Objective:To investigate the feasibility of optimization of coronary computed tomography angiography (CCTA) with pre-scan size-specific dose estimate(SSDE).Methods:Ninety patients from Quzhou People′s Hospital during March and May 2018 who underwent CCTA were defined as modelled patients, the regression equation of body mass index (BMI) and water-equivalent diameter ( dw) were conducted and upper quartile of CTDI vol values was calculated. Other 67 patients were divided into two groups: control group (CCTA scan protocol, based on CTDI vol) and study group (CCTA scan protocol using SSDE). The image quality and radiation dose including breast dose (Dose bre) in two groups were assessed. Results:The positive correlation was found between BMI and dw with a linear regression equation of dw=9.241 + 0.644×BMI( r=0.823, P<0.05), and the upper quartile of CTDI vol was 7.92 mGy. The proportions of high-level image quality were 94.10% (367/390) and 93.93% (402/428) in the control and study groups, respectively ( P>0.05). The median signal to noise ratio (SNR) and contrast to noise ratio (CNR) were 21.08/24.39, 17.24/19.94 in the control and study groups, respectively ( P>0.05). The CTDI vol, SSDE and Dbreof the study group were reduced by 37.04%, 35.77% and 37.37% compared with the control group, and statistically significant differences were found( z=-7.041, t=18.479, 15.079, P<0.05) among them. Conclusions:The CCTA scan protocol based on the pre-scan SSDE can significantly reduce the radiation dose and provide the diagnostic image quality.

Objective:To explore the feasibility for taking weight and body mass index (BMI) to calculate the size-specific dose estimate (SSDE) in abdomen-pelvis CT examination.Methods:512 adult patients undergoing abdomen-pelvis CT examination were retrospectively analyzed. The in-house software based on MATLAB platform were used to calculate automatically water equivalent diameter ( dw), size-dependent conversion factor ( f), SSDE, together with their respective averaged values. The correlations between age, height, weight and BMI with dw were calculated by using Spearman correlation analysis. Two regression equations were established to calculate the SSDE (SSDE weight, SSDE BMI), one for the correlation of weight with dw based on first half of these cases and the other for that between BMI with dw based on another half as the cases to be verified. With reference of the SSDE derived from the in-house software, the averaged relative differences and root-mean-square errors in SSDE weightand SSDE BMI were calculated, respectively. Results:No statistically significant correlation between age and d w ( P>0.05) was shown, but weak correlation between height and dw( r=0.260, P<0.05), strong correlation between either weight or BMI with dw( r=0.879, 0.851, P<0.05). Two regression equations were described as dw=13.808+ 0.184×weight, dw=11.142+ 0.618×BMI. The mean SSDE, SSDE weight and SSDE BMI for the verified patients were (13.55±1.66) mGy, (13.84±2.03) mGy and (13.83±2.02) mGy, respectively. As compared to actual SSDE, the averaged relative differences in SSDE weight and SSDE BMI were 1.97% and 1.87%; 0.38% and 2.75% for male patients; 4.58% and 0.43% for female patients; 0.11% and 3.32% for patients with BMI<18.5 kg/m 2;1.92% and 2.06% for those with 18.5 kg/m 2≤BMI<24.0 kg/m 2;2.57% and 1.57% for those with 24 kg/m 2≤BMI<28.0 kg/m 2;3.28% and -1.36% for those with BMI≥28.0 kg/m 2. The averaged root-mean-square errors in SSDE weight and SSDE BMI were both 0.80 mGy; 0.65 and 0.67 mGy for male patients; 0.98 and 0.59 mGy for female patients; 0.73 and 1.03 mGy for underweight, 0.74 and 0.66 mGy for normal weight, 0.85 and 0.79 mGy for overweight, and 1.10 and 1.32 mGy for obesity. Conclusions:Weight and BMI can be used as the surrogate dw to compute SSDE in adult abdomen-pelvis CT examination. However, Weight rather than BMI is more applied to male patients, and BMI is more suitable for female patients.