Document Type

Article

Language

eng

Publication Date

2-1-2019

Publisher

American Association of Physicists in Medicine

Source Publication

Medical Physics

Source ISSN

0094-2405

Abstract

Purpose

To improve dose reporting of CT scans, patient‐specific organ doses are highly desired. However, estimating the dose distribution in a fast and accurate manner remains challenging, despite advances in Monte Carlo methods. In this work, we present an alternative method that deterministically solves the linear Boltzmann transport equation (LBTE), which governs the behavior of x‐ray photon transport through an object.

Methods

Our deterministic solver for CT dose (Acuros CTD) is based on the same approach used to estimate scatter in projection images of a CT scan (Acuros CTS). A deterministic method is used to compute photon fluence within the object, which is then converted to deposited energy by multiplying by known, material‐specific conversion factors.

To benchmark Acuros CTD, we used the AAPM Task Group 195 test for CT dose, which models an axial, fan beam scan (10 mm thick beam) and calculates energy deposited in each organ of an anthropomorphic phantom. We also validated our own Monte Carlo implementation of Geant4 to use as a reference to compare Acuros against for other common geometries like an axial, cone beam scan (160 mm thick beam) and a helical scan (40 mm thick beam with table motion for a pitch of 1).

Results

For the fan beam scan, Acuros CTD accurately estimated organ dose, with a maximum error of 2.7% and RMSE of 1.4% when excluding organs with3provided marginal improvement to the accuracy for the cone beam scan but came at the expense of increased run time. Across the different scan geometries, run time of Acuros CTD ranged from 8 to 23 s.

Conclusions

In this digital phantom study, a deterministic LBTE solver was capable of fast and accurate organ dose estimates.

Comments

Accepted version. Medical Physics, Vol. 46, No. 2 (February 2019): 925-933. DOI. © 2019 American Association of Physicists in Medicine. Used with permission.

Available for download on Monday, February 03, 2020

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