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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 was: (1) supplied by the manufacturer in the CT localizer radiograph and (2) 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: (1) projection data containing actual tube current values at each projection view, (2) CT localizer radiograph (topogram) and (3) 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%....

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.

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 limi...

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.

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.

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.

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.