Purpose To compare the difference of CT coronary artery imaging quality under highflow oxygen uptake and normal breathing, and to investigate the effect of high flow oxygen uptake on the quality of CT coronary artery imaging.Materials and Methods 132 patients underwent coronary CTA examination using 256-slice CT (Philips), among them 71 patients were supplied with highflow oxygen, and the other 61 were asked to breathe normally. Coronary arteries were post-processed and reconstructed on AW 4.4 workstation. Scanning completion rate, signal to noise ratio (SNR), contrast to noise ratios(CNR) and image quality score ofcoronary segment using these two prospective ECG-gating techniques were compared.Results The scanning completion rate and image quality score of the highflow oxygen uptake group were significantly superior to those of the normal breathing group (P<0.05). However, there was no statistically significant difference of SNR and CNR between the two groups (P>0.05).Conclusion Imaging quality of coronary CTA can be improved using highflow oxygen uptake with reduced patient radiation dose, thus worth being used clinically as a simple and practicable method.

Objective To develop a deep learning method for volumetric assessment of traumatic intracerebral hemorrhage(TICH)using the Trans-UNet model and to compare its performance with traditional formula-based methods.Methods CT data from 141 TICH patients admitted to Army Medical Center of PLA between May 2018 and May 2023 were collected.A deep learning method based on the Trans-UNet model was established.Manual delineation via picture archiving and communication system(PACS)was served as the gold standard for comparing the accuracy,consistency,and time efficiency of our method against 10 different formula-based methods for measuring the amount of TICH.Results The median volume of TICH,as manual delineation via PACS,was 1.167 mL,with a median measurement time of 135 s per patient.The median percentage error in volume between the deep learning method and manual delineation via PACS was 3.59％.Spearman correlation coefficient was 0.999(P＜0.001),and a median measurement time was only 4.38 s per patient.In contrast,in the formula-based methods,the lowest median percentage error in volume was 16.451％,the highest Spearman correlation coefficient was 0.986(P＜0.001),and the lowest median measurement time was 20 s for a single patient.The statistical differences were observed in percentage error in volume and measurement time between the 2 types of methods(all P＜0.001).Conclusion Our developed deep learning method for volumetric assessment of TICH is superior to the formula-based methods in terms of measurement accuracy and time efficiency.