ dose estimates were compared to corresponding dose estimates from a previously validated MC method based on Penelope. The dose estimates from our MC tool agreed within 5% for all organs (except thyroid) tabulated by TG-195 and within 10% for all TLD locations in the adult and pediactric phantoms, across all validation cases. Compared against Penelope, the organ dose estimates agreed within 3% on average for all organs in the patient population study. The average run duration for each patient was estimated at 23.79 s, representing a significant speedup (~700×) over existing non-parallelized MC methods. The accuracy of dose estimates combined with a significant improvement in execution times suggests a feasible solution utilizing the proposed MC tool for real-time individualized dosimetry in the clinic.

Organ doses from CT localizer radiographs: Development, validation, and application of a Monte Carlo estimation technique

PURPOSE

The purpose of this study was to simulate and validate organ doses from different computed tomography (CT) localizer radiograph geometries using Monte Carlo methods for a population of patients.

METHODS

A Monte Carlo method was developed to estimate organ doses from CT localizer radiographs using PENELOPE. The method was validated by comparing dosimetry estimates with measurements using an anthropomorphic phantom imbedded with thermoluminescent dosimeters (TLDs) scanned on a commercial CT system (Siemens SOMATOM Flash). The Monte Carlo simulation platform was then applied to conduct a population study with 57 adult computational phantoms (XCAT). In the population study, clinically relevant chest localizer protocols were simulated with the x-ray tube in anterior-posterior (AP), right lateral, and PA positions. Mean organ doses and associated standard deviations (in mGy) were then estimated for all simulations. The obtained organ doses were studied as a function of patient chest diameter. Organ doses for breast and lung were compared across different views and represented as a percentage of organ doses from rotational CT scans.

RESULTS

The validation study showed an agreement between the Monte Carlo and physical TLD measurements with a maximum percent difference of 15.5% and a mean difference of 3.5% across all organs. The XCAT population study showed that breast dose from AP localizers was the highest with a mean value of 0.24 mGy across patients, while the lung dose was relatively consistent across different localizer geometries. The organ dose estimates were found to vary across the patient population, partially explained by the changes in the patient chest diameter. The average effective dose was 0.18 mGy for AP, 0.09 mGy for lateral, and 0.08 mGy for PA localizer.

CONCLUSION

A platform to estimate organ doses in CT localizer scans using Monte Carlo methods was implemented and validated based on comparison with physical dose measurements. The simulation platform was applied to a virtual patient population, where the localizer organ doses were found to range within 0.4%-8.6% of corresponding organ doses for a typical CT scan, 0.2%-3.3% of organ doses for a CT pulmonary angiography scan, and 1.1%-20.8% of organ doses for a low-dose lung cancer screening scan.

DukeSim: A Realistic, Rapid, and Scanner-Specific Simulation Framework in Computed Tomography

The purpose of this study was to develop a CT simulation platform that is: 1) compatible with voxel-based computational phantoms; 2) capable of modeling the geometry and physics of commercial CT scanners; and 3) computationally efficient. Such a simulation platform is designed to enable the virtual evaluation and optimization of CT protocols and parameters for achieving a targeted image quality while reducing radiation dose. Given a voxelized computational phantom and a parameter file describing the desired scanner and protocol, the developed platform DukeSim calculates projection images using a combination of ray-tracing and Monte Carlo techniques. DukeSim includes detailed models for the detector quantum efficiency, quantum and electronic noise, detector crosstalk, subsampling of the detector and focal spot areas, focal spot wobbling, and the bowtie filter. DukeSim was accelerated using GPU computing. The platform was validated using physical and computational versions of a phantom (Mercury phantom). Clinical and simulated CT scans of the phantom were acquired at multiple dose levels using a commercial CT scanner (Somatom Definition Flash; Siemens Healthcare). The real and simulated images were compared in terms of image contrast, noise magnitude, noise texture, and spatial resolution. The relative error between the clinical and simulated images was less than 1.4%, 0.5%, 2.6%, and 3%, for image contrast, noise magnitude, noise texture, and spatial resolution, respectively, demonstrating the high realism of DukeSim. The runtime, dependent on the imaging task and the hardware, was approximately 2-3 minutes per rotation in our study using a computer with 4 GPUs. DukeSim, when combined with realistic human phantoms, provides the necessary toolset with which to perform large-scale and realistic virtual clinical trials in a patient and scanner-specific manner.

Development and validation of an open source Monte Carlo dosimetry model for wide-beam CT scanners using Fluka

PURPOSE

Development and validation of an open source Fluka-based Monte Carlo source model for diagnostic patient dose calculations.

METHODS

A framework to simulate a computed tomography (CT) scanner using Fluka Monte Carlo particle transport code was developed. The General Electric (GE) Revolution scanner with the large body filter and 120 kV tube potential was characterized using measurements. The model was validated on benchmark CT test problems and on dose measurements in computed tomography dose index (CTDI) and anthropomorphic phantoms. Axial and helical operation modes with provision for tube current modulation (TCM) were implemented. The particle simulations in Fluka were accelerated by executing them on a high-performance computing cluster.

RESULTS

The simulation results agreed to better than an average of 4% of the reference simulation results from the AAPM Report 195 test scenarios, namely: better than 2% for both test problems in case 4 using the PMMA phantom, and better than 5% of the reference result for 14 of 17 organs in case 5, and within 10% for the three remaining organs. The Fluka simulation results agreed to better than 2% of the air kerma measured in-air at isocenter of the GE Revolution scanner. The simulated air kerma in the center of the CTDI phantom overestimated the measurement by 7.5% and a correction factor was introduced to account for this. The simulated mean absorbed doses for a chest scan of the pediatric anthropomorphic phantom was completed in ~9 min and agreed to within the 95% CI for bone, soft tissue, and lung measurements made using MOSFET detectors for fixed current axial and helical scans as well as helical scan with TCM.

CONCLUSION

A Fluka-based Monte Carlo simulation model of axial and helical acquisition techniques using a wide-beam collimation CT scanner demonstrated good agreement between measured and simulated results for both fixed current and TCM in complex and simple geometries. Code and dataset will be made available at https://github.com/chezhia/FLUKA_CT.

Organ doses evaluation for chest computed tomography procedures with TL dosimeters: Comparison with Monte Carlo simulations

Purpose

To evaluate organ doses in routine and low‐dose chest computed tomography (CT) protocols using an experimental methodology. To compare experimental results with results obtained by the National Cancer Institute dosimetry system for CT (NCICT) organ dose calculator. To address the differences on organ dose measurements using tube current modulation (TCM) and fixed tube current protocols.

Methods

An experimental approach to evaluate organ doses in pediatric and adult anthropomorphic phantoms using thermoluminescent dosimeters (TLDs) was employed in this study. Several analyses were performed in order to establish the best way to achieve the main results in this investigation. The protocols used in this study were selected after an analysis of patient data collected from the Institute of Radiology of the School of Medicine of the University of São Paulo (InRad). The image quality was evaluated by a radiologist from this institution. Six chest adult protocols and four chest pediatric protocols were evaluated. Lung doses were evaluated for the adult phantom and lung and thyroid doses were evaluated for the pediatric phantom. The irradiations were performed using both a GE and a Philips CT scanner. Finally, organ doses measured with dosimeters were compared with Monte Carlo simulations performed with NCICT.

Results

After analyzing the data collected from all CT examinations performed during a period of 3 yr, the authors identified that adult and pediatric chest CT are among the most applied protocol in patients in that clinical institution, demonstrating the relevance on evaluating organ doses due to these examinations. With regards to the scan parameters adopted, the authors identified that using 80 kV instead of 120 kV for a pediatric chest routine CT, with TCM in both situations, can lead up to a 28.7% decrease on the absorbed dose. Moreover, in comparison to the standard adult protocol, which is performed with fixed mAs, TCM, and ultra low‐dose protocols resulted in dose reductions of up to 35.0% and 90.0%, respectively. Finally, the percent differences found between experimental and Monte Carlo simulated organ doses were within a 20% interval.

Conclusions

The results obtained in this study measured the impact on the absorbed dose in routine chest CT by changing several scan parameters while the image quality could be potentially preserved.

Two-step validation of a Monte Carlo dosimetry framework for general radiology

The Monte Carlo technique is considered gold standard when it comes to patient-specific dosimetry. Any newly developed Monte Carlo simulation framework, however, has to be carefully calibrated and validated prior to its use. For many researchers this is a tedious work. We propose a two-step validation procedure for our newly built Monte Carlo framework and provide all input data to make it feasible for future related application by the wider community. The validation was at first performed by benchmarking against simulation data available in literature. The American Association of Physicists in Medicine (AAPM) report of task group 195 (case 2) was considered most appropriate for our application. Secondly, the framework was calibrated and validated against experimental measurements for trunk X-ray imaging protocols using a water phantom. The dose results obtained from all simulations and measurements were compared. Our Monte Carlo framework proved to agree with literature data, by showing a maximal difference below 4% to the AAPM report. The mean difference with the water phantom measurements was around 7%. The statistical uncertainty for clinical applications of the dosimetry model is expected to be within 10%. This makes it reliable for clinical dose calculations in general radiology. Input data and the described procedure allow for the validation of other Monte Carlo frameworks.

Estimating the Patient-specific Dose to the Thyroid and Breasts and Overall Risk in Chest CT When Using Organ-based Tube Current Modulation

Purpose To assess the potential dose reduction to the thyroid and breasts in chest computed tomography (CT) with organ-based tube current modulation (OBTCM). Materials and Methods In this retrospective study (from January 2015 to December 2016), the location of the breasts with respect to the reduced tube current zone was determined. With Monte Carlo simulations, patient-specific dose distributions of chest CT scans were calculated for 50 female patients (mean age, 53.7 years ± 17.5; range, 20-80 years). The potential dose reduction with OBTCM was assessed. In addition, simulations of clinical OBTCM scans were made for 17 of the 50 female patients (mean age, 43.8 years ± 17.1; range, 20-69 years). Posterior organs in the field of view were analyzed and lifetime attributable risk (LAR) of cancer incidence and mortality was estimated. Image quality between standard CT and OBTCM scans was compared. Results No women had all breast tissue within the reduced tube current zone. Dose reductions of 18% in the thyroid and 9% in the breasts were observed, whereas the doses in lung, liver, and kidney were 17%, 11%, and 26% higher. Overall, the LAR for cancer incidence was not significantly different between conventional and OBTCM scanning (P = .06). Image quality improved with OBTCM (P < .002). Conclusion The potential benefit of OBTCM to the female breast in chest CT is overestimated because of a limited reduced tube current zone; despite a 9% dose reduction to the female breast, posterior organs will absorb up to 26% more radiation, resulting in no reduction in radiation-induced malignancies. ^© RSNA, 2018.

Optimizing Communication With Parents on Benefits and Radiation Risks in Pediatric Imaging

Effective radiation risk communication is a core competency for radiology care providers and can prevent and resolve potential conflicts while helping achieve effective public health safeguards. The authors present a synopsis of the challenges to holding such dialogue and review published methods for strengthening and maintaining this discourse. Twelve strategies are discussed in this article that can help alleviate concerns about the iatrogenic risk associated with medical imaging using radiation exposure.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies.

Radiation risk index for pediatric CT: a patient-derived metric

BACKGROUND

There is a benefit in characterizing radiation-induced cancer risk in pediatric chest and abdominopelvic CT: a singular metric that represents the whole-body radiation burden while also accounting for age, gender and organ sensitivity.

OBJECTIVE

To compute an index of radiation risk for pediatric chest and abdominopelvic CT.

MATERIALS AND METHODS

Using a protocol approved by our institutional review board, 42 pediatric patients (age: 0-16 years, weight: 2-80 kg) were modeled into virtual whole-body anatomical models. Organ doses were estimated for clinical chest and abdominopelvic CT examinations of the patients using validated Monte Carlo simulations of two major scanner models. Using age-, size- and gender-specific organ risk coefficients, the values were converted to normalized effective dose (by dose length product) (denoted as the k factor) and a normalized risk index (denoted as the q factor). An analysis was performed to determine how these factors are correlated with patient age and size for both males and females to provide a strategy to better characterize individualized risk.

RESULTS

The k factor was found to be exponentially correlated with the average patient diameter. For both genders, the q factor also exhibited an exponential relationship with both the average patient diameter and with patient age. For both factors, the differences between the scanner models were less than 8%.

CONCLUSION

The study defines a whole-body radiation risk index for chest and abdominopelvic CT imaging, that incorporates individual estimated organ dose values, organ radiation sensitivity, patient size, exposure age and patient gender. This indexing metrology enables the assessment and potential improvement of chest and abdominopelvic CT performance through surveillance of practice dose profiles across patients and may afford improved informed communication.

Size-based quality-informed framework for quantitative optimization of pediatric CT

The purpose of this study was to formulate a systematic, evidence-based method to relate quantitative diagnostic performance to radiation dose, enabling a multidimensional system to optimize computed tomography imaging across pediatric populations. Based on two prior foundational studies, radiation dose was assessed in terms of organ doses, effective dose ([Formula: see text]), and risk index for 30 patients within nine color-coded pediatric age-size groups as a function of imaging parameters. The cases, supplemented with added noise and simulated lesions, were assessed in terms of nodule detection accuracy in an observer receiving operating characteristic study. The resulting continuous accuracy-dose relationships were used to optimize individual scan parameters. Before optimization, the nine protocols had a similar [Formula: see text] of [Formula: see text] with accuracy decreasing from 0.89 for the youngest patients to 0.67 for the oldest. After optimization, a consistent target accuracy of 0.83 was established for all patient categories with [Formula: see text] ranging from 1 to 10 mSv. Alternatively, isogradient operating points targeted a consistent ratio of accuracy-per-unit-dose across the patient categories. The developed model can be used to optimize individual scan parameters and provide for consistent diagnostic performance across the broad range of body sizes in children.

Organ dose variability and trends in tomosynthesis and radiography

The purpose of this study was to investigate relationships between patient attributes and organ dose for a population of computational phantoms for 20 tomosynthesis and radiography protocols. Organ dose was estimated from 54 adult computational phantoms (age: 18 to 78 years, weight 52 to 117 kg) using a validated Monte-Carlo simulation (PENELOPE) of a system capable of performing tomosynthesis and radiography. The geometry and field of view for each exam were modeled to match clinical protocols. For each protocol, the energy deposited in each organ was estimated by the simulations, converted to dose units, and then normalized by exposure in air. Dose to radiosensitive organs was studied as a function of average patient thickness in the region of interest and as a function of body mass index. For tomosynthesis, organ doses were also studied as a function of x-ray tube position. This work developed comprehensive information for organ dose dependencies across a range of tomosynthesis and radiography protocols. The results showed a protocol-dependent exponential decrease with an increasing patient size. There was a variability in organ dose across the patient population, which should be incorporated in the metrology of organ dose. The results can be used to prospectively and retrospectively estimate organ dose for tomosynthesis and radiography.

Breast dose reduction with organ-based, wide-angle tube current modulated CT

This study aimed to estimate the organ dose reduction potential for organ-dose-based tube current modulated (ODM) thoracic computed tomography (CT) with a wide dose reduction arc. Twenty-one computational anthropomorphic phantoms (XCAT) were used to create a virtual patient population with clinical anatomic variations. The phantoms were created based on patient images with normal anatomy (age range: 27 to 66 years, weight range: 52.0 to 105.8 kg). For each phantom, two breast tissue compositions were simulated: [Formula: see text] and [Formula: see text] (glandular-to-adipose ratio). A validated Monte Carlo program (PENELOPE, Universitat de Barcelona, Spain) was used to estimate the organ dose for standard tube current modulation (TCM) (SmartmA, GE Healthcare) and ODM (GE Healthcare) for a commercial CT scanner (Revolution, GE Healthcare) using a typical clinical thoracic CT protocol. Both organ dose and [Formula: see text]-to-organ dose conversion coefficients ([Formula: see text] factors) were compared between TCM and ODM. ODM significantly reduced all radiosensitive organ doses ([Formula: see text]). The breast dose was reduced by [Formula: see text]. For [Formula: see text] factors, organs in the anterior region (e.g., thyroid and stomach) exhibited substantial decreases, and the medial, distributed, and posterior region saw either an increase of less than 5% or no significant change. ODM significantly reduced organ doses especially for radiosensitive superficial anterior organs such as the breasts.

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.

Automated, patient-specific estimation of regional imparted energy and dose from tube current modulated computed tomography exams across 13 protocols

Currently, computed tomography (CT) dosimetry relies on surrogates for dose, such as CT dose index and size-specific dose estimates, rather than dose per se. Organ dose is considered as the gold standard for radiation dosimetry. However, organ dose estimation requires precise knowledge of organ locations. Regional imparted energy and dose can also be used to quantify radiation burden and are beneficial because they do not require knowledge of organ size or location. This work investigated an automated technique to retrospectively estimate the imparted energy from tube current-modulated (TCM) CT exams across 13 protocols. Monte Carlo simulations of various head and body TCM CT examinations across various tube potentials and TCM strengths were performed on 58 adult computational extended cardiac-torso phantoms to develop relationships between scanned mass and imparted energy normalized by dose length product. Results from the Monte Carlo simulations indicate that normalized imparted energy increases with increasing both scanned mass and tube potential, but it is relatively unaffected by the strength of the TCM. The automated algorithm was tested on 40 clinical datasets with a 98% success rate.

Voxel dosimetry: Comparison of MCNPX and DOSXYZnrc Monte Carlo codes in patient specific phantom calculations

INTRODUCTION

Dose evaluation with two Monte Carlo codes using patient specific voxel phantom is presented in this paper. We employ both MCNPX and DOSXYZnrc to perform dosimetry for mathematical voxel phantoms generated by our in-house developed voxel phantom generator and EGSnrc/CTCreate respectively.

MATERIAL AND METHOD

Our case study was a 2.5 × 2.4 × 2.4 cm3 tumor in the middle lobe of right lung of a male patient exposed to 6MV parallel beam. In order to compare these Monte Carlo codes with together gross tumor volume (GTV) and organ at risks (OAR) doses and dose volume histograms (DVH) were calculated.

RESULTS

Comparing the mean absorbed dose results (in Gy) from both codes indicates that gross tumor volume, heart and spinal cord have 2% to 10% difference. The 10% difference between the codes were from the spinal cord region where was not in the therapy beam and it just received the scatter radiation. The dose volume DVH obtained from DOSXYZnrc results demonstrate a milder slope compared with MCNPX DVHs.

CONCLUSION

It was revealed that MCNPX has some advantages in comparison to DOSXYZnrc, but it is important to consider that for equal precision in voxel dosimetry calculation, DOSXYZnrc runs faster than MCNPX and it is a great advantage.

A Monte Carlo study on quantifying the amount of dose reduction by shielding the superficial organs of an Iranian 11-year-old boy

A method for minimizing organ dose during computed tomography examinations is the use of shielding to protect superficial organs. There are some scientific reports that usage of shielding technique reduces the surface dose to patients with no appreciable loss in diagnostic quality. Therefore, in this Monte Carlo study based on the phantom of a 11-year-old Iranian boy, the effect of using an optimized shield on dose reduction to body organs was quantified. Based on the impact of shield on image quality, lead shields with thicknesses of 0.2 and 0.4 mm were considered for organs exposed directly and indirectly in the scan range, respectively. The results showed that there is 50%–62% reduction in amounts of dose for organs located fully or partly in the scan range at different tube voltages and modeling the true location of all organs in human anatomy, especially the ones located at the border of the scan, range affects the results up to 49%.

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 development of a population of 4D pediatric XCAT phantoms for imaging research and optimization

PURPOSE

We previously developed a set of highly detailed 4D reference pediatric extended cardiac-torso (XCAT) phantoms at ages of newborn, 1, 5, 10, and 15 yr with organ and tissue masses matched to ICRP Publication 89 values. In this work, we extended this reference set to a series of 64 pediatric phantoms of varying age and height and body mass percentiles representative of the public at large. The models will provide a library of pediatric phantoms for optimizing pediatric imaging protocols.

METHODS

High resolution positron emission tomography-computed tomography data obtained from the Duke University database were reviewed by a practicing experienced radiologist for anatomic regularity. The CT portion of the data was then segmented with manual and semiautomatic methods to form a target model defined using nonuniform rational B-spline surfaces. A multichannel large deformation diffeomorphic metric mapping algorithm was used to calculate the transform from the best age matching pediatric XCAT reference phantom to the patient target. The transform was used to complete the target, filling in the nonsegmented structures and defining models for the cardiac and respiratory motions. The complete phantoms, consisting of thousands of structures, were then manually inspected for anatomical accuracy. The mass for each major tissue was calculated and compared to linearly interpolated ICRP values for different ages.

RESULTS

Sixty four new pediatric phantoms were created in this manner. Each model contains the same level of detail as the original XCAT reference phantoms and also includes parameterized models for the cardiac and respiratory motions. For the phantoms that were 10 yr old and younger, we included both sets of reproductive organs. This gave them the capability to simulate both male and female anatomy. With this, the population can be expanded to 92. Wide anatomical variation was clearly seen amongst the phantom models, both in organ shape and size, even for models of the same age and sex. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities.

CONCLUSIONS

This work provides a large cohort of highly detailed pediatric phantoms with 4D capabilities of varying age, height, and body mass. The population of phantoms will provide a vital tool with which to optimize 3D and 4D pediatric imaging devices and techniques in terms of image quality and radiation-absorbed dose.

Numerical Analysis of Organ Doses Delivered During Computed Tomography Examinations Using Japanese Adult Phantoms with the WAZA-ARI Dosimetry System

A dosimetry system for computed tomography (CT) examinations, named WAZA-ARI, is being developed to accurately assess radiation doses to patients in Japan. For dose calculations in WAZA-ARI, organ doses were numerically analyzed using average adult Japanese male (JM) and female (JF) phantoms with the Particle and Heavy Ion Transport code System (PHITS). Experimental studies clarified the photon energy distribution of emitted photons and dose profiles on the table for some multi-detector row CT (MDCT) devices. Numerical analyses using a source model in PHITS could specifically take into account emissions of x rays from the tube to the table with attenuation of photons through a beam-shaping filter for each MDCT device based on the experiment results. The source model was validated by measuring the CT dose index (CTDI). Numerical analyses with PHITS revealed a concordance of organ doses with body sizes of the JM and JF phantoms. The organ doses in the JM phantoms were compared with data obtained using previously developed systems. In addition, the dose calculations in WAZA-ARI were verified with previously reported results by realistic NUBAS phantoms and radiation dose measurement using a physical Japanese model (THRA1 phantom). The results imply that numerical analyses using the Japanese phantoms and specified source models can give reasonable estimates of dose for MDCT devices for typical Japanese adults.

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.

Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method

PURPOSE

Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently.

METHODS

Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. The CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods.

RESULTS

The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors' study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer.

CONCLUSIONS

The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.

Evaluation of organ doses in adult and paediatric CT examinations based on Monte Carlo simulations and in-phantom dosimetry

The aim of this study was to validate the computed tomography dose index (CTDI) and organ doses evaluated by Monte Carlo simulations through comparisons with doses evaluated by in-phantom dosimetry. Organ doses were measured with radio-photoluminescence glass dosemeter (RGD) set at various organ positions within adult and 1-y-old anthropomorphic phantoms. For the dose simulations, the X-ray spectrum and bow-tie filter shape of a CT scanner were estimated and 3D voxelised data of the CTDI and anthropomorphic phantoms from the acquired CT images were derived. Organ dose simulations and measurements were performed with chest and abdomen-pelvis CT examination scan parameters. Relative differences between the simulated and measured doses were within 5 % for the volume CTDI and 13 % for organ doses for organs within the scan range in adult and paediatric CT examinations. The simulation results were considered to be in good agreement with the measured doses.

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.

In vitro dose measurements in a human cadaver with abdomen/pelvis CT scans

PURPOSE

To present a study of radiation dose measurements with a human cadaver scanned on a clinical CT scanner.

METHODS

Multiple point dose measurements were obtained with high-accuracy Thimble ionization chambers placed inside the stomach, liver, paravertebral gutter, ascending colon, left kidney, and urinary bladder of a human cadaver (183 cm in height and 67.5 kg in weight) whose abdomen/pelvis region was scanned repeatedly with a multidetector row CT. The flat energy response and precision of the dosimeters were verified, and the slight differences in each dosimeter's response were evaluated and corrected to attain high accuracy. In addition, skin doses were measured for radiosensitive organs outside the scanned region with OSL dosimeters: the right eye, thyroid, both nipples, and the right testicle. Three scan protocols were used, which shared most scan parameters but had different kVp and mA settings: 120-kVp automA, 120-kVp 300 mA, and 100-kVp 300 mA. For each protocol three repeated scans were performed.

RESULTS

The tube starting angle (TSA) was found to randomly vary around two major conditions, which caused large fluctuations in the repeated point dose measurements: for the 120-kVp 300 mA protocol this angle changed from approximately 110° to 290°, and caused 8%-25% difference in the point dose measured at the stomach, liver, colon, and urinary bladder. When the fluctuations of the TSA were small (within 5°), the maximum coefficient of variance was approximately 3.3%. The soft tissue absorbed doses averaged from four locations near the center of the scanned region were 27.2±3.3 and 16.5±2.7 mGy for the 120 and 100-kVp fixed-mA scans, respectively. These values were consistent with the corresponding size specific dose estimates within 4%. The comparison of the per-100-mAs tissue doses from the three protocols revealed that: (1) dose levels at nonsuperficial locations in the TCM scans could not be accurately deduced by simply scaling the fix-mA doses with local mA values; (2) the general power law relationship between dose and kVp varied from location to location, with the power index ranged between 2.7 and 3.5. The averaged dose measurements at both nipples, which were about 0.6 cm outside the prescribed scan region, ranged from 23 to 27 mGy at the left nipple, and varied from 3 to 20 mGy at the right nipple over the three scan protocols. Large fluctuations over repeated scans were also observed, as a combined result of helical scans of large pitch (1.375) and small active areas of the skin dosimeters. In addition, the averaged skin dose fell off drastically with the distance to the nearest boundary of the scanned region.

CONCLUSIONS

This study revealed the complexity of CT dose fluctuation and variation with a human cadaver.