270 A. Khallouqi et al.: Radioprotection 2025, 60( 3), 268 – 276 Fig. 2. Hounsfield unit histogram for the central slice, highlighting low-attenuating regions( HU < �700).
where CTDI vol was the mean over the whole scan range, while f( D eff) was the size-dependent conversion factor given in AAPM( 2011) , depending on D eff, calculated in the middle of the scan interval.
In addition, at each image location, SSDE was calculated as a function of D w where f( D w) is the conversion factor based on the measured D w( AAPM, 2014)( Eq.( 4)):
SSDE dw ¼ CTDI vol fðD w Þ: ð4Þ
Due to numerous low-density tissues and elements within the chest, which can significantly reduce radiation attenuation, D eff demonstrates marked divergence from D w, rendering it unsuitable for precise dosimetric calculations. To address this, the relative contribution of low-attenuating regions, represented by F LA, was calculated for each patient based on the image at the center of the scan range. Specifically, F LA was determined by counting the number of pixels within the body contour that had values lower than �700 HU( indicating low-attenuating tissues such as fat), and normalizing this count to the total number of pixels in the region( Fig. 2). Additionally, the relationship between F D ¼ d EFF d W ratio and F LA was analyzed for both male and female patients.
The data was analyzed using IBM SPSS version 23.0( IBM Corporation, Armonk, NY, USA). Descriptive statistics, including the mean, standard deviation, minimum, and maximum values, were computed.
3 Results
The gender distribution within the study population( 48 % male, 52 % female) closely approximates the general demographic balance, potentially offering insights into gender-specific variations in CTPA findings. The mean age
was 60.5 years and between 28 and 94 years old. Analysis of dosimetric data reveals a correlation between dose parameters and patient morphology. The CTDIvol shows a notable increase as a function of the patient’ s lateral diameter( Fig. 3).
Figure 3 illustrates the relationship between D LAT and dose measurements in CTPA, demonstrating a positive correlation for both CTDIvol and SSDE W. A dispersion of data was observed during the analysis, with CTDIvol values ranging from 5.1 to 11.5 mGy and SSDE values extending from 5.0 to 15.8 mGy, across a LAT( lateral) range of 22 to 38 cm. Trend lines indicate a more pronounced increase in SSDE compared to CTDIvol as d LAT increases, evidenced by the slopes of their respective regression lines. This divergence becomes more accentuated at higher LAT values due to the importance of taking into consideration attenuation in dose estimation, particularly for patients with larger body habitus.
Comparison between SSDE Deff and SSDE Dw reveals an average overestimation of 10 % for SSDE Deff. However, indepth analysis of the distribution highlights considerable variability, ranging from �12 %( obese patients) to þ41 %( thin patients). This dispersion shows the importance of accounting for body composition in dose estimation.
In Figure 4, a scatterplot of SSDE using a linear regression revealed a squared correlation coefficient of R 2 = 0.8108 between SSDE computed from D eff against SSDE computed using D w.
In Figure 5, the distributions( density) of the D W and D eff measurements are presented. The average value of D W was calculated to be 23.75 cm, with a standard deviation of 3.24 cm. In contrast, the average value of D eff reached 25.91 cm, accompanied by a standard deviation of 2.70 cm. It is noteworthy that there were no D W values exceeding 32 cm, while 3 % of the D eff measurements were observed beyond this threshold, indicating a limited occurrence of high values.