(Sunday, 7/14/2019) 4:00 PM - 5:00 PM
Room: 221CD
Purpose: The Size-Specific Dose Estimate (SSDE) accounts for patient size and should be widely available in the near future. While not intended to represent organ doses, the purpose of this work was to explore the ability of SSDE to provide a reasonable estimate of organ doses in routine chest examinations across a wide range of patient sizes.
Methods: Raw projection data, topograms, and patient protocol pages for 29 patients (12 pediatric, 15 adult, and 2 bariatric) who underwent routine chest CT exams with tube current modulation (TCM) were gathered from a Siemens Definition AS64 MDCT. Image data were reconstructed and were semi-automatically segmented to identify lung and glandular breast tissues. Segmented image data were used to create voxelized models of chest anatomy. TCM data was extracted from the raw projection data to describe the tube current values as a function of gantry angle and table location. Voxelized patient models and TCM data were incorporated into a validated Monte Carlo (MC) simulation engine to estimate absolute lung (Dlung) and breast (Dbreast) dose using an MDCT source model of the AS64 scanner. Normalized lung (nDlung) and breast (nDbreast) doses were obtained by dividing Dlung and Dbreast by the CTDIvol values from the patient protocol pages. For each patient, SSDE values were acquired using AAPM Report 204 and the water equivalent diameter (Dw) information in the topograms. Normalized doses were then compared to SSDE f-factors and percent differences were recorded.
Results: The average difference and bias for nDlung relative to SSDE f-factors was observed to be 14.9% and 21.1%, respectively. The average difference and bias for nDbreast relative to SSDE f-factors was observed to be 31.0% and 38.8%, respectively.
Conclusion: SSDE may serve as a reasonable estimate for nDlung and nDbreast for many patient sizes, but may overestimate organ doses for bariatric patients.
Funding Support, Disclosures, and Conflict of Interest: Michael McNitt-Gray, PhD - Departmental master research agreement with Siemens Healthineers
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