Kyle McMillan

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.

Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195

The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, such validation involves either comparison of simulation results to physical measurements or to previously published results obtained with established Monte Carlo codes. The former is complicated due to nuances of experimental conditions and uncertainty, while the latter is challenging due to typical graphical presentation and lack of simulation details in previous publications. In addition, entering the field of Monte Carlo simulations in general involves a steep learning curve. It is not a simple task to learn how to program and interpret a Monte Carlo simulation, even when using one of the publicly available code packages. This Task Group report provides a common reference for benchmarking Monte Carlo simulations across a range of Monte Carlo codes and simulation scenarios. In the report, all simulation conditions are provided for six different Monte Carlo simulation cases that involve common x-ray based imaging research areas. The results obtained for the six cases using four publicly available Monte Carlo software packages are included in tabular form. In addition to a full description of all simulation conditions and results, a discussion and comparison of results among the Monte Carlo packages and the lessons learned during the compilation of these results are included. This abridged version of the report includes only an introductory description of the six cases and a brief example of the results of one of the cases. This work provides an investigator the necessary information to benchmark his/her Monte Carlo simulation software against the reference cases included here before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self-teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs.

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.

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.

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.

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.

Dual-particle imager for standoff detection of special nuclear material

An advanced dual-particle imaging system is being developed for standoff, passive detection of special nuclear material. This system consists of three detector planes and will be capable of imaging both photons and fast neutrons. The ability of the system to detect fast neutrons makes it more difficult to effectively shield a threat source. This feature has an advantage over the commonly used Compton-camera systems, which are only sensitive to photons. Additionally, the detection of fast neutrons will allow for increased performance in regions with high levels of photon background radiation. The first two planes of the system consist of EJ-309 liquid scintillators and the third plane consists of NaI scintillators. This detector/plane combination allows image reconstruction using both neutrons and photons. In the liquid scintillators, neutron interactions are distinguished from photon interactions using an optimized pulse shape discrimination technique. The Monte Carlo transport code MCNPX-PoliMi has been used for the initial studies of this system due to its ability to track detailed information on interactions of interest and time-correlated particle production. This information has been used to optimize system parameters and has also allowed for investigation of image reconstruction techniques including simple backprojection and maximum likelihood expectation maximization (MLEM). A small-scale prototype is being developed for testing and validation of the simulations. This paper will analyze preliminary measurements and will also discuss simulations of several shielded source scenarios.

Patient Size–Specific Analysis of Dose Indexes From CT Lung Cancer Screening

OBJECTIVE The U.S. Centers for Medicare & Medicaid Services (CMS) recently approved the use of low-dose CT for lung cancer screening and described volumetric CT dose index (CTDIvol) requirements. These were based on the National Lung Screening Trial, which used only fixed-tube-current techniques. The aim of this study was to evaluate dose index data from a lung cancer screening program using automatic exposure control (AEC) techniques to ensure compliance with requirements and to correlate dose index values with patient size. MATERIALS AND METHODS CTDIvol, dose-length product (DLP), and body mass index (BMI) data were collected for 563 lung cancer screening examinations performed with AEC between January 1, 2014, through August 31, 2015. CTDIvol and DLP were analyzed according to the patients BMI classification. Results were compared with the CMS requirement that the CTDIvol for a standard-sized patient (height, 170 cm; weight, 70 kg) be 3.0 mGy or less, with adjustments for patients of different sizes. For a subset of patients, the average water-equivalent diameter and size-specific dose estimate were estimated. RESULTS The average CTDIvol for a standard-sized patient was 1.8 mGy, which meets CMS requirements. CTDIvol values were lower for smaller patients and higher for larger patients. Overall, the mean CTDIvol and DLP were 2.1 mGy and 74 mGy⋅cm, respectively. The size-specific dose estimate for the average water-equivalent diameter (27.5 cm) of the patient subset was 2.6 mGy. CONCLUSION The screening protocols using AEC resulted in CTDIvol values that were compliant with CMS requirements. CTDIvol values greater than 3.0 mGy were only observed for overweight or obese patients.

Large-scale Compton-camera simulations, validation experiments, and image reconstruction

Recent efforts in nonproliferation and homeland security areas have focused on designing systems to accurately detect and locate radioactive material. This task is especially challenging when trying to locate material at large distances. One solution that has been under investigation is the Compton camera. In this work, the performance of a large-scale, two-plane Compton camera is investigated using different imaging reconstruction methods on simulated data. The simulation methodology is being validated by measurements conducted using a small-scale prototype of the system in the laboratory environment. The geometry consists of two planar arrays of scintillation detectors.

MO-E-17A-01: BEST IN PHYSICS (IMAGING) - Calculating SSDE From CT Exams Using Size Data Available in the DICOM Header of CT Localizer Radiographs

PURPOSE To demonstrate the feasibility of using existing data stored within the DICOM header of certain CT localizer radiographs as a patient size metric for calculating CT size-specific dose estimates (SSDE). METHODS For most Siemens CT scanners, the CT localizer radiograph (topogram) contains a private DICOM field that stores an array of numbers describing AP and LAT attenuation-based measures of patient dimension. The square root of the product of the AP and LAT size data, which provides an estimate of water-equivalent-diameter (WED), was calculated retrospectively from topogram data of 20 patients who received clinically-indicated abdomen/pelvis (n=10) and chest (n=10) scans (WED-topo). In addition, slice-by-slice water-equivalent-diameter (WED-image) and effective diameter (ED-image) values were calculated from the respective image data. Using TG-204 lookup tables, size-dependent conversion factors were determined based upon WED-topo, WED-image and ED-image values. These conversion factors were used with the reported CTDIvol to calculate slice-by-slice SSDE for each method. Averaging over all slices, a single SSDE value was determined for each patient and size metric. Patientspecific SSDE and CTDIvol values were then compared with patientspecific organ doses derived from detailed Monte Carlo simulations of fixed tube current scans. RESULTS For abdomen/pelvis scans, the average difference between liver dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 18.70%, 8.17%, 6.84%, and 7.58%, respectively. For chest scans, the average difference between lung dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 25.80%, 3.33%, 4.11%, and 7.66%, respectively. CONCLUSION SSDE calculated using WED derived from data in the DICOM header of the topogram was comparable to SSDE calculated using WED and ED derived from axial images; each of these estimated organ dose to within 10% for both abdomen/pelvis and chest CT examinations. The topogrambased method has the advantage that WED data are already provided and therefore available without additional post-processing of the image data. Funding Support: NIH Grant R01-EB017095; Disclosures - Michael McNitt-Gray: Institutional Research Agreement, Siemens AG; Research Support, Siemens AG; Consultant, Flaherty Sensabaugh Bonasso PLLC; Consultant, Fulbright and Jaworski; Disclosures - Cynthia McCollough: Research Grant, Siemens Healthcare.