The development, validation and application of a multi-detector CT (MDCT) scanner model for assessing organ doses to the pregnant patient and the fetus using Monte Carlo simulations

Abstract

The latest multiple-detector technologies have further increased the popularity of x-ray CT as a diagnostic imaging modality. There is a continuing need to assess the potential radiation risk associated with such rapidly evolving multi-detector CT (MDCT) modalities and scanning protocols. This need can be met by the use of CT source models that are integrated with patient computational phantoms for organ dose calculations. Based on this purpose, this work developed and validated an MDCT scanner using the Monte Carlo method, and meanwhile the pregnant patient phantoms were integrated into the MDCT scanner model for assessment of the dose to the fetus as well as doses to the organs or tissues of the pregnant patient phantom. A Monte Carlo code, MCNPX, was used to simulate the x-ray source including the energy spectrum, filter and scan trajectory. Detailed CT scanner components were specified using an iterative trial-and-error procedure for a GE LightSpeed CT scanner. The scanner model was validated by comparing simulated results against measured CTDI values and dose profiles reported in the literature. The source movement along the helical trajectory was simulated using the pitch of 0.9375 and 1.375, respectively. The validated scanner model was then integrated with phantoms of a pregnant patient in three different gestational periods to calculate organ doses. It was found that the dose to the fetus of the 3 month pregnant patient phantom was 0.13 mGy/100 mAs and 0.57 mGy/100 mAs from the chest and kidney scan, respectively. For the chest scan of the 6 month patient phantom and the 9 month patient phantom, the fetal doses were 0.21 mGy/100 mAs and 0.26 mGy/100 mAs, respectively. The paper also discusses how these fetal dose values can be used to evaluate imaging procedures and to assess risk using recommendations of the report from AAPM Task Group 36. This work demonstrates the ability of modeling and validating an MDCT scanner by the Monte Carlo method, as well as assessing fetal and organ doses by combining the MDCT scanner model and the pregnant patient phantom.

Pediatric Chest and Abdominopelvic CT: Organ Dose Estimation Based on 42 Patient Models

“…Because the individual patient organ dose cannot be directly measured, the reference standard for organ dose estimation is Monte Carlo computation, which simulates the x-ray photon transport through the body during the CT acquisition process. To be precise, however, the Monte Carlo simulation requires detailed modeling of (a) the CT scanner and (b) patient anatomy (9)(10)(11). The modeling of the CT scanner requires access to detailed, sometimes proprietary, information about the scanner (12), which is difficult but doable (13,14).…”

Thorax organ dose estimation in computed tomography based on patient CT data using Monte Carlo simulation

“…Imparted energy to the phantom is dependent on the rotation time (duration of one rotation around phantom) and beam intensity (mA). Gu et al (24) used 16 projections for dose calculation in CTDI phantom. Figure 6 shows a case of the simulation set up and dose map in several slices and thorax organ dose calculation processes in this study.…”

Dose estimation in reference and non-reference pediatric patients undergoing computed tomography examinations: a Monte Carlo study

“…In the MCNP code, there are at least three ways to define the specific shape of the fan beam (Khursheed et al, 2002;Gu et al, 2008Gu et al, , 2009. In this research, the same method as Khursheed et al was used.…”

“…In addition, these kinds of information could help the manufacturer to improve the CT machine, so that the benefit to risk ratio would be as high as reasonably achievable (Kalender, 2014). Considering this issue, dosimetry tools that accurately quantify the dose to children would improve administration of CT scans (making informed decision) of the pediatric body (Gu et al, 2009).…”