Purpose: To develop and demonstrate an automated computational method used to provide organ and effective dose assessments of computed tomography (CT) examinations, using a pre‐calculated organ dose database. Methods: A five dimensional organ dose matrix, D (33 organs, 6 age groups, 2 genders, 3 tube potentials, scan positions with 1 cm z‐resolution), was calculated using a Monte Carlo transport method which couples a reference CT scanner model (Siemens Sensation 16) with a series of pediatric and adult hybrid computational phantoms. CT scans with a given scan range were approximated as the sum of doses from multiple axial slices included in the scan range of interest. Patient‐specific doses were calculated using the organ and effective doses normalized to CTDIvol of the reference scanner and patient/scan‐specific parameters: body part scanned, CTDIvol, age, gender, scan length, kVp, and mAs. The parameters were obtained from a manually‐ and electronically‐extracted DICOM dataset of 3,982 CT exams randomly selected from five health care systems participating in the NCI‐funded Cancer Research Network (CRN). Illustrative dose analysis and comparison of dose for a subset of scans were performed. Results: Based on an evaluation of 3,983 CT examinations the following values were provided: effective dose, CTDIvol, dose length product (DLP) and the absorbed doses for 33 organs. Illustrative analysis for brain dose in head scans revealed a large dose variation in the age less than 30‐year scans (COV=0.445) compared to the age above 30‐year (COV=0.104). We observed that brain dose is strongly correlated with scan length compared to other scan parameters. Conclusion: The automated organ and effective dose calculation method developed in this study reduces the time needed to calculate doses on a large number of patients. We have successfully utilized this program for a variety of CT‐related studies including retrospective epidemiological study and CT dose trend analysis studies.
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging