背景:没有研究严格比较了采用不同基于发射技术的最新CT系统的碘定量性能,取决于制造商和型号。
方法:本研究使用特定的定制体模,12种已知浓度的碘化对比剂:0.4、0.5、1.0、2.0、3.0、4.0、5.0、10.0、15.0、20.0、30.0和50.0mg/mL。测试了三种不同的双能量扫描仪:一种使用双源采集的系统(CT#1)和两种使用快速千伏峰切换技术±人工智能(AI)重建方法的系统(CT#2和#3)来自两个不同的制造商。对于每个系统,按照推荐的临床方案进行螺旋扫描.每个碘浓度(mg/mL)进行四次采集,并使用ROI在碘图上进行测量。将平均测量值与已知浓度进行比较,绝对定量误差(AQE)和相对百分比误差(RPE)用于比较每种CT的性能。
结果:获得的测量结果的准确性取决于所研究的模型,而不是采集模式(双源vskVp开关±AI)。在高浓度下定量更精确。CT#2(kVp开关)的RPE值低于10%,CT#1(双源)的RPE值低于25%,但CT#3(kVp开关+AI)明显更高,在低浓度(<3mg/mL)时超过50%。
结论:在幻影的帮助下,我们根据CT模型确定了结果准确性的变异性,有时有明显的偏差。考虑到不同DECT技术在碘标测中的性能,双源(CT#1)和kVp开关(CT#2)技术似乎比kVp开关技术结合基于深度学习的重建(CT#3)更准确,特别是在低浓度(<3mg/mL)。
结论:作为医疗成像设备的主要和日常用户,射线技师的作用是关注成像系统的性能,特别是在进行定量采集时,如碘定量。在CT定量成像(碘图)中,射线技师必须考虑他们的CT系统作为测量工具,并意识到它们的准确性和局限性。
No
study has rigorously compared the performances of iodine quantification on recent CT systems employing different emission-based technologies, depending on the manufacturers and models.
A specific bespoke phantom was used for this
study, with 12 known concentrations of iodinated contrast agent: 0.4, 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, 10.0, 15.0, 20.0, 30.0 and 50.0 mg/mL. Three different dual-energy scanners were tested: one system using dual-source acquisition (CT#1) and two systems using Fast kilovolt-peak switching technology ± artificial intelligence (AI) reconstruction methods (CT#2 and #3) from two different manufacturers. For each system, helical scans were performed following recommended clinical protocols. Four acquisitions were performed per iodine concentration (mg/mL), and measurements were made on iodine-maps using ROIs. Mean measured values were compared to the known concentrations, and the absolute quantification error (AQE) and the relative percentage error (RPE) were used to compare the performances of each CT.
The accuracy of the obtained measurements varied depending on the studied model but not on the acquisition mode (dual-source vs kVp switch ± AI). The quantification was more precise at high concentrations. RPE values were below 10 % with CT#2 (kVp switch) and below 25 % with CT#1 (dual-source), but were significantly higher with CT#3 (kVp switch + AI), exceeding 50 % at low concentrations (<3 mg/mL).
With the help of a phantom, we identified variability in the results accuracy depending on the CT model, with sometimes significant deviation. Considering the performances of the different DECT technologies in iodine mapping, dual-source (CT#1) and kVp switch (CT#2) technologies appear more accurate than kVp switch technology combined with deep-learning-based reconstruction (CT#3) especially at low concentrations (<3 mg/mL).
As the primary and daily user of medical imaging devices, the radiographer role is to be attentive to the performance of imaging systems, particularly when performing quantitative acquisitions like iodine-quantification. In CT quantitative imaging (iodine map), it\'s essential for radiographers to consider their CT systems as measuring tools, and to be aware of their accuracies and limits.