Department of Radiology, the second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
GE HealthCare, Beijing, China.
Cancer Imaging. 2024 Sep 15;24(1):123. doi: 10.1186/s40644-024-00770-z.
To explore the effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction (ASiR-V) strength level on the detection and characterization of pulmonary nodules by an artificial intelligence (AI) software in ultra-low-dose chest CT (ULDCT).
An anthropomorphic thorax phantom containing 12 spherical simulated nodules (Diameter: 12 mm, 10 mm, 8 mm, 5 mm; CT value: -800HU, -630HU, 100HU) was scanned with three ULDCT protocols: Dose-1 (70kVp:0.11mSv, 100kVp:0.10mSv), Dose-2 (70kVp:0.34mSv, 100kVp:0.32mSv), Dose-3 (70kVp:0.53mSv, 100kVp:0.51mSv). All scanning protocols were repeated five times. CT images were reconstructed using four different strength levels of ASiR-V (0%=FBP, 30%, 50%, 70%ASiR-V) with a slice thickness of 1.25 mm. The characteristics of the physical nodules were used as reference standards. All images were analyzed using a commercially available AI software to identify nodules for calculating nodule detection rate (DR) and to obtain their long diameter and short diameter, which were used to calculate the deformation coefficient (DC) and size measurement deviation percentage (SP) of nodules. DR, DC and SP of different imaging groups were statistically compared.
Image noise decreased with the increase of ASiR-V strength level, and the 70 kV images had lower noise under the same strength level (mean-value 70 kV: 40.14 ± 7.05 (dose 1), 27.55 ± 7.38 (dose 2), 23.88 ± 6.98 (dose 3); 100 kV: 42.36 ± 7.62 (dose 1); 30.78 ± 6.87 (dose 2); 26.49 ± 6.61 (dose 3)). Under the same dose level, there were no differences in DR between 70 kV and 100 kV (dose 1: 58.76% vs. 58.33%; dose 2: 73.33% vs. 70.83%; dose 3: 75.42% vs. 75.42%, all p > 0.05). The DR of GGNs increased significantly at dose 2 and higher (70 kV: 38.12% (dose 1), 60.63% (dose 2), 64.38% (dose 3); 100 kV: 37.50% (dose 1), 59.38% (dose 2), 66.25% (dose 3)). In general, the use of ASiR-V at higher strength levels (> 50%) and 100 kV provided better (lower) DC and SP.
Detection rates are similar between 70 kV and 100 kV scans. The 70 kV images have better noise performance under the same ASiR-V level, while images of 100 kV and higher ASiR-V levels are better in preserving the nodule morphology (lower DC and SP); the dose levels above 0.33mSv provide high sensitivity for nodules detection, especially the simulated ground glass nodules.
探讨管电压、辐射剂量和自适应统计迭代重建（ASiR-V）强度水平对超低剂量胸部 CT（ULDCT）中人工智能（AI）软件检测和描绘肺结节的影响。
采用含有 12 个模拟结节（直径：12mm、10mm、8mm、5mm；CT 值：-800HU、-630HU、100HU）的体模进行扫描，有三个 ULDCT 方案：剂量 1（70kVp：0.11mSv，100kVp：0.10mSv）、剂量 2（70kVp：0.34mSv，100kVp：0.32mSv）、剂量 3（70kVp：0.53mSv，100kVp：0.51mSv）。所有扫描方案均重复五次。使用 ASiR-V 四种不同强度（0%=FBP，30%、50%、70%ASiR-V）进行重建，层厚为 1.25mm。使用商用 AI 软件分析所有图像，以识别结节，计算结节检出率（DR），并获得其长径和短径，用于计算结节的变形系数（DC）和大小测量偏差百分比（SP）。统计比较不同成像组的 DR、DC 和 SP。
图像噪声随 ASiR-V 强度的增加而降低，同一强度下 70kV 图像噪声较低（均值：70kV：40.14±7.05（剂量 1）、27.55±7.38（剂量 2）、23.88±6.98（剂量 3）；100kV：42.36±7.62（剂量 1）、30.78±6.87（剂量 2）、26.49±6.61（剂量 3））。在相同剂量水平下，70kV 和 100kV 的 DR 无差异（剂量 1：58.76%比 58.33%；剂量 2：73.33%比 70.83%；剂量 3：75.42%比 75.42%，均 p>0.05）。在剂量 2 及更高剂量下，GGN 的 DR 显著增加（70kV：38.12%（剂量 1）、60.63%（剂量 2）、64.38%（剂量 3）；100kV：37.50%（剂量 1）、59.38%（剂量 2）、66.25%（剂量 3））。一般来说，使用较高强度（>50%）的 ASiR-V 和 100kV 可以获得更好的（更低）DC 和 SP。
70kV 和 100kV 扫描的检出率相似。在相同的 ASiR-V 水平下，70kV 图像具有更好的噪声性能，而 100kV 及更高 ASiR-V 水平的图像在保持结节形态方面表现更好（更低的 DC 和 SP）；0.33mSv 以上的剂量水平对结节检测具有较高的灵敏度，尤其是模拟磨玻璃结节。
