TH-EF-BRA-10: Monte Carlo Simulation of CT Dose Index and Equilibrium Dose-Pitch Product: Effect of Ion Chamber Model On Simulated Dose Response

Authors

  • Liptak C,

    1. Medical Physics Graduate Program, Department of Physics, Cleveland State University, Cleveland, OH
    2. Section of Medical Physics, Imaging Institute, Cleveland Clinic, Cleveland, OH
    3. Siemens Medical Solutions USA, Inc.
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  • Morgan A,

    1. Medical Physics Graduate Program, Department of Physics, Cleveland State University, Cleveland, OH
    2. Section of Medical Physics, Imaging Institute, Cleveland Clinic, Cleveland, OH
    3. Siemens Medical Solutions USA, Inc.
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  • Dong F,

    1. Medical Physics Graduate Program, Department of Physics, Cleveland State University, Cleveland, OH
    2. Section of Medical Physics, Imaging Institute, Cleveland Clinic, Cleveland, OH
    3. Siemens Medical Solutions USA, Inc.
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  • Primak A,

    1. Medical Physics Graduate Program, Department of Physics, Cleveland State University, Cleveland, OH
    2. Section of Medical Physics, Imaging Institute, Cleveland Clinic, Cleveland, OH
    3. Siemens Medical Solutions USA, Inc.
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  • Li X

    1. Medical Physics Graduate Program, Department of Physics, Cleveland State University, Cleveland, OH
    2. Section of Medical Physics, Imaging Institute, Cleveland Clinic, Cleveland, OH
    3. Siemens Medical Solutions USA, Inc.
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Abstract

Purpose:

In Monte Carlo simulations of patient dose from a CT scan, accurate knowledge about the x-ray energy spectra is essential. Simulated CT dose index (CTDI₁₀₀) free-in-air is often used together with measured values to calibrate the intensity of the spectra. To simulate CTDI₁₀₀, a computational model of the ion chamber is required. Various chamber modeling methods have been reported. The purpose of this study was to investigate systematically how chamber modeling affects simulated dose response. Both the pencil chamber and the thimble chamber recently recommended by AAPM TG111 were studied.

Methods:

A Monte Carlo program previously validated for a clinical CT system (SOMATOM Definition Flash, Siemens Healthcare) was used. To examine the effect of chamber modeling, a highly detailed model of an actual CTDI₁₀₀ pencil chamber (model 10×5−3CT, Radcal Corporation) was first defined. Five additional models with reduced detail were then created. They differed from the first model in terms of their dimensions, component parts, material composition, and the use of quadric or voxel geometry. Two models of a TG111 thimble chamber were also created, representing a highly detailed and a rather crude rendition of an actual thimble chamber (model 10×0.6−3CT, Radcal Corporation). Single axial scans for CTDI₁₀₀ chamber models and helical scans for TG111 chamber models were simulated free-in-air at 70 and 120 kVp. Simulated dose responses were then compared amongst different chamber models.

Results:

For the six models of the CTDI₁₀₀ pencil chamber, the coefficient of variation of the simulated CTDI₁₀₀ was 0.9% at 70 kVp and 1.0% at 120 kVp. For the two models of the TG111 thimble chamber, the difference in the simulated equilibrium-dose-pitch product was 1.9% at 70 kVp and 2.1% at 120 kVp.

Conclusion:

In Monte Carlo simulations of CT ion chambers, detailed modeling of chamber geometry and material composition is not necessary.

This research is supported in part by a Faculty Startup Fund from Cleveland State University.

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