Purpose:A recent work has demonstrated the feasibility of estimating the dose to individual organs from multidetector CT exams using patient-specific, scanner-independent CTDI vol -to-organ-dose conversion coefficients. However, the previous study only investigated organ dose to a single patient model from a full-body helical CT scan. The purpose of this work was to extend the validity of this dose estimation technique to patients of any size undergoing a common clinical exam. This was done by determining the influence of patient size on organ dose conversion coefficients generated for typical abdominal CT exams. Methods: Monte Carlo simulations of abdominal exams were performed using models of 64-slice MDCT scanners from each of the four major manufacturers to obtain dose to radiosensitive organs for eight patient models of varying size, age, and gender. The scanner-specific organ doses were normalized by corresponding CTDI vol values and averaged across scanners to obtain scannerindependent CTDI vol -to-organ-dose conversion coefficients for each patient model. In order to obtain a metric for patient size, the outer perimeter of each patient was measured at the central slice of the abdominal scan region. Then, the relationship between CTDI vol -to-organ-dose conversion coefficients and patient perimeter was investigated for organs that were directly irradiated by the abdominal scan. These included organs that were either completely ͑"fully irradiated"͒ or partly ͑"partially irradiated"͒ contained within the abdominal exam region. Finally, dose to organs that were not at all contained within the scan region ͑"nonirradiated"͒ were compared to the doses delivered to fully irradiated organs. Results: CTDI vol -to-organ-dose conversion coefficients for fully irradiated abdominal organs had a strong exponential correlation with patient perimeter. Conversely, partially irradiated organs did not have a strong dependence on patient perimeter. In almost all cases, the doses delivered to nonirradiated organs were less than 5%, on average across patient models, of the mean dose of the fully irradiated organs. Conclusions: This work demonstrates the feasibility of calculating patient-specific, scannerindependent CTDI vol -to-organ-dose conversion coefficients for fully irradiated organs in patients undergoing typical abdominal CT exams. A method to calculate patient-specific, scanner-specific, and exam-specific organ dose estimates that requires only knowledge of the CTDI vol for the scan protocol and the patient's perimeter is thus possible. This method will have to be extended in future 820 820 Med. Phys. 38 "2…,

This work has revealed that there is considerable variation among modern MDCT scanners in both CTDIvol and organ dose values. Because these variations are similar, CTDIvol can be used as a normalization factor with excellent results. This demonstrates the feasibility of establishing scanner-independent organ dose estimates by using CTDIvol to account for the differences between scanners.

The purpose of this study was to present a method for generating x-ray source models for performing Monte Carlo ͑MC͒ radiation dosimetry simulations of multidetector row CT ͑MDCT͒ scanners. These so-called "equivalent" source models consist of an energy spectrum and filtration description that are generated based wholly on the measured values and can be used in place of proprietary manufacturer's data for scanner-specific MDCT MC simulations. Required measurements include the half value layers ͑HVL 1 and HVL 2 ͒ and the bowtie profile ͑exposure values across the fan beam͒ for the MDCT scanner of interest. Using these measured values, a method was described ͑a͒ to numerically construct a spectrum with the calculated HVLs approximately equal to those measured ͑equivalent spectrum͒ and then ͑b͒ to determine a filtration scheme ͑equivalent filter͒ that attenuates the equivalent spectrum in a similar fashion as the actual filtration attenuates the actual x-ray beam, as measured by the bowtie profile measurements. Using this method, two types of equivalent source models were generated: One using a spectrum based on both HVL 1 and HVL 2 measurements and its corresponding filtration scheme and the second consisting of a spectrum based only on the measured HVL 1 and its corresponding filtration scheme. Finally, a third type of source model was built based on the spectrum and filtration data provided by the scanner's manufacturer. MC simulations using each of these three source model types were evaluated by comparing the accuracy of multiple CT dose index ͑CTDI͒ simulations to measured CTDI values for 64-slice scanners from the four major MDCT manufacturers. Comprehensive evaluations were carried out for each scanner using each kVp and bowtie filter combination available. CTDI experiments were performed for both head ͑16 cm in diameter͒ and body ͑32 cm in diameter͒ CTDI phantoms using both central and peripheral measurement positions. Both equivalent source model types result in simulations with an average root mean square ͑RMS͒ error between the measured and simulated values of approximately 5% across all scanner and bowtie filter combinations, all kVps, both phantom sizes, and both measurement positions, while data provided from the manufacturers gave an average RMS error of approximately 12% pooled across all conditions. While there was no statistically significant difference between the two types of equivalent source models, both of these model types were shown to be statistically significantly different from the source model based on manufacturer's data. These results demonstrate that an equivalent source model based only on measured values can be used in place of manufacturer's data for Monte Carlo simulations for MDCT dosimetry.

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.