A Monte Carlo-based method to estimate radiation dose from spiral CT: from phantom testing to patient-specific models

Automatic organ completion with image stitching for personalized radiation dosimetry in CT examinations

PURPOSE

Computed tomography (CT) image-based patient-specific voxel-based dosimetry has difficulties complementing missing tissues for organs located partially inside or completely outside the image volume. Previous studies constructed patient-specific whole-body models by rescaling reference phantoms or extending regional CT images with manually adjusted phantoms. This study proposes a methodology for automatic organ completion of regional CT images for CT dosimetry using a stitching approach.

METHODS

Virtual clinical trials were performed by truncating whole-body CT images to generate virtual clinical chest and abdominopelvic CT images. Corresponding anchor images for each patient were selected according to sex and similarity of the axial length and water equivalent diameter of the virtual regional CT images. Automatic image stitching was performed by transformation initialization and iteration, while the stitched CT images and organ atlas were used in GPU-based Geant4 Monte Carlo simulations to generate a radiation dose map and absorbed organ dose. To evaluate the performance of the stitching model in radiation dosimetry, organ mass differences and Jaccard's coefficient of stitched and rescaled anchor images were calculated, and the radiation doses were compared among the corresponding values from the VirtualDose®, original whole-body CT, stitching model, regional CT, registration-based rescaling method, and WED-based rescaling method.

RESULTS

The anatomical accuracy of stitched images was significantly improved. For organs partially inside the image volume, organ dose estimation from the stitching model could be more accurate than that reported in previous studies. The absolute differences in effective dose from the stitched images were 6.55% and 4.81% for chest and abdominopelvic CT scans, respectively.

CONCLUSION

The proposed automatic stitching model partially complements organs inside or outside the CT scan range and provides more accurate anatomical representations for radiation dosimetry than traditional phantom rescaling methods.

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

PURPOSE

With the rising number of computed tomography (CT) examinations and the trend toward personalized medicine, patient-specific dose estimates are becoming more and more important in CT imaging. However, current approaches are often too slow or too inaccurate to be applied routinely. Therefore, we propose the so-called deep dose estimation (DDE) to provide highly accurate patient dose distributions in real time METHODS: To combine accuracy and computational performance, the DDE algorithm uses a deep convolutional neural network to predict patient dose distributions. To do so, a U-net like architecture is trained to reproduce Monte Carlo simulations from a two-channel input consisting of a CT reconstruction and a first-order dose estimate. Here, the corresponding training data were generated using CT simulations based on 45 whole-body patient scans. For each patient, simulations were performed for different anatomies (pelvis, abdomen, thorax, head), different tube voltages (80 kV, 100 kV, 120 kV), different scan trajectories (circle, spiral), and with and without bowtie filtration and tube current modulation. Similar simulations were performed using a second set of eight whole-body CT scans from the Visual Concept Extraction Challenge in Radiology (Visceral) project to generate testing data. Finally, the DDE algorithm was evaluated with respect to the generalization to different scan parameters and the accuracy of organ dose and effective dose estimates based on an external organ segmentation.

RESULTS

DDE dose distributions were quantified in terms of the mean absolute percentage error (MAPE) and a gamma analysis with respect to the ground truth Monte Carlo simulation. Both measures indicate that DDE generalizes well to different scan parameters and different anatomical regions with a maximum MAPE of 6.3% and a minimum gamma passing rate of 91%. Evaluating the organ dose values for all organs listed in the International Commission on Radiological Protection (ICRP) recommendation, shows an average error of 3.1% and maximum error of 7.2% (bone surface).

CONCLUSIONS

The DDE algorithm provides an efficient approach to determine highly accurate dose distributions. Being able to process a whole-body CT scan in about 1.5 s, it provides a valuable alternative to Monte Carlo simulations on a graphics processing unit (GPU). Here, the main advantage of DDE is that it can be used on top of any existing Monte Carlo code such that real-time performance can be achieved without major adjustments. Thus, DDE opens up new options not only for dosimetry but also for scan and protocol optimization.

Technical note: Evaluation of a V‐Net autosegmentation algorithm for pediatric CT scans: Performance, generalizability and application to patient‐specific CT dosimetry

PURPOSE

This study developed and evaluated a fully convolutional network (FCN) for pediatric CT organ segmentation and investigated the generalizability of the FCN across image heterogeneities such as CT scanner model protocols and patient age. We also evaluated the autosegmentation models as part of a software tool for patient-specific CT dose estimation.

METHODS

A collection of 359 pediatric CT datasets with expert organ contours were used for model development and evaluation. Autosegmentation models were trained for each organ using a modified FCN 3D V-Net. An independent test set of 60 patients was withheld for testing. To evaluate the impact of CT scanner model protocol and patient age heterogeneities, separate models were trained using a subset of scanner model protocols and pediatric age groups. Train and test sets were split to answer questions about the generalizability of pediatric FCN autosegmentation models to unseen age groups and scanner model protocols, as well as the merit of scanner model protocol or age-group-specific models. Finally, the organ contours resulting from the autosegmentation models were applied to patient-specific dose maps to evaluate the impact of segmentation errors on organ dose estimation.

RESULTS

Results demonstrate that the autosegmentation models generalize to CT scanner acquisition and reconstruction methods which were not present in the training dataset. While models are not equally generalizable across age groups, age-group-specific models do not hold any advantage over combining heterogeneous age groups into a single training set. Dice similarity coefficient (DSC) and mean surface distance results are presented for 19 organ structures, for example, median DSC of 0.52 (duodenum), 0.74 (pancreas), 0.92 (stomach), and 0.96 (heart). The FCN models achieve a mean dose error within 5% of expert segmentations for all 19 organs except for the spinal canal, where the mean error was 6.31%.

CONCLUSIONS

Overall, these results are promising for the adoption of FCN autosegmentation models for pediatric CT, including applications for patient-specific CT dose estimation.

A comparison of breast and lung doses from chest CT scans using organ-based tube current modulation (OBTCM) vs. Automatic tube current modulation (ATCM)

PURPOSE

The purpose of this work was to estimate and compare breast and lung doses of chest CT scans using organ-based tube current modulation (OBTCM) to those from conventional, attenuation-based automatic tube current modulation (ATCM) across a range of patient sizes.

METHODS

Thirty-four patients (17 females, 17 males) who underwent clinically indicated CT chest/abdomen/pelvis (CAP) examinations employing OBTCM were collected from two multi-detector row CT scanners. Patient size metric was assessed as water equivalent diameter (Dw ) taken at the center of the scan volume. Breast and lung tissues were segmented from patient image data to create voxelized models for use in a Monte Carlo transport code. The OBTCM schemes for the chest portion were extracted from the raw projection data. ATCM schemes were estimated using a recently developed method. Breast and lung doses for each TCM scenario were estimated for each patient model. CTDIvol -normalized breast (nDbreast ) and lung (nDlung ) doses were subsequently calculated. The differences between OBTCM and ATCM normalized organ dose estimates were tested using linear regression models that included CT scanner and Dw as covariates.

RESULTS

Mean dose reduction from OBTCM in nDbreast was significant after adjusting for the scanner models and patient size (P = 0.047). When pooled with females and male patient, mean dose reduction from OBTCM in nDlung was observed to be trending after adjusting for the scanner model and patient size (P = 0.085).

CONCLUSIONS

One specific manufacturer's OBTCM was analyzed. OBTCM was observed to significantly decrease normalized breast relative to a modeled version of that same manufacturer's ATCM scheme. However, significant dose savings were not observed in lung dose over all. Results from this study support the use of OBTCM chest protocols for females only.

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

PURPOSE

Task Group Report 195 of the American Association of Physicists in Medicine contains reference datasets for the direct comparison of results among different Monte Carlo (MC) simulation tools for various aspects of imaging research that employs ionizing radiation. While useful for comparing and validating MC codes, that effort did not provide the information needed to compare absolute dose estimates from CT exams. Therefore, the purpose of this work is to extend those efforts by providing a reference dataset for benchmarking fetal dose derived from MC simulations of clinical CT exams.

ACQUISITION AND VALIDATION METHODS

The reference dataset contains the four necessary elements for validating MC engines for CT dosimetry: (a) physical characteristics of the CT scanner, (b) patient information, (c) exam specifications, and (d) fetal dose results from previously validated and published MC simulations methods in tabular form. Scanner characteristics include non-proprietary descriptions of equivalent source cumulative distribution function (CDF) spectra and bowtie filtration profiles, as well as scanner geometry information. Additionally, for the MCNPX MC engine, normalization factors are provided to convert raw simulation results to absolute dose in mGy. The patient information is based on a set of publicly available fetal dose models and includes de-identified image data; voxelized MC input files with fetus, uterus, and gestational sac identified; and patient size metrics in the form of water equivalent diameter (D_w ) z-axis distributions from a simulated topogram (D_w,topo ) and from the image data (D_w,image ). Exam characteristics include CT scan start and stop angles and table and patient locations, helical pitch, nominal collimation and measured beam width, and gantry rotation time for each simulation. For simulations involving estimating doses from exams using tube current modulation (TCM), a realistic TCM scheme is presented that is estimated based upon a validated method. (d) Absolute and CTDI_vol -normalized fetal dose results for both TCM and FTC simulations are given for each patient model under each scan scenario.

DATA FORMAT AND USAGE NOTES

Equivalent source CDFs and bowtie filtration profiles are available in text files. Image data are available in DICOM format. Voxelized models are represented by a header followed by a list of integers in a text file representing a three-dimensional model of the patient. Size distribution metrics are also given in text files. Results of absolute and normalized fetal dose with associated MC error estimates are presented in tabular form in an Excel spreadsheet. All data are stored on Zenodo and are publicly accessible using the following link: https://zenodo.org/record/3959512.

POTENTIAL APPLICATIONS

Similar to the work of AAPM Report 195, this work provides a set of reference data for benchmarking fetal dose estimates from clinical CT exams. This provides researchers with an opportunity to compare MC simulation results to a set of published reference data as part of their efforts to validate absolute and normalized fetal dose estimates. This could also be used as a basis for comparison to other non-MC approaches, such as deterministic approaches, or to commercial packages that provide estimates of fetal doses from clinical CT exams.

Photon fluence and dose estimation in computed tomography using a discrete ordinates Boltzmann solver

In this study, cone-beam single projection and axial CT scans are modeled with a software package—DOCTORS, which solves the linear Boltzmann equation using the discrete ordinates method. Phantoms include a uniform 35 cm diameter water cylinder and a non-uniform abdomen phantom. Series simulations were performed with different simulation parameters, including the number of quadrature angles, the order of Legendre polynomial expansions, and coarse and fine mesh grid. Monte Carlo simulations were also performed to benchmark DOCTORS simulations. A quantitative comparison was made between the simulation results obtained using DOCTORS and Monte Carlo methods. The deterministic simulation was in good agreement with the Monte Carlo simulation on dose estimation, with a root-mean-square-deviation difference of around 2.87%. It was found that the contribution of uncollided photon fluence directly from the source dominates the local absorbed dose in the diagnostic X-ray energy range. The uncollided photon fluence can be calculated accurately using a ‘ray-tracing’ algorithm. The accuracy of collided photon fluence estimation is largely affected by the pre-calculated multigroup cross-sections. The primary benefit of DOCTORS lies in its rapid computation speed. Using DOCTORS, parallel computing with GPU enables the cone-beam CT dose estimation nearly in real-time.

Individual Calculation of Effective Dose and Risk of Malignancy Based on Monte Carlo Simulations after Whole Body Computed Tomography

Detailed knowledge about radiation exposure is crucial for radiology professionals. The conventional calculation of effective dose (ED) for computed tomography (CT) is based on dose length product (DLP) and population-based conversion factors (k). This is often imprecise and unable to consider individual patient characteristics. We sought to provide more precise and individual radiation exposure calculation using image based Monte Carlo simulations (MC) in a heterogeneous patient collective and to compare it to phantom based MC provided from the National Cancer Institute (NCI) as academic reference. Dose distributions were simulated for 22 patients after whole-body CT during Positron Emission Tomography-CT. Based on MC we calculated individual Lifetime Attributable Risk (LAR) and Excess Relative Risk (ERR) of cancer mortality. ED_MC was compared to ED_DLP and ED_NCI. ED_DLP (13.2 ± 4.5 mSv) was higher compared to ED_NCI (9.8 ± 2.1 mSv) and ED_MC (11.6 ± 1.5 mSv). Relative individual differences were up to -48% for ED_MC and -44% for ED_NCI compared to ED_DLP. Matching pair analysis illustrates that young age and gender are affecting LAR and ERR significantly. Because of these uncertainties in radiation dose assessment automated individual dose and risk estimation would be desirable for dose monitoring in the future.

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.

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

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

Size-specific dose estimations for pediatric chest, abdomen/pelvis and head CT scans with the use of GATE

PURPOSE

The purpose of this study is to create an organ dose database for pediatric individuals undergoing chest, abdomen/pelvis, and head computed tomography (CT) examinations, and to report the differences in absorbed organ doses, when anatomical differences exist for pediatric patients.

METHODS

The GATE Monte Carlo (MC) toolkit was used to model the GE BrightSpeed Elite CT model. The simulated scanner model was validated with the standard Computed Tomography Dose Index (CTDI) head phantom. Twelve computational models (2.1-14 years old) were used. First, contributions to effective dose and absorbed doses per CTDI_vol and per 100 mAs were estimated for all organs. Then, doses per CTDI_vol were correlated with patient model weight for the organs inside the scan range for chest and abdomen/pelvis protocols. Finally, effective doses per dose-length product (DLP) were estimated and compared with the conventional conversion k-factors.

RESULTS

The system was validated against experimental CTDI_w measurements. The doses per CTDI_vol and per 100 mAs for selected organs were estimated. The magnitude of the dependency between the dose and the anatomical characteristics was calculated with the coefficient of determination at 0.5-0.7 for the internal scan organs for chest and abdomen/pelvis protocols. Finally, effective doses per DLP were compared with already published data, showing discrepancies between 13 and 29% and were correlated strongly with the total weight (R² > 0.8) for the chest and abdomen protocols.

CONCLUSIONS

Big differences in absorbed doses are reported even for patients of similar age or same gender, when anatomical differences exist on internal organs of the body.

Estimating fetal dose from tube current-modulated (TCM) and fixed tube current (FTC) abdominal/pelvis CT examinations

PURPOSE

The purpose of this work was to estimate scanner-independent CTDI_vol -to-fetal-dose coefficients for tube current-modulated (TCM) and fixed tube current (FTC) computed tomography (CT) examinations of pregnant patients of various gestational ages undergoing abdominal/pelvic CT examinations.

METHODS

For 24 pregnant patients of gestational age from <5 to 36 weeks who underwent clinically indicated CT examinations, voxelized models of maternal and fetal (or embryo) anatomy were created from abdominal/pelvic image data. Absolute fetal dose (D_fetus ) was estimated using Monte Carlo (MC) simulations of helical scans covering the abdomen and pelvis for TCM and FTC scans. Estimated TCM schemes were generated for each patient model using a validated method that accounts for patient attenuation and scanner output limits for one scanner model and were incorporated into MC simulations. FTC scans were also simulated for each patient model with multidetector row CT scanners from four manufacturers. Normalized fetal dose estimates, nD_fetus , was obtained by dividing D_fetus from the MC simulations by CTDI_vol . Patient size was described using water equivalent diameter (D_w ) measured at the three-dimensional geometric centroid of the fetus. Fetal depth (DE_f ) was measured from the anterior skin surface to the anterior part of the fetus. nD_fetus and D_w were correlated using an exponential model to develop equations for fetal dose conversion coefficients for TCM and FTC abdominal/pelvic CT examinations. Additionally, bivariate linear regression was performed to analyze the correlation of nD_fetus with D_w and fetal depth (DE_f ). For one scanner model, nD_fetus from TCM was compared to FTC and the size-specific dose estimate (SSDE) conversion coefficients (f-factors) from American Association of Physicists in Medicine (AAPM) Report 204. nD_fetus from FTC simulations was averaged across all scanners for each patient ( n D fetus ¯ ) . n D fetus ¯ was then compared with SSDE f-factors and correlated with D_w using an exponential model and with D_w and DE_f using a bivariate linear model.

RESULTS

For TCM, the coefficient of determination (R² ) of nD_fetus and D_w was observed to be 0.73 using an exponential model. Using the bivariate linear model with D_w and DE_f , an R² of 0.78 was observed. For the TCM technology modeled, TCM yielded nD_fetus values that were on average 6% and 17% higher relative to FTC and SSDE f-factors, respectively. For FTC, the R² of n D fetus ¯ with respect to D_w was observed to be 0.64 using an exponential model. Using the bivariate linear model, an R² of 0.75 was observed for n D fetus ¯ with respect to D_w and DE_f . A mean difference of 0.4% was observed between n D fetus ¯ and SSDE f-factors.

CONCLUSION

Good correlations were observed for nD_fetus from TCM and FTC scans using either an exponential model with D_w or a bivariate linear model with both D_w and DE_f . These results indicate that fetal dose from abdomen/pelvis CT examinations of pregnant patients of various gestational ages may be reasonably estimated with models that include (a) scanner-reported CTDI_vol and (b) D_w as a patient size metric, in addition to (c) DE_f if available. These results also suggest that SSDE f-factors may provide a reasonable (within ±25%) estimate of nD_fetus for TCM and FTC abdomen/pelvis CT exams.

A fast, linear Boltzmann transport equation solver for computed tomography dose calculation (Acuros CTD)

PURPOSE

To improve dose reporting of CT scans, patient-specific organ doses are highly desired. However, estimating the dose distribution in a fast and accurate manner remains challenging, despite advances in Monte Carlo methods. In this work, we present an alternative method that deterministically solves the linear Boltzmann transport equation (LBTE), which governs the behavior of x-ray photon transport through an object.

METHODS

Our deterministic solver for CT dose (Acuros CTD) is based on the same approach used to estimate scatter in projection images of a CT scan (Acuros CTS). A deterministic method is used to compute photon fluence within the object, which is then converted to deposited energy by multiplying by known, material-specific conversion factors. To benchmark Acuros CTD, we used the AAPM Task Group 195 test for CT dose, which models an axial, fan beam scan (10 mm thick beam) and calculates energy deposited in each organ of an anthropomorphic phantom. We also validated our own Monte Carlo implementation of Geant4 to use as a reference to compare Acuros against for other common geometries like an axial, cone beam scan (160 mm thick beam) and a helical scan (40 mm thick beam with table motion for a pitch of 1).

RESULTS

For the fan beam scan, Acuros CTD accurately estimated organ dose, with a maximum error of 2.7% and RMSE of 1.4% when excluding organs with <0.1% of the total energy deposited. The cone beam and helical scans yielded similar levels of accuracy compared to Geant4. Increasing the number of source positions beyond 18 or decreasing the voxel size below 5 × 5 × 5 mm³ provided marginal improvement to the accuracy for the cone beam scan but came at the expense of increased run time. Across the different scan geometries, run time of Acuros CTD ranged from 8 to 23 s.

CONCLUSIONS

In this digital phantom study, a deterministic LBTE solver was capable of fast and accurate organ dose estimates.

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.

ESTIMATION OF FEMALE RADIATION DOSES AND BREAST CANCER RISK FROM CHEST CT EXAMINATIONS

Breast organ doses, effective doses and lifetime attributable risk (LAR) of breast cancer from chest CT scans are presented for 200 female patients surveyed from 10 hospitals in the West Bank and Gaza Strip, Palestine. Patient data were collected and organized in a database from May to November 2016. Data include age (15-80 years), weight, height, and calculated body mass index. Exposure data were also recorded for every examination. Exposure data includes milliampere-second (mAs), X-ray tube kilovoltage (kVp), computed tomography dose index, dose length product, manufacturer, name and type of operated CT scanner. Organ and effective doses were evaluated using a web-based commercially available Monte Carlo software: VirtualDose™CT, a product of Virtual Phantoms, Inc. The software utilizes male and female tissue equivalent phantoms of all ages and sizes including pregnant patients. The corresponding phantom was selected for every patient according to patient's tomographic parameters. Calculated organ doses were used to estimate the LAR of breast cancer according to BEIR VII Phase 2 report. It was found that radiation doses resulting from the same exam vary widely between different hospitals, depending on the parameters used and the type of scanner. For all patients, the breast organ dose ranged from 6.5 to 28 mGy per examination, with an average breast organ dose of 15 mGy. The effective dose from chest CT scan per examination ranged from 3 to 14.7 mSv with an average of 7 mSv. For younger females (15-29 years), the LAR of breast cancer risk was estimated to be around 0.05%. For older female patients (60-79 years), the risk was ~0.001%. It was found that LAR decreases remarkably with patient's age. Values obtained in this study vary between hospitals, they are generally low and consistent with other studies reported worldwide.

Determination and verification of the x-ray spectrum of a CT scanner

The accuracy of Monte Carlo (MC) simulations in estimating the computed tomography radiation dose is highly dependent on the proprietary x-ray source information. To address this, this study develops a method to precisely estimate the x-ray spectrum and bowtie (BT) filter thickness of the x-ray source based on physical measurements and calculations. The static x-ray source of the CT localizer radiograph was assessed to measure the total filtration at the isocenter for the x-ray spectrum characterization and the BT profile (air-kerma values as a function of fan angle). With these values, the utilized BT filter in the localizer radiograph was assessed by integrating the measured air kerma in a full 360-deg cycle. The consistency observed between the integrated BT filter profiles and the directly measured profiles pointed to the similarity in the utilized BT filter in terms of thickness and material between the static and rotating x-ray geometries. Subsequently, the measured air kerma was used to calculate the BT filter thickness and was verified using MC simulations by comparing the calculated and measured air-kerma values, where a very good agreement was observed. This would allow a more accurate computed tomography simulation and facilitate the estimation of the dose delivered to the patients.

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.

Estimating organ doses from tube current modulated CT examinations using a generalized linear model

PURPOSE

Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the Generalized Linear Model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed.

METHODS

The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equivalent diameter (WED) and regional CTDI_vol as variables and (b) using the same exponential relationship with the addition of categorical variables such as scanner model and organ to provide a more complete estimate of factors that may affect organ dose. Finally, estimates from generated models were compared to those obtained from SSDE and ImPACT.

RESULTS

The Generalized Linear Model yielded organ dose estimates that were significantly closer to the MC reference organ dose values than were organ doses estimated via SSDE or ImPACT. Moreover, the GLM estimates were better than those of SSDE or ImPACT irrespective of whether or not categorical variables were used in the model. While the improvement associated with a categorical variable was substantial in estimating breast dose, the improvement was minor for other organs.

CONCLUSIONS

The GLM approach extends the current CT dose estimation methods by allowing the use of additional variables to more accurately estimate organ dose from TCM scans. Thus, this approach may be able to overcome the limitations of current CT dose metrics to provide more accurate estimates of patient dose, in particular, dose to organs with considerable variability across the population.

A measurement-based generalized source model for Monte Carlo dose simulations of CT scans

The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients' CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm

The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was [Formula: see text], with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors.

Diagnostic Reference Levels of CT Radiation Dose in Whole-Body PET/CT

The role of CT in PET/CT imaging includes acquisition techniques for diagnostic, anatomic localization, and attenuation correction purposes. Diagnostic reference levels of the volumetric CT dose index (CTDIvol) are available for dedicated CT procedures on selected body regions, but similar reference levels for whole-body CT used in PET/CT examinations are limited. This work reports CTDIvol values from sites that conduct whole-body oncologic PET/CT examinations and participated in the scanner validation program of the Society of Nuclear Medicine and Molecular Imaging Clinical Trials Network.

METHODS

From 2010 to 2014, a total of 154 sites submitted CT acquisition parameters used in their clinical (18)F-FDG PET/CT oncology protocols. From these parameters, the CTDIvol was estimated using the ImPACT CTDI dosimetry tables. Histograms of CTDIvol values were created for each year, and descriptive statistics, including mean, median, and 75th percentile, were reported. Repeated-measures ANOVA was performed to determine whether significant differences occurred between reporting years.

RESULTS

A wide range of technical parameters was reported, most notably in tube current. Between 2010 and 2014, the median CTDIvol ranged from 4.9 to 6.2 mGy and the 75th percentile from 9.7 to 10.2 mGy. There was no significant change in CTDIvol between reporting years (repeated-measures ANOVA, P = 0.985).

CONCLUSION

The 75th percentile CTDIvol reported in this work was 9.8 mGy averaged over all reporting years. These data provide a resource for establishing CTDIvol reference values specific to performing CT in PET/CT whole-body examinations. The wide ranges of CT acquisition parameters reported by sites suggest that CTDIvol reference levels may be beneficial for optimization of CT protocols.

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.

Attenuation-based size metric for estimating organ dose to patients undergoing tube current modulated CT exams

PURPOSE

Task Group 204 introduced effective diameter (ED) as the patient size metric used to correlate size-specific-dose-estimates. However, this size metric fails to account for patient attenuation properties and has been suggested to be replaced by an attenuation-based size metric, water equivalent diameter (DW). The purpose of this study is to investigate different size metrics, effective diameter, and water equivalent diameter, in combination with regional descriptions of scanner output to establish the most appropriate size metric to be used as a predictor for organ dose in tube current modulated CT exams.

METHODS

101 thoracic and 82 abdomen/pelvis scans from clinically indicated CT exams were collected retrospectively from a multidetector row CT (Sensation 64, Siemens Healthcare) with Institutional Review Board approval to generate voxelized patient models. Fully irradiated organs (lung and breasts in thoracic scans and liver, kidneys, and spleen in abdominal scans) were segmented and used as tally regions in Monte Carlo simulations for reporting organ dose. Along with image data, raw projection data were collected to obtain tube current information for simulating tube current modulation scans using Monte Carlo methods. Additionally, previously described patient size metrics [ED, DW, and approximated water equivalent diameter (DWa)] were calculated for each patient and reported in three different ways: a single value averaged over the entire scan, a single value averaged over the region of interest, and a single value from a location in the middle of the scan volume. Organ doses were normalized by an appropriate mAs weighted CTDIvol to reflect regional variation of tube current. Linear regression analysis was used to evaluate the correlations between normalized organ doses and each size metric.

RESULTS

For the abdominal organs, the correlations between normalized organ dose and size metric were overall slightly higher for all three differently (global, regional, and middle slice) reported DW and DWa than they were for ED, but the differences were not statistically significant. However, for lung dose, computed correlations using water equivalent diameter calculated in the middle of the image data (DW,middle) and averaged over the low attenuating region of lung (DW,regional) were statistically significantly higher than correlations of normalized lung dose with ED.

CONCLUSIONS

To conclude, effective diameter and water equivalent diameter are very similar in abdominal regions; however, their difference becomes noticeable in lungs. Water equivalent diameter, specifically reported as a regional average and middle of scan volume, was shown to be better predictors of lung dose. Therefore, an attenuation-based size metric (water equivalent diameter) is recommended because it is more robust across different anatomic regions. Additionally, it was observed that the regional size metric reported as a single value averaged over a region of interest and the size metric calculated from a single slice/image chosen from the middle of the scan volume are highly correlated for these specific patient models and scan types.

Monte Carlo modeling of a conventional X-ray computed tomography scanner for gel dosimetry purposes

Our purpose in the current study was to model an X-ray CT scanner with the Monte Carlo (MC) method for gel dosimetry. In this study, a conventional CT scanner with one array detector was modeled with use of the MCNPX MC code. The MC calculated photon fluence in detector arrays was used for image reconstruction of a simple water phantom as well as polyacrylamide polymer gel (PAG) used for radiation therapy. Image reconstruction was performed with the filtered back-projection method with a Hann filter and the Spline interpolation method. Using MC results, we obtained the dose-response curve for images of irradiated gel at different absorbed doses. A spatial resolution of about 2 mm was found for our simulated MC model. The MC-based CT images of the PAG gel showed a reliable increase in the CT number with increasing absorbed dose for the studied gel. Also, our results showed that the current MC model of a CT scanner can be used for further studies on the parameters that influence the usability and reliability of results, such as the photon energy spectra and exposure techniques in X-ray CT gel dosimetry.

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.

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.

Development and validation of a GEANT4 radiation transport code for CT dosimetry

The authors have created a radiation transport code using the GEANT4 Monte Carlo toolkit to simulate pediatric patients undergoing CT examinations. The focus of this paper is to validate their simulation with real-world physical dosimetry measurements using two independent techniques. Exposure measurements were made with a standard 100-mm CT pencil ionization chamber, and absorbed doses were also measured using optically stimulated luminescent (OSL) dosimeters. Measurements were made in air with a standard 16-cm acrylic head phantom and with a standard 32-cm acrylic body phantom. Physical dose measurements determined from the ionization chamber in air for 100 and 120 kVp beam energies were used to derive photon-fluence calibration factors. Both ion chamber and OSL measurement results provide useful comparisons in the validation of the Monte Carlo simulations. It was found that simulated and measured CTDI values were within an overall average of 6% of each other.

Effect of ROI filtering in 3D cone-beam rotational angiography on organ dose and effective dose in cerebral investigations

The assessment of intracranial aneurysms is increasingly performed using three-dimensional cone-beam rotational angiography (3D CBRA). To reduce the dose to the patient during 3D CBRA procedures, filtered region-of-interest imaging (FROI) is presented in literature to be an effective technique as the dose in regions of low interest is reduced, while high image quality is preserved in the ROI. The purpose of this study was to quantify the benefit of FROI imaging during a typical 3D CBRA procedure in a patient's head region. A cone-beam rotational angiography unit (Infinix) was modeled in GMctdospp, an EGSnrc-based Monte Carlo software, which calculates patient dose distributions in rotational computed tomography. Kodak Lanex, a gadolinium compound, was chosen to be the ROI filter material. The adult female ICRP reference phantom was integrated in GMctdospp to calculate organ and effective doses in simulations of FROI-CBRA examinations. During the Monte Carlo simulations, different parameters as the ROI filter thickness, the ROI opening size, the tube voltage, and the isocenter position were varied. The results showed that the reduction in dose clearly depends on these parameters. Comparing the reduction in organ dose in standard 3D CBRA and FROI-CBRA, a maximum reduction of about 60%-80% could be achieved with a small sized ROI filter and about 40%-70% of the dose could be saved using a ROI filter with a large opening. Further we could show that dose reduction strongly depends on filter thickness, the location of the organ in the radiated area, and the position of the isocenter. As a consequence, dose reduction partially differs from theoretically calculated values by a factor up to 1.6. The effective dose could be reduced to a minimum of about 40%. Due to the fact that standard 3D CBRA is only used for the assessment of aneurysms at present and, thus, most of the patient dose originates from the aneurysm treatment (with 2D techniques) itself, the dose reduction effect of ROI filtering in 3D CBRA tends to be much smaller, if the patient dose of a whole aneurysm treatment procedure is considered.

Accuracy of Monte Carlo simulations compared to in-vivo MDCT dosimetry

PURPOSE

The purpose of this study was to assess the accuracy of a Monte Carlo simulation-based method for estimating radiation dose from multidetector computed tomography (MDCT) by comparing simulated doses in ten patients to in-vivo dose measurements.

METHODS

MD Anderson Cancer Center Institutional Review Board approved the acquisition of in-vivo rectal dose measurements in a pilot study of ten patients undergoing virtual colonoscopy. The dose measurements were obtained by affixing TLD capsules to the inner lumen of rectal catheters. Voxelized patient models were generated from the MDCT images of the ten patients, and the dose to the TLD for all exposures was estimated using Monte Carlo based simulations. The Monte Carlo simulation results were compared to the in-vivo dose measurements to determine accuracy.

RESULTS

The calculated mean percent difference between TLD measurements and Monte Carlo simulations was -4.9% with standard deviation of 8.7% and a range of -22.7% to 5.7%.

CONCLUSIONS

The results of this study demonstrate very good agreement between simulated and measured doses in-vivo. Taken together with previous validation efforts, this work demonstrates that the Monte Carlo simulation methods can provide accurate estimates of radiation dose in patients undergoing CT examinations.

An indirect transmission measurement-based spectrum estimation method for computed tomography

The characteristics of an x-ray spectrum can greatly influence imaging and related tasks. In practice, due to the pile-up effect of the detector, it's difficult to directly measure the spectrum of a CT scanner using an energy resolved detector. An alternative solution is to estimate the spectrum using transmission measurements with a step phantom or another CT phantom. In this work, we present a new spectrum estimation method based on indirect transmission measurement and a model spectra mixture approach. The estimated x-ray spectrum was expressed as a weighted summation of a set of model spectra, which can significantly reduce the degrees of freedom of the spectrum estimation problem. Next, an estimated projection was calculated with the assumed spectrum. By iteratively updating the unknown weights, we minimized the difference between the estimated projection data and the raw projection data. The final spectrum was calculated with these calibrated weights and the model spectra. Both simulation and experimental data were used to evaluate the proposed method. In the simulation study, the estimated spectra were compared to the raw spectra which were used to generate the raw projection data. For the experimental study, the ground truth measurement of the raw x-ray spectrum was not available. Therefore, the estimated spectrum was compared against the spectra generated using the SpekCalc software with tube configurations provided by the scanner manufacturer. The results show the proposed method has the potential to accurately estimate x-ray spectra using the raw projection data. The difference between the mean energy of the raw spectra and the mean energy of the estimated spectra was less than 0.5 keV for both the simulation and experimental data. Further tests show the method was robust with respect to the model spectra generator.

Effects of shielding the radiosensitive superficial organs of ORNL pediatric phantoms on dose reduction in computed tomography

In computed tomography (CT), some superficial organs which have increased sensitivity to radiation, receive doses that are significant enough to be matter of concern. Therefore, in this study, the effects of using shields on the amount of dose reduction and image quality was investigated for pediatric imaging. Absorbed doses of breasts, eyes, thyroid and testes of a series of pediatric phantoms without and with different thickness of bismuth and lead were calculated by Monte Carlo simulation. Appropriate thicknesses of shields were chosen based on their weights, X-ray spectrum, and the amount of dose reduction. In addition, the effect of lead shield on image quality of a simple phantom was assessed quantitatively using region of interest (ROI) measurements. Considering the maximum reduction in absorbed doses and X-ray spectrum, using a lead shield with a maximum thickness of 0.4 mm would be appropriate for testes and thyroid and two other organs (which are exposed directly) should be protected with thinner shields. Moreover, the image quality assessment showed that lead was associated with significant increases in both noise and CT attenuation values, especially in the anterior of the phantom. Overall, the results suggested that shielding is a useful optimization tool in CT.

Implementing the complete beam hardening effect of the bowtie filter versus scaling beam intensities: effects on dosimetric applications in computed tomography

The bowtie filter is an essential element of computed tomography scanners. Implementation of this filter in a Monte Carlo dosimetry platform can be based on Turner's method, which describes how to measure the filter thickness and relate the x-ray beam as a function of bowtie angle to the central beam. In that application, the beam hardening is accounted for by means of weighting factors that are associated to the photons according to their position (fan angle) and energy. We assessed an alternative approximation in which the photon spectrum is given a fan angle-dependent scaling factor. The aim of our investigation was to evaluate the effects on dose accuracy estimation when using the gold standard bowtie filter method versus a beam scaling approximation method. In particular, we wanted to assess the percentage dose differences between the two methods for several water thicknesses representative for different patients of different body mass index. The largest percentage differences were found for the thickest part of the bowtie filter and increased with patient size.

Development and validation of a measurement-based source model for kilovoltage cone-beam CT Monte Carlo dosimetry simulations

PURPOSE

The purpose of this study is to adapt an equivalent source model originally developed for conventional CT Monte Carlo dose quantification to the radiation oncology context and validate its application for evaluating concomitant dose incurred by a kilovoltage (kV) cone-beam CT (CBCT) system integrated into a linear accelerator.

METHODS

In order to properly characterize beams from the integrated kV CBCT system, the authors have adapted a previously developed equivalent source model consisting of an equivalent spectrum module that takes into account intrinsic filtration and an equivalent filter module characterizing the added bowtie filtration. An equivalent spectrum was generated for an 80, 100, and 125 kVp beam with beam energy characterized by half-value layer measurements. An equivalent filter description was generated from bowtie profile measurements for both the full- and half-bowtie. Equivalent source models for each combination of equivalent spectrum and filter were incorporated into the Monte Carlo software package MCNPX. Monte Carlo simulations were then validated against in-phantom measurements for both the radiographic and CBCT mode of operation of the kV CBCT system. Radiographic and CBCT imaging dose was measured for a variety of protocols at various locations within a body (32 cm in diameter) and head (16 cm in diameter) CTDI phantom. The in-phantom radiographic and CBCT dose was simulated at all measurement locations and converted to absolute dose using normalization factors calculated from air scan measurements and corresponding simulations. The simulated results were compared with the physical measurements and their discrepancies were assessed quantitatively.

RESULTS

Strong agreement was observed between in-phantom simulations and measurements. For the radiographic protocols, simulations uniformly underestimated measurements by 0.54%-5.14% (mean difference = -3.07%, SD = 1.60%). For the CBCT protocols, simulations uniformly underestimated measurements by 1.35%-5.31% (mean difference = -3.42%, SD = 1.09%).

CONCLUSIONS

This work demonstrates the feasibility of using a measurement-based kV CBCT source model to facilitate dose calculations with Monte Carlo methods for both the radiographic and CBCT mode of operation. While this initial work validates simulations against measurements for simple geometries, future work will involve utilizing the source model to investigate kV CBCT dosimetry with more complex anthropomorphic phantoms and patient specific models.

Patient-based estimation of organ dose for a population of 58 adult patients across 13 protocol categories

PURPOSE

This study aimed to provide a comprehensive patient-specific organ dose estimation across a multiplicity of computed tomography (CT) examination protocols.

METHODS

A validated Monte Carlo program was employed to model a common CT system (LightSpeed VCT, GE Healthcare). The organ and effective doses were estimated from 13 commonly used body and neurological CT examination. The dose estimation was performed on 58 adult computational extended cardiac-torso phantoms (35 male, 23 female, mean age 51.5 years, mean weight 80.2 kg). The organ dose normalized by CTDIvol (h factor) and effective dose normalized by the dose length product (DLP) (k factor) were calculated from the results. A mathematical model was derived for the correlation between the h and k factors with the patient size across the protocols. Based on this mathematical model, a dose estimation iPhone operating system application was designed and developed to be used as a tool to estimate dose to the patients for a variety of routinely used CT examinations.

RESULTS

The organ dose results across all the protocols showed an exponential decrease with patient body size. The correlation was generally strong for the organs which were fully or partially located inside the scan coverage (Pearson sample correlation coefficient (r) of 0.49). The correlation was weaker for organs outside the scan coverage for which distance between the organ and the irradiation area was a stronger predictor of dose to the organ. For body protocols, the effective dose before and after normalization by DLP decreased exponentially with increasing patient's body diameter (r > 0.85). The exponential relationship between effective dose and patient's body diameter was significantly weaker for neurological protocols (r < 0.41), where the trunk length was a slightly stronger predictor of effective dose (0.15 < r < 0.46).

CONCLUSIONS

While the most accurate estimation of a patient dose requires specific modeling of the patient anatomy, a first order approximation of organ and effective doses from routine CT scan protocols can be reasonably estimated using size specific factors. Estimation accuracy is generally poor for organ outside the scan range and for neurological protocols. The dose calculator designed in this study can be used to conveniently estimate and report the dose values for a patient across a multiplicity of CT scan protocols.

Estimating peak skin and eye lens dose from neuroperfusion examinations: use of Monte Carlo based simulations and comparisons to CTDIvol, AAPM Report No. 111, and ImPACT dosimetry tool values

PURPOSE

CT neuroperfusion examinations are capable of delivering high radiation dose to the skin or lens of the eyes of a patient and can possibly cause deterministic radiation injury. The purpose of this study is to: (a) estimate peak skin dose and eye lens dose from CT neuroperfusion examinations based on several voxelized adult patient models of different head size and (b) investigate how well those doses can be approximated by some commonly used CT dose metrics or tools, such as CTDIvol, American Association of Physicists in Medicine (AAPM) Report No. 111 style peak dose measurements, and the ImPACT organ dose calculator spreadsheet.

METHODS

Monte Carlo simulation methods were used to estimate peak skin and eye lens dose on voxelized patient models, including GSF's Irene, Frank, Donna, and Golem, on four scanners from the major manufacturers at the widest collimation under all available tube potentials. Doses were reported on a per 100 mAs basis. CTDIvol measurements for a 16 cm CTDI phantom, AAPM Report No. 111 style peak dose measurements, and ImPACT calculations were performed for available scanners at all tube potentials. These were then compared with results from Monte Carlo simulations.

RESULTS

The dose variations across the different voxelized patient models were small. Dependent on the tube potential and scanner and patient model, CTDIvol values overestimated peak skin dose by 26%-65%, and overestimated eye lens dose by 33%-106%, when compared to Monte Carlo simulations. AAPM Report No. 111 style measurements were much closer to peak skin estimates ranging from a 14% underestimate to a 33% overestimate, and with eye lens dose estimates ranging from a 9% underestimate to a 66% overestimate. The ImPACT spreadsheet overestimated eye lens dose by 2%-82% relative to voxelized model simulations.

CONCLUSIONS

CTDIvol consistently overestimates dose to eye lens and skin. The ImPACT tool also overestimated dose to eye lenses. As such they are still useful as a conservative predictor of dose for CT neuroperfusion studies. AAPM Report No. 111 style measurements are a better predictor of both peak skin and eye lens dose than CTDIvol and ImPACT for the patient models used in this study. It should be remembered that both the AAPM Report No. 111 peak dose metric and CTDIvol dose metric are dose indices and were not intended to represent actual organ doses.

Direct action of radiation on mummified cells: modeling of computed tomography by Monte Carlo algorithms

X-ray imaging is a nondestructive and preferred method in paleopathology to reconstruct the history of ancient diseases. Sophisticated imaging technologies such as computed tomography (CT) have become common for the investigation of skeletal disorders in human remains. Researchers have investigated the impact of ionizing radiation on living cells, but never on ancient cells in dry tissue. The effects of CT exposure on ancient cells have not been examined in the past and may be important for subsequent genetic analysis. To remedy this shortcoming, we developed different Monte Carlo models to simulate X-ray irradiation on ancient cells. Effects of mummification were considered by using two sizes of cells and three different phantom tissues, which enclosed the investigated cell cluster. This cluster was positioned at the isocenter of a CT scanner model, where the cell hit probabilities P(0,1,…, n) were calculated according to the Poisson distribution. To study the impact of the dominant physics process, CT scans for X-ray spectra of 80 and 120 kVp were simulated. Comparison between normal and dry tissue phantoms revealed that the probability of unaffected cells increased by 21 % following cell shrinkage for 80 kVp, while for 120 kVp, a further increase of unaffected cells of 23 % was observed. Consequently, cell shrinkage caused by dehydration decreased the impact of X-ray radiation on mummified cells significantly. Moreover, backscattered electrons in cortical bone protected deeper-lying ancient cells from radiation damage at 80 kVp X-rays.

Feasibility of an image planning system for kilovoltage image-guided radiation therapy

PURPOSE

Image guidance has become a standard of care for many treatment scenarios in radiation therapy. This is most typically accomplished by use of kV x-ray devices mounted onto the linear accelerator (Linac) gantry that yield planar, fluoroscopic, and cone-beam computed tomography (CBCT) images. Image acquisition parameters are chosen via preset techniques that rely on broad categorizations in patient anatomy and imaging goal. However, the optimal imaging technique results in detectability of the features of interest while exposing the patient to minimum dose. Herein, the authors present an investigation into the feasibility of developing an image planning system (IPS) for radiotherapy.

METHODS

In this first phase, the authors focused on developing an algorithm to predict tissue contrast produced by a common radiotherapy planar imaging chain. Input parameters include a CT dataset and simulated planar imaging technique settings that include kV and mAs. Energy-specific attenuation through each voxel of the CT dataset was calculated in the algorithm to derive a net transmitted intensity. The response of the flat panel detector was integrated into the image simulation algorithm. Verification was conducted by comparing simulated and measured images using four phantoms. Comparisons were made in both high and low contrast settings, as well as changes in the geometric appearance due to image saturation.

RESULTS

The authors studied a lung nodule test object to assess the planning system's ability to predict object contrast and detectability. Verification demonstrated that the slope of the pixel intensities is similar, the presence of the nodule is evident, and image saturation at high mAs values is evident in both images. The appearance of the lung nodule is a function of the image detector saturation. The authors assessed the dimensions of the lung nodule in measured and simulated images. Good quantitative agreement affirmed the algorithm's predictive capabilities. The invariance of contrast with kVp and mAs prior to saturation was predicted, as well as the gradual loss of object detectability as saturation was approached. Small changes in soft tissue density were studied using a mammography step wedge phantom. Data were acquired at beam qualities of 80 and 120 kVp and over exposure values ranging from 0.04 to 500 mAs. The data showed good agreement in terms of the absolute value of pixel intensities predicted, as well as small variations across the step wedge pattern. The saturation pixel intensity was consistent between the two beam qualities studied. Boney tissue contrast was assessed using two abdominal phantoms. Measured and calculated values agree in terms of predicting the mAs value at which detector saturation, and subsequent loss of contrast occurs. The lack of variation in contrast over mAs values lower than 10 suggests that there is wide latitude for minimizing patient dose.

CONCLUSIONS

The authors developed and tested an algorithm that can be used to assist in kV imaging technique selection during localization for radiotherapy. Phantom testing demonstrated the algorithm's predictive accuracy for both low and high contrast imaging scenarios. Detector saturation with subsequent loss of imaging detail, both in terms of object size and contrast were accurately predicted by the algorithm.

The feasibility of a regional CTDIvol to estimate organ dose from tube current modulated CT exams

PURPOSE

In AAPM Task Group 204, the size-specific dose estimate (SSDE) was developed by providing size adjustment factors which are applied to the Computed Tomography (CT) standardized dose metric, CTDI(vol). However, that work focused on fixed tube current scans and did not specifically address tube current modulation (TCM) scans, which are currently the majority of clinical scans performed. The purpose of this study was to extend the SSDE concept to account for TCM by investigating the feasibility of using anatomic and organ specific regions of scanner output to improve accuracy of dose estimates.

METHODS

Thirty-nine adult abdomen/pelvis and 32 chest scans from clinically indicated CT exams acquired on a multidetector CT using TCM were obtained with Institutional Review Board approval for generating voxelized models. Along with image data, raw projection data were obtained to extract TCM functions for use in Monte Carlo simulations. Patient size was calculated using the effective diameter described in TG 204. In addition, the scanner-reported CTDI(vo)l (CTDI(vol),global) was obtained for each patient, which is based on the average tube current across the entire scan. For the abdomen/pelvis scans, liver, spleen, and kidneys were manually segmented from the patient datasets; for the chest scans, lungs and for female models only, glandular breast tissue were segmented. For each patient organ doses were estimated using Monte Carlo Methods. To investigate the utility of regional measures of scanner output, regional and organ anatomic boundaries were identified from image data and used to calculate regional and organ-specific average tube current values. From these regional and organ-specific averages, CTDI(vol) values, referred to as regional and organ-specific CTDI(vol), were calculated for each patient. Using an approach similar to TG 204, all CTDI(vol) values were used to normalize simulated organ doses; and the ability of each normalized dose to correlate with patient size was investigated.

RESULTS

For all five organs, the correlations with patient size increased when organ doses were normalized by regional and organ-specific CTDI(vol) values. For example, when estimating dose to the liver, CTDI(vol),global yielded a R(2) value of 0.26, which improved to 0.77 and 0.86, when using the regional and organ-specific CTDI(vol) for abdomen and liver, respectively. For breast dose, the global CTDI(vol) yielded a R(2) value of 0.08, which improved to 0.58 and 0.83, when using the regional and organ-specific CTDI(vol) for chest and breasts, respectively. The R(2) values also increased once the thoracic models were separated for the analysis into females and males, indicating differences between genders in this region not explained by a simple measure of effective diameter.

CONCLUSIONS

This work demonstrated the utility of regional and organ-specific CTDI(vol) as normalization factors when using TCM. It was demonstrated that CTDI(vol),global is not an effective normalization factor in TCM exams where attenuation (and therefore tube current) varies considerably throughout the scan, such as abdomen/pelvis and even thorax. These exams can be more accurately assessed for dose using regional CTDI(vol) descriptors that account for local variations in scanner output present when TCM is employed.

Spiral computed tomography phase-space source model in the BEAMnrc/EGSnrc Monte Carlo system: implementation and validation

Currently, the BEAMnrc/EGSnrc Monte Carlo (MC) system does not provide a spiral CT source model for the simulation of spiral CT scanning. We developed and validated a spiral CT phase-space source model in the BEAMnrc/EGSnrc system. The spiral phase-space source model was implemented in the DOSXYZnrc user code of the BEAMnrc/EGSnrc system by analyzing the geometry of spiral CT scan-scan range, initial angle, rotational direction, pitch, slice thickness, etc. Table movement was simulated by changing the coordinates of the isocenter as a function of beam angles. Some parameters such as pitch, slice thickness and translation per rotation were also incorporated into the model to make the new phase-space source model, designed specifically for spiral CT scan simulations. The source model was hard-coded by modifying the 'ISource = 8: Phase-Space Source Incident from Multiple Directions' in the srcxyznrc.mortran and dosxyznrc.mortran files in the DOSXYZnrc user code. In order to verify the implementation, spiral CT scans were simulated in a CT dose index phantom using the validated x-ray tube model of a commercial CT simulator for both the original multi-direction source (ISOURCE = 8) and the new phase-space source model in the DOSXYZnrc system. Then the acquired 2D and 3D dose distributions were analyzed with respect to the input parameters for various pitch values. In addition, surface-dose profiles were also measured for a patient CT scan protocol using radiochromic film and were compared with the MC simulations. The new phase-space source model was found to simulate the spiral CT scanning in a single simulation run accurately. It also produced the equivalent dose distribution of the ISOURCE = 8 model for the same CT scan parameters. The MC-simulated surface profiles were well matched to the film measurement overall within 10%. The new spiral CT phase-space source model was implemented in the BEAMnrc/EGSnrc system. This work will be beneficial in estimating the spiral CT scan dose in the BEAMnrc/EGSnrc system.

A comparison of methods to estimate organ doses in CT when utilizing approximations to the tube current modulation function

PURPOSE

Most methods to estimate patient dose from computed tomography (CT) exams have been developed based on fixed tube current scans. However, in current clinical practice, many CT exams are performed using tube current modulation (TCM). Detailed information about the TCM function is difficult to obtain and therefore not easily integrated into patient dose estimate methods. The purpose of this study was to investigate the accuracy of organ dose estimates obtained using methods that approximate the TCM function using more readily available data compared to estimates obtained using the detailed description of the TCM function.

METHODS

Twenty adult female models generated from actual patient thoracic CT exams and 20 pediatric female models generated from whole body PET∕CT exams were obtained with IRB (Institutional Review Board) approval. Detailed TCM function for each patient was obtained from projection data. Monte Carlo based models of each scanner and patient model were developed that incorporated the detailed TCM function for each patient model. Lungs and glandular breast tissue were identified in each patient model so that organ doses could be estimated from simulations. Three sets of simulations were performed: one using the original detailed TCM function (x, y, and z modulations), one using an approximation to the TCM function (only the z-axis or longitudinal modulation extracted from the image data), and the third was a fixed tube current simulation using a single tube current value which was equal to the average tube current over the entire exam. Differences from the reference (detailed TCM) method were calculated based on organ dose estimates. Pearson's correlation coefficients were calculated between methods after testing for normality. Equivalence test was performed to compare the equivalence limit between each method (longitudinal approximated TCM and fixed tube current method) and the detailed TCM method. Minimum equivalence limit was reported for each organ.

RESULTS

Doses estimated using the longitudinal approximated TCM resulted in small differences from doses obtained using the detailed TCM function. The calculated root-mean-square errors (RMSE) for adult female chest simulations were 9% and 3% for breasts and lungs, respectively; for pediatric female chest and whole body simulations RMSE were 9% and 7% for breasts and 3% and 1% for lungs, respectively. Pearson's correlation coefficients were consistently high for the longitudinal approximated TCM method, ranging from 0.947 to 0.999, compared to the fixed tube current value ranging from 0.8099 to 0.9916. In addition, an equivalence test illustrated that across all models the longitudinal approximated TCM is equivalent to the detailed TCM function within up to 3% for lungs and breasts.

CONCLUSIONS

While the best estimate of organ dose requires the detailed description of the TCM function for each patient, extracting these values can be difficult. The presented results show that an approximation using available data extracted from the DICOM header provides organ dose estimates with RMSE of less than 10%. On the other hand, the use of the overall average tube current as a single tube current value was shown to result in poor and inconsistent estimates of organ doses.

Organ doses for reference pediatric and adolescent patients undergoing computed tomography estimated by Monte Carlo simulation

PURPOSE

To establish an organ dose database for pediatric and adolescent reference individuals undergoing computed tomography (CT) examinations by using Monte Carlo simulation. The data will permit rapid estimates of organ and effective doses for patients of different age, gender, examination type, and CT scanner model.

METHODS

The Monte Carlo simulation model of a Siemens Sensation 16 CT scanner previously published was employed as a base CT scanner model. A set of absorbed doses for 33 organs∕tissues normalized to the product of 100 mAs and CTDI(vol) (mGy∕100 mAs mGy) was established by coupling the CT scanner model with age-dependent reference pediatric hybrid phantoms. A series of single axial scans from the top of head to the feet of the phantoms was performed at a slice thickness of 10 mm, and at tube potentials of 80, 100, and 120 kVp. Using the established CTDI(vol)- and 100 mAs-normalized dose matrix, organ doses for different pediatric phantoms undergoing head, chest, abdomen-pelvis, and chest-abdomen-pelvis (CAP) scans with the Siemens Sensation 16 scanner were estimated and analyzed. The results were then compared with the values obtained from three independent published methods: CT-Expo software, organ dose for abdominal CT scan derived empirically from patient abdominal circumference, and effective dose per dose-length product (DLP).

RESULTS

Organ and effective doses were calculated and normalized to 100 mAs and CTDI(vol) for different CT examinations. At the same technical setting, dose to the organs, which were entirely included in the CT beam coverage, were higher by from 40 to 80% for newborn phantoms compared to those of 15-year phantoms. An increase of tube potential from 80 to 120 kVp resulted in 2.5-2.9-fold greater brain dose for head scans. The results from this study were compared with three different published studies and∕or techniques. First, organ doses were compared to those given by CT-Expo which revealed dose differences up to several-fold when organs were partially included in the scan coverage. Second, selected organ doses from our calculations agreed to within 20% of values derived from empirical formulae based upon measured patient abdominal circumference. Third, the existing DLP-to-effective dose conversion coefficients tended to be smaller than values given in the present study for all examinations except head scans.

CONCLUSIONS

A comprehensive organ∕effective dose database was established to readily calculate doses for given patients undergoing different CT examinations. The comparisons of our results with the existing studies highlight that use of hybrid phantoms with realistic anatomy is important to improve the accuracy of CT organ dosimetry. The comprehensive pediatric dose data developed here are the first organ-specific pediatric CT scan database based on the realistic pediatric hybrid phantoms which are compliant with the reference data from the International Commission on Radiological Protection (ICRP). The organ dose database is being coupled with an adult organ dose database recently published as part of the development of a user-friendly computer program enabling rapid estimates of organ and effective dose doses for patients of any age, gender, examination types, and CT scanner model.

Development of a database of organ doses for paediatric and young adult CT scans in the United Kingdom

Despite great potential benefits, there are concerns about the possible harm from medical imaging including the risk of radiation-related cancer. There are particular concerns about computed tomography (CT) scans in children because both radiation dose and sensitivity to radiation for children are typically higher than for adults undergoing equivalent procedures. As direct empirical data on the cancer risks from CT scans are lacking, the authors are conducting a retrospective cohort study of over 240,000 children in the UK who underwent CT scans. The main objective of the study is to quantify the magnitude of the cancer risk in relation to the radiation dose from CT scans. In this paper, the methods used to estimate typical organ-specific doses delivered by CT scans to children are described. An organ dose database from Monte Carlo radiation transport-based computer simulations using a series of computational human phantoms from newborn to adults for both male and female was established. Organ doses vary with patient size and sex, examination types and CT technical settings. Therefore, information on patient age, sex and examination type from electronic radiology information systems and technical settings obtained from two national surveys in the UK were used to estimate radiation dose. Absorbed doses to the brain, thyroid, breast and red bone marrow were calculated for reference male and female individuals with the ages of newborns, 1, 5, 10, 15 and 20 y for a total of 17 different scan types in the pre- and post-2001 time periods. In general, estimated organ doses were slightly higher for females than males which might be attributed to the smaller body size of the females. The younger children received higher doses in pre-2001 period when adult CT settings were typically used for children. Paediatric-specific adjustments were assumed to be used more frequently after 2001, since then radiation doses to children have often been smaller than those to adults. The database here is the first detailed organ-specific paediatric CT scan database for the UK. As well as forming the basis for the UK study, the results and description of the methods will also serve as a key resource for paediatric CT scan studies currently underway in other countries.