Maryam Bostani

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.

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

Purpose: The vast majority of body CT exams are performed with automatic exposure control (AEC), which adapts the mean tube current to the patient size and modulates the tube current either angularly, longitudinally or both. However, most radiation dose estimation tools are based on fixed tube current scans. Accurate estimates of patient dose from AEC scans require knowledge of the tube current values, which is usually unavailable. The purpose of this work was to develop and validate methods to accurately estimate the tube current values prescribed by one manufacturers AEC system to enable accurate estimates of patient dose. Methods: Methods were developed that took into account available patient attenuation information, user selected image quality reference parameters and x‐ray system limits to estimate tube current values for patient scans. Methods consistent with AAPM Report 220 were developed that used patient attenuation data that were: (a) supplied by the manufacturer in the CT localizer radiograph and (b) based on a simulated CT localizer radiograph derived from image data. For comparison, actual tube current values were extracted from the projection data of each patient. Validation of each approach was based on data collected from 40 pediatric and adult patients who received clinically indicated chest (n = 20) and abdomen/pelvis (n = 20) scans on a 64 slice multidetector row CT (Sensation 64, Siemens Healthcare, Forchheim, Germany). For each patient dataset, the following were collected with Institutional Review Board (IRB) approval: (a) projection data containing actual tube current values at each projection view, (b) CT localizer radiograph (topogram) and (c) reconstructed image data. Tube current values were estimated based on the actual topogram (actual‐topo) as well as the simulated topogram based on image data (sim‐topo). Each of these was compared to the actual tube current values from the patient scan. In addition, to assess the accuracy of each method in estimating patient organ doses, Monte Carlo simulations were performed by creating voxelized models of each patient, identifying key organs and incorporating tube current values into the simulations to estimate dose to the lungs and breasts (females only) for chest scans and the liver, kidney, and spleen for abdomen/pelvis scans. Organ doses from simulations using the actual tube current values were compared to those using each of the estimated tube current values (actual‐topo and sim‐topo). Results: When compared to the actual tube current values, the average error for tube current values estimated from the actual topogram (actual‐topo) and simulated topogram (sim‐topo) was 3.9% and 5.8% respectively. For Monte Carlo simulations of chest CT exams using the actual tube current values and estimated tube current values (based on the actual‐topo and sim‐topo methods), the average differences for lung and breast doses ranged from 3.4% to 6.6%. For abdomen/pelvis exams, the average differences for liver, kidney, and spleen doses ranged from 4.2% to 5.3%. Conclusions: Strong agreement between organ doses estimated using actual and estimated tube current values provides validation of both methods for estimating tube current values based on data provided in the topogram or simulated from image data.

Optimizing Radiation Doses for Computed Tomography Across Institutions: Dose Auditing and Best Practices

Importance Radiation doses for computed tomography (CT) vary substantially across institutions. Objective To assess the impact of institutional-level audit and collaborative efforts to share best practices on CT radiation doses across 5 University of California (UC) medical centers. Design, Setting, and Participants In this before/after interventional study, we prospectively collected radiation dose metrics on all diagnostic CT examinations performed between October 1, 2013, and December 31, 2014, at 5 medical centers. Using data from January to March (baseline), we created audit reports detailing the distribution of radiation dose metrics for chest, abdomen, and head CT scans. In April, we shared reports with the medical centers and invited radiology professionals from the centers to a 1.5-day in-person meeting to review reports and share best practices. Main Outcomes and Measures We calculated changes in mean effective dose 12 weeks before and after the audits and meeting, excluding a 12-week implementation period when medical centers could make changes. We compared proportions of examinations exceeding previously published benchmarks at baseline and following the audit and meeting, and calculated changes in proportion of examinations exceeding benchmarks. Results Of 158 274 diagnostic CT scans performed in the study period, 29 594 CT scans were performed in the 3 months before and 32 839 CT scans were performed 12 to 24 weeks after the audit and meeting. Reductions in mean effective dose were considerable for chest and abdomen. Mean effective dose for chest CT decreased from 13.2 to 10.7 mSv (18.9% reduction; 95% CI, 18.0%-19.8%). Reductions at individual medical centers ranged from 3.8% to 23.5%. The mean effective dose for abdominal CT decreased from 20.0 to 15.0 mSv (25.0% reduction; 95% CI, 24.3%-25.8%). Reductions at individual medical centers ranged from 10.8% to 34.7%. The number of CT scans that had an effective dose measurement that exceeded benchmarks was reduced considerably by 48% and 54% for chest and abdomen, respectively. After the audit and meeting, head CT doses varied less, although some institutions increased and some decreased mean head CT doses and the proportion above benchmarks. Conclusions and Relevance Reviewing institutional doses and sharing dose-optimization best practices resulted in lower radiation doses for chest and abdominal CT and more consistent doses for head CT.

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 institutions 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 patients 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 CTDIvol 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.

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.

TU-H-207A-08: Estimating Radiation Dose From Low-Dose Lung Cancer Screening CT Exams Using Tube Current Modulation

PURPOSE The purpose of this work is to estimate effective and lung doses from a low-dose lung cancer screening CT protocol using Tube Current Modulation (TCM) across patient models of different sizes. METHODS Monte Carlo simulation methods were used to estimate effective and lung doses from a low-dose lung cancer screening protocol for a 64-slice CT (Sensation 64, Siemens Healthcare) that used TCM. Scanning parameters were from the AAPM protocols. Ten GSF voxelized patient models were used and had all radiosensitive organs identified to facilitate estimating both organ and effective doses. Predicted TCM schemes for each patient model were generated using a validated method wherein tissue attenuation characteristics and scanner limitations were used to determine the TCM output as a function of table position and source angle. The water equivalent diameter (WED) was determined by estimating the attenuation at the center of the scan volume for each patient model. Monte Carlo simulations were performed using the unique TCM scheme for each patient model. Lung doses were tallied and effective doses were estimated using ICRP 103 tissue weighting factors. Effective and lung dose values were normalized by scanspecific 32 cm CTDIvol values based upon the average tube current across the entire simulated scan. Absolute and normalized doses were reported as a function of WED for each patient. RESULTS For all ten patients modeled, the effective dose using TCM protocols was below 1.5 mSv. Smaller sized patient models experienced lower absolute doses compared to larger sized patients. Normalized effective and lung doses showed some dependence on patient size (R2 = 0.77 and 0.78, respectively). CONCLUSION Effective doses for a low-dose lung screening protocol using TCM were below 1.5 mSv for all patient models used in this study. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.

Investigation of DNA Damage Dose-Response Kinetics after Ionizing Radiation Schemes Similar to CT Protocols

Although there has been extensive research done on the biological response to doses of ionizing radiation relevant to radiodiagnostic procedures, very few studies have examined radiation schemes similar to those frequently utilized in CT exams. Instead of a single exposure, CT exams are often made up of a series of scans separated on the order of minutes. DNA damage dose-response kinetics after radiation doses and schemes similar to CT protocols were established in both cultured (ESW-WT3) and whole blood lymphocytes and compared to higher dose exposures. Both the kinetics and extent of H2AX phosphorylation were found to be dose dependent. Damage induction and detection showed a clear dose response, albeit different, at all time points and differences in the DNA repair kinetics of ESW-WT3 and whole blood lymphocytes were characterized. Moreover, using a modified split-dose in vitro experiment, we show that phosphorylation of H2AX is significantly reduced after exposure to CT doses fractionated over a few minutes compared to the same total dose delivered as a single exposure. Because the split-dose exposures investigated here are more similar to those experienced during a CT examination, it is essential to understand why and how these differences occur. This work provides compelling evidence supporting differential biological responses not only between high and low doses, but also between single and multiple exposures to low doses of ionizing radiation.

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.