摘要目的:探讨TrueFidelity深度学习重建算法在腹盆部CT血管成像（CTA）低剂量扫描时的应用价值。方法:前瞻性纳入2020年6月至2021年3月就诊于西安交通大学第一附属医院，临床申请行腹盆部CTA的患者。所有患者均行低剂量腹盆部CTA扫描，管电压为80 kV，管电流为智能管电流（100~720 mA），扫描完成后均使用传统滤波反投影（FBP）、自适应统计迭代重建算法（ASIR-V 50%）、TrueFidelity算法［降噪强度：中等强度（TF-M）和高强度（TF-H）］4种重建算法对图像进行重建。测量腹主动脉、同层腰大肌及皮下脂肪的CT值和CT值的标准差（SD），计算信噪比（SNR）和对比噪声比（CNR），另外测量腰大肌密度均匀区域的CT值偏度，同时使用5分法评价所有图像的颗粒度、模糊度及股骨头层面的硬化伪影。客观评价指标采用重复测量单因素方差分析进行检验。结果:共纳入46例患者。CT检查的辐射剂量为（1.09±0.31）mGy。4组重建图像血管和肌肉的CT值比较差异无统计学意义（ P>0.05），SD值比较差异有统计学意义（ P<0.001），FBP组的SD值最大，TF-H组的SD值最小。SNR和CNR比较差异有统计学意义（ P<0.001），整体趋势与SD值趋势相反。偏度值比较4组差异无统计学意义。颗粒度评分FBP组评分最高，TF-H组评分最低，4组间差异有统计学意义。模糊度评分TF-H组评分稍高于其余3组，但差异无统计学意义。硬化伪影评分FBP和ASIR-V 50%组评分最差，TF-H最好（ P<0.001）。 结论:综合考虑图像噪声、模糊度、均匀度和硬化伪影的表现，在腹盆部CTA低剂量扫描时，相比于FBP和ASIR-V，TrueFidelity重建算法可以提供更优的图像质量，其中TF-H的图像质量最佳。

abstractsObjective:To investigate the practicality of TrueFidelity deep learning reconstruction algorithm in low-dose abdominal and pelvic CT angiography (CTA).Methods:The patients who required abdominal and pelvic CTA were prospectively included at the First Affiliated Hospital of Xi′an Jiaotong University from June 2020 to March 2021. All patients underwent low-dose CTA with a tube voltage of 80 kV and smart tube current modulation (100-720 mA). Images were reconstructed using the traditional FBP, adaptive statistical iterative reconstruction with a strength of 50% (ASIR-V 50%), TrueFidelity with medium (TF-M) and high (TF-H) strength. The CT value and standard deviation (SD value) of the abdominal aorta, psoas major muscle and subcutaneous fat in the same layer were measured, signal to noise ratio (SNR) and contrast to noise ratio (CNR) were calculated. We also introduced the measurement of skewness of CT value in psoas major muscle with uniform density. The above indexes of the four groups of reconstructed images were compared. A 5-point scoring method was used to evaluate the granularity, fuzziness and beam-hardening artifacts of all images. Objective measurement indicators, such as CT values, were tested by repeated measure ANOVA with the Bonferroni post hoc test.Results:There were forty-six patients in the study. The volume CT dose index of the scan was low at (1.09±0.31)mGy. There was no significant difference in CT values of vessels and muscles between the four groups ( P>0.05), but there was a significant difference in SD value( P<0.001). The SD value of the FBP group was the largest and that of the TF-H group was the smallest. The difference between SNR and CNR was statistically significant ( P<0.001), and the overall trend was opposite to that of the SD value. There was no significant difference in the skewness between the four groups. The granularity score of the FBP group was the largest, that of the TF-H group was the smallest, and there was a significant difference among the four groups. The score of fuzziness in the TF-H group was slightly higher than that in the other three groups, but there was no significant difference. The beam-hardening artifact score of FBP and ASIR-V 50% group was the worst, and the TF-H group was the best ( P<0.001). Conclusions:Compared with FBP and ASIR-V, TrueFidelity reconstruction algorithm provides better image quality (comprehensively considering image noise, fuzziness, uniformity, and hardening artifacts) in low-dose CT scanning of abdominal and pelvic vessels, and TF-H has the best image quality.