TU-H-207A-08: Estimating Radiation Dose From Low-Dose Lung Cancer Screening CT Exams Using Tube Current Modulation

Authors


Abstract

Purpose:

The purpose of this work is to estimate effective and lung doses from a low-dose lung cancer screening CT protocol using Tube Current Modulation (TCM) across patient models of different sizes.

Methods:

Monte Carlo simulation methods were used to estimate effective and lung doses from a low-dose lung cancer screening protocol for a 64-slice CT (Sensation 64, Siemens Healthcare) that used TCM. Scanning parameters were from the AAPM protocols. Ten GSF voxelized patient models were used and had all radiosensitive organs identified to facilitate estimating both organ and effective doses. Predicted TCM schemes for each patient model were generated using a validated method wherein tissue attenuation characteristics and scanner limitations were used to determine the TCM output as a function of table position and source angle. The water equivalent diameter (WED) was determined by estimating the attenuation at the center of the scan volume for each patient model. Monte Carlo simulations were performed using the unique TCM scheme for each patient model. Lung doses were tallied and effective doses were estimated using ICRP 103 tissue weighting factors. Effective and lung dose values were normalized by scanspecific 32 cm CTDIvol values based upon the average tube current across the entire simulated scan. Absolute and normalized doses were reported as a function of WED for each patient.

Results:

For all ten patients modeled, the effective dose using TCM protocols was below 1.5 mSv. Smaller sized patient models experienced lower absolute doses compared to larger sized patients. Normalized effective and lung doses showed some dependence on patient size (R2 = 0.77 and 0.78, respectively).

Conclusion:

Effective doses for a low-dose lung screening protocol using TCM were below 1.5 mSv for all patient models used in this study.

Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics

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