# Estimating Specific Patient Organ Dose for Chest CT Examinations with Monte Carlo Method
## 3 Results
### Estimation of Organ Doses with CTDI\({}_{vol}\) and WED  
In principle, the organ dose depends on both the radiation output (\(CTDI_{vol}\)) and patient size. Previous studies have indicated that the organ doses normalized by the \(CTDI_{vol}\) could eliminate the impact of the scanner output [30]. Figure 4 plots the simulated  
Figure 3: Organ doses simulated by Monte Carlo methods as a function of _WED_ for male.  
Figure 2: Organ doses simulated by Monte Carlo methods as a function of _WED_ for female.  
lung, breast, and heart doses normalized by the \(CTDI_{\text{red}}\) and the \(WEDs\) for the 18 patients in this study. The lung, heart, and breast doses normalized by \(CTDI_{\text{red}}\) were 1.48 \(\pm\) 0.22, 1.54 \(\pm\) 0.20, and 1.41 \(\pm\) 0.13, respectively. As shown in Figure 4, the normalized lung, heart, and breast doses significantly decrease with the increase of the \(WED\), while the decrease in the normalized breast dose seems more gradual.  
Through the regression analysis, it was also found that all of the three organ doses could be expressed in the form of the same exponential function listed below, and the coefficient of determination (R\({}^{2}\)) of regression equations are 0.85, 0.81, and 0.57 for the lung, heart, and breast, respectively.  
\[\text{D}_{lung}=4.13\times\exp(-0.042\times WED)\times CTDI_{\text{red}} \tag{3}\]  
\[\text{D}_{heart}=4.02\times\exp(-0.041\times WED)\times CTDI_{\text{red}} \tag{4}\]  
\[\text{D}_{breasts}=2.43\times\exp(-0.024\times WED)\times CTDI_{\text{red}} \tag{5}\]  
Based on the above functions, the relative deviations between the estimated organ doses and the simulated ones for the 18 patients are summarized in Table 2. For comparison, the deviations estimated by using the functions built by [PERSON] et al. [17] and [PERSON] et al. [15] are also listed in Table 2. The organ doses for comparison in the table from [PERSON] et al. were calculated using the regional average \(WED\).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Organ**} & \multicolumn{2}{c}{**[PERSON] et al.**} & \multicolumn{2}{c}{**[PERSON] et al.**} & \multicolumn{2}{c}{**This Study**} \\ \cline{2-7}  & **Range** & **Average** & **Range** & **Average** & **Range** & **Average** \\ \hline Lung & (\(-\)13.50–17.40) \% & 6.54\% & (\(-\)13.70–17.92) \% & 7.48\% & (\(-\)13.54–16.56) \% & 5.34\% \\ Heart & – & – & (\(-\)7.18–33.20) \% & 9.74\% & (\(-\)7.65–25.09) \% & 2.13\% \\ Breast & (\(-\)18.15–25.36) \% & \(-\)10.08\% & – & – & (\(-\)8.54–5.90) \% & 0.93\% \\ \hline \hline \end{tabular}  
* Relative deviations = (MC simulation results – estimated organ doses)/MC simulation results \(\times\) 100%.  
\end{table}
Table 2: Relative deviations * between the estimated organ doses and the simulation results for the 18 patients.  
Figure 4: Normalized lung, breast, and heart doses and the \(WED\) for 18 patients.  
As shown in Table 2, for lung, heart, and breast doses, the average deviation of all 18 patients was less than 10.08% when using any of the three functions. It indicates that the function built by [PERSON] et al. and [PERSON] et al. using patients from a Western population are suitable for a Chinese population.