(Thursday, 8/2/2018) 10:00 AM - 12:00 PM
Room: Room 202
Purpose: Organ and effective dose from a routine CT procedure is commonly estimated from CT dose index or dose length product using published conversion factors. For non-routine procedures, software such as the ImPACT spreadsheet may be used to allow the specification of scan starting and ending positions. Both approaches, however, are based on simple, unrealistic, definitions of human anatomy. The purpose of this study was to use a realistic patient model to allow dose conversion factors to be quickly established for body CT of arbitrary anatomical coverage.
Methods: Our study included a normal-weight female model from the extended cardiac-torso family. A validated Monte Carlo program was used to simulate a series of 203 contiguous axial scans with a collimation of 10.35 mm to cover the entire patient model. For each axial scan, organ and effective dose were normalized by weighted CTDI (CTDIw). To determine dose conversion factors for a clinical scan with arbitrary anatomical coverage, CTDIw-normalized axial scan doses were summed over the anatomical coverage. The accuracy of this approach was validated for a routine chest scan for variable tube starting angle, pitch, and collimation settings using simulated helical scan dose conversion factors as benchmark.
Results: For organs fully inside the scan coverage, results from summed axial scans differed from helical scan results by <4% for all scan parameter settings tested. Good agreement was also found for the effective dose conversion factor (discrepancies < 6%). For organs on the periphery or outside of the scan coverage, the discrepancies ranged between 0 and 63%, depending on scan parameter settings.
Conclusion: Summing contributions from contiguous axial scans allows for an accurate and quick estimation of dose conversion factors for effective dose and for organs fully inside the scan coverage. Large uncertainties, however, may exist for other organs.
Funding Support, Disclosures, and Conflict of Interest: The work is supported in part by a research grant from Siemens Healthcare.
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