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

PURPOSE: The purpose of this study was to estimate the radiation dose to the lung and breast as well as the effective dose from tube current modulated (TCM) lung cancer screening (LCS) scans across a range of patient sizes. METHODS: Monte Carlo (MC) methods were used to calculate lung, breast, and effective doses from a low-dose LCS protocol for a 64-slice CT that used TCM. Scanning parameters were from the protocols published by AAPM's Alliance for Quality CT. To determine lung, breast, and effective doses from lung cancer screening, eight GSF/ICRP voxelized phantom models with all radiosensitive organs identified were used to estimate lung, breast, and effective doses. Additionally, to extend the limited size range provided by the GSF/ICRP phantom models, 30 voxelized patient models of thoracic anatomy were generated from LCS patient data. For these patient models, lung and breast were semi-automatically segmented. TCM schemes for each of the GSF/ICRP phantom models were generated using a validated method wherein tissue attenuation and scanner limitations were used to determine the TCM output as a function of table position and source angle. TCM schemes for voxelized patient models were extracted from the raw projection data. The water equivalent diameter, Dw, was used as the patient size descriptor. Dw was estimated for the GSF/ICRP models. For the thoracic patient models, Dw was extracted from the DICOM header of the CT localizer radiograph. MC simulations were performed using the TCM scheme for each model. Absolute organ doses were tallied and effective doses were calculated using ICRP 103 tissue weighting factors for the GSF/ICRP models. Metrics of scanner radiation output were determined based on each model's TCM scheme, including CTDIvol , dose length product (DLP), and CTDIvol, Low Att , a previously described regional metric of scanner output covering most of the lungs and breast. All lung and breast doses values were normalized by scan-specific CTDIvol and CTDIvol, Low Att . Effective doses were normalized by scan-specific CTDIvol and DLP. Absolute and normalized doses were reported as a function of Dw. RESULTS: Lung doses normalized by CTDIvol, Low Att were modeled as an exponential relationship with respect to Dw with coefficients of determination (R2 ) of 0.80. Breast dose normalized by CTDIvol, Low Att was modeled with an exponential relationship to Dw with an R2 of 0.23. For all eight GSF/ICRP phantom models, the effective dose using TCM protocols was below 1.6 mSv. Effective doses showed some size dependence but when normalized by DLP demonstrated a constant behavior. CONCLUSION: Lung, breast, and effective doses from LCS CT exams with TCM were estimated with respect to patient size. Normalized lung dose can be reasonably estimated with a measure of a patient size such as Dw and regional metric of CTDIvol covering the thorax such as CTDIvol, Low Att , while normalized breast dose can also be estimated with a regional metric of CTDIvol but with a larger degree of variability than observed for lung. Effective dose normalized by DLP can be estimated with a constant multiplier.

Low-dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge.

PURPOSE: Using common datasets, to estimate and compare the diagnostic performance of image-based denoising techniques or iterative reconstruction algorithms for the task of detecting hepatic metastases. METHODS: Datasets from contrast-enhanced CT scans of the liver were provided to participants in an NIH-, AAPM- and Mayo Clinic-sponsored Low Dose CT Grand Challenge. Training data included full-dose and quarter-dose scans of the ACR CT accreditation phantom and 10 patient examinations; both images and projections were provided in the training data. Projection data were supplied in a vendor-neutral standardized format (DICOM-CT-PD). Twenty quarter-dose patient datasets were provided to each participant for testing the performance of their technique. Images were provided to sites intending to perform denoising in the image domain. Fully preprocessed projection data and statistical noise maps were provided to sites intending to perform iterative reconstruction. Upon return of the denoised or iteratively reconstructed quarter-dose images, randomized, blinded evaluation of the cases was performed using a Latin Square study design by 11 senior radiology residents or fellows, who marked the locations of identified hepatic metastases. Markings were scored against reference locations of clinically or pathologically demonstrated metastases to determine a per-lesion normalized score and a per-case normalized score (a faculty abdominal radiologist established the reference location using clinical and pathological information). Scores increased for correct detections; scores decreased for missed or incorrect detections. The winner for the competition was the entry that produced the highest total score (mean of the per-lesion and per-case normalized score). Reader confidence was used to compute a Jackknife alternative free-response receiver operating characteristic (JAFROC) figure of merit, which was used for breaking ties. RESULTS: 103 participants from 90 sites and 26 countries registered to participate. Training data were shared with 77 sites that completed the data sharing agreements. Subsequently, 41 sites downloaded the 20 test cases, which included only the 25% dose data (CTDIvol = 3.0 ± 1.8 mGy, SSDE = 3.5 ± 1.3 mGy). 22 sites submitted results for evaluation. One site provided binary images and one site provided images with severe artifacts; cases from these sites were excluded from review and the participants removed from the challenge. The mean (range) per-lesion and per-case normalized scores were -24.2% (-75.8%, 3%) and 47% (10%, 70%), respectively. Compared to reader results for commercially reconstructed quarter-dose images with no noise reduction, 11 of the 20 sites showed a numeric improvement in the mean JAFROC figure of merit. Notably two sites performed comparably to the reader results for full-dose commercial images. The study was not designed for these comparisons, so wide confidence intervals surrounded these figures of merit and the results should be used only to motivate future testing. CONCLUSION: Infrastructure and methodology were developed to rapidly estimate observer performance for liver metastasis detection in low-dose CT examinations of the liver after either image-based denoising or iterative reconstruction. The results demonstrated large differences in detection and classification performance between noise reduction methods, although the majority of methods provided some improvement in performance relative to the commercial quarter-dose images with no noise reduction applied.

Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.

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

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

A virtual clinical trial using projection-based nodule insertion to determine radiologist reader performance in lung cancer screening CT.

Task-based image quality assessment using model observers is promising to provide an efficient, quantitative, and objective approach to CT dose optimization. Before this approach can be reliably used in practice, its correlation with radiologist performance for the same clinical task needs to be established. Determining human observer performance for a well-defined clinical task, however, has always been a challenge due to the tremendous amount of efforts needed to collect a large number of positive cases. To overcome this challenge, we developed an accurate projection-based insertion technique. In this study, we present a virtual clinical trial using this tool and a low-dose simulation tool to determine radiologist performance on lung-nodule detection as a function of radiation dose, nodule type, nodule size, and reconstruction methods. The lesion insertion and low-dose simulation tools together were demonstrated to provide flexibility to generate realistically-appearing clinical cases under well-defined conditions. The reader performance data obtained in this virtual clinical trial can be used as the basis to develop model observers for lung nodule detection, as well as for dose and protocol optimization in lung cancer screening 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 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 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 patient's 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.

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.

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.

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.

Size-specific, scanner-independent organ dose estimates in contiguous axial and helical head CT examinations.

PURPOSE: AAPM Task Group 204 introduced size-specific dose estimates for pediatric and adult patients undergoing body CT examinations. This investigation extends that work to head CT exams by using Monte Carlo simulations to develop size-specific, scanner-independent CTDIvol-to-organ-dose conversion coefficients. METHODS: Using eight patient models from the GSF family of voxelized phantoms, dose to the brain and lens of the eye was estimated using Monte Carlo simulations of contiguous axial and helical scans for 64-slice multidetector CT scanners from four major manufacturers. For each patient model and scan mode, scanner-independent CTDIvol-to-organ-dose conversion coefficients were calculated by normalizing organ dose by scanner-specific 16 cm CTDIvol values and averaging across all scanners. Head size was measured using both geometric and attenuation-based size metrics. Head perimeter and effective diameter (ED), both geometric size metrics, were measured directly from the GSF data at the first slice superior to the eyes. Because the GSF models' pixel data are provided in terms of organ identification numbers instead of CT numbers, an indirect estimate of water equivalent diameter (WED), an attenuation-based size metric, was determined based on the relationships between WED and both ED and perimeter for a sample of patient data. Correlations between CTDIvol-to-organ-dose conversion coefficients and the various patient size metrics were then explored. RESULTS: The analysis of the patient data revealed a best-fit linear relationship (R(2) of 0.87) between ED and WED across a wide variety of patient sizes. Using this relationship along with ED determined from the GSF data, WED was estimated for each GSF model. An exponential relationship between CTDIvol normalized organ dose and WED was observed for both contiguous axial and helical scanning. For head perimeter and ED measured directly from the GSF data, an exponential relationship between CTDIvol normalized organ dose and patient size was also observed for each scan mode. For all patient size metrics and scan modes, R(2) of the exponential fits ranged from 0.92 to 0.93 and 0.73 to 0.85 for the brain and lens of the eye, respectively. CONCLUSIONS: For all scan modes, strong correlation exists between CTDIvol normalized brain dose and both geometric and attenuation-based patient size metrics. A slightly lower correlation between CTDIvol normalized organ dose and patient size was observed for the lens of the eye. This may be due to the combination of the eye lens being a small peripheral organ and the presence of surface dose variation in both contiguous axial and helical scanning. Results indicate that robust estimates of patient-specific head CT dose may be provided using the size-specific, scanner-independent CTDIvol-to-organ-dose conversion coefficients described in this work.

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.

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.

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.

Interaction of anesthetics with neurotransmitter release machinery proteins.

General anesthetics produce anesthesia by depressing central nervous system activity. Activation of inhibitory GABA(A) receptors plays a central role in the action of many clinically relevant general anesthetics. Even so, there is growing evidence that anesthetics can act at a presynaptic locus to inhibit neurotransmitter release. Our own data identified the neurotransmitter release machinery as a target for anesthetic action. In the present study, we sought to examine the site of anesthetic action more closely. Exocytosis was stimulated by directly elevating the intracellular Ca(2+) concentration at neurotransmitter release sites, thereby bypassing anesthetic effects on channels and receptors, allowing anesthetic effects on the neurotransmitter release machinery to be examined in isolation. Three different PC12 cell lines, which had the expression of different release machinery proteins stably suppressed by RNA interference, were used in these studies. Interestingly, there was still significant neurotransmitter release when these knockdown PC12 cells were stimulated. We have previously shown that etomidate, isoflurane, and propofol all inhibited the neurotransmitter release machinery in wild-type PC12 cells. In the present study, we show that knocking down synaptotagmin I completely prevented etomidate from inhibiting neurotransmitter release. Synaptotagmin I knockdown also diminished the inhibition produced by propofol and isoflurane, but the magnitude of the effect was not as large. Knockdown of SNAP-25 and SNAP-23 expression also changed the ability of these three anesthetics to inhibit neurotransmitter release. Our results suggest that general anesthetics inhibit the neurotransmitter release machinery by interacting with multiple SNARE and SNARE-associated proteins.

Comparison of methods of estimation of lifetime cancer risk due to chronic exposure to transuranics.

The cancer risk due to chronic transuranic intakes is properly calculated using an integration over multiple years of intake of the annual effective dose rates arising each year following an intake multiplied by age-dependent risk functions for the year during which the dose is actually received. Approximate computations of risk involving sums of the products of committed effective dose and the age-dependent risk functions for each year of intake indicate the appropriateness of the committed effective dose as a surrogate quantity for risk when applied to different circumstances. The assumptions that all dose is received at the time of intake with committed effective dose and that risk is uniform over a range of ages both lead to a misuse of the available age-dependent risk functions and thus contribute to a divergence from the true risk associated with an intake over multiple years. Comparison of the correctly integrated risk functions with the approximations gives insights into how the current committed effective dose models used for regulatory purposes are not necessarily indicative of the risk for chronic intakes of radionuclides with long biological and radiological half-lives. A summary and comparison of such computations for transuranic intakes was prepared for the ingestion of water and the inhalation of different particle sizes by both males and females. Risk results for committed effective dose consistently overestimated risks by approximately 100% for all transuranics for ingestion models and approximately 75% for all transuranics for Type M inhalation models considering age-dependent risk models. For constant risk as a function of age, the committed effective dose integration underestimated the actual risk situation by nearly 60% for ingestion and 50% for Type M inhalation during the first 20 y.

Etomidate and propofol inhibit the neurotransmitter release machinery at different sites.

The mechanism of general anaesthetic action is only partially understood. Facilitation of inhibitory GABAA receptors plays an important role in the action of most anaesthetics, but is thought to be especially relevant in the case of intravenous anaesthetics, like etomidate and propofol. Recent evidence suggests that anaesthetics also inhibit excitatory synaptic transmission via a presynaptic mechanism(s), but it has been difficult to determine whether these agents act on the neurotransmitter release machinery itself. In the present study we sought to determine whether the intravenous anaesthetics propofol and etomidate inhibit the release machinery. For these studies we used an experimental approach that directly regulated [Ca2+]i at neurotransmitter release sites, thereby bypassing anaesthetic effects on channels and receptors in order to allow anaesthetic effects on the neurotransmitter release machinery to be examined in isolation. The data show that clinically relevant concentrations of propofol and etomidate inhibited the neurotransmitter release machinery in neurosecretory cells and in cultured hippocampal neurons. md130A is a mutant form of syntaxin with a truncated C-terminus. Overexpressing md130A in PC12 cells completely eliminated the reduction in neurotransmitter release produced by propofol, without affecting release itself. In contrast, overexpressing md130A in PC12 cells had little or no effect on the response to etomidate. These results suggest that both propofol and etomidate inhibit neurotransmitter release by a direct interaction with SNAREs and/or SNARE-associated proteins but they do so at different sites.

Two classes of deleterious recessive alleles in a natural population of zebrafish, Danio rerio.

Natural populations carry deleterious recessive alleles which cause inbreeding depression. We compared mortality and growth of inbred and outbred zebrafish, Danio rerio, between 6 and 48 days of age. Grandparents of the studied fish were caught in the wild. Inbred fish were generated by brother-sister mating. Mortality was 9% in outbred fish, and 42% in inbred fish, which implies at least 3.6 lethal equivalents of deleterious recessive alleles per zygote. There was no significant inbreeding depression in the growth, perhaps because the surviving inbred fish lived under less crowded conditions. In contrast to alleles that cause embryonic and early larval mortality in the same population, alleles responsible for late larval and early juvenile mortality did not result in any gross morphological abnormalities. Thus, deleterious recessive alleles that segregate in a wild zebrafish population belong to two sharply distinct classes: early-acting, morphologically overt, unconditional lethals; and later-acting, morphologically cryptic, and presumably milder alleles.