Effects of tube voltage, radiation dose and adaptive statistical iterative reconstruction strength level on the detection and characterization of pulmonary nodules in ultra-low-dose chest CT

IF 3.5 2区 医学 Q2 ONCOLOGY Cancer Imaging Pub Date : 2024-09-15 DOI:10.1186/s40644-024-00770-z
Yue Yao, Xuan Su, Lei Deng, JingBin Zhang, Zengmiao Xu, Jianying Li, Xiaohui Li
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Abstract

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.
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管电压、辐射剂量和自适应统计迭代重建强度水平对超低剂量胸部 CT 中肺部结节检测和定性的影响
探讨超低剂量胸部 CT(ULDCT)中管电压、辐射剂量和自适应统计迭代重建(ASiR-V)强度水平对人工智能(AI)软件检测和表征肺结节的影响。用三种超低剂量胸部 CT 方案扫描了一个拟人胸部模型,该模型包含 12 个球形模拟结节(直径:12 毫米、10 毫米、8 毫米、5 毫米;CT 值:-800HU、-630HU、100HU):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。使用四种不同强度的 ASiR-V (0%=FBP、30%、50%、70%ASiR-V)重建 CT 图像,切片厚度为 1.25 毫米。物理结节的特征被用作参考标准。使用市售人工智能软件对所有图像进行分析,识别结节以计算结节检出率(DR),并获得结节的长径和短径,用于计算结节的变形系数(DC)和尺寸测量偏差百分比(SP)。对不同成像组的 DR、DC 和 SP 进行统计比较。图像噪声随 ASiR-V 强度的增加而降低,在相同强度下,70 kV 图像的噪声较低(平均值 70 kV:40.14 ± 7.05(剂量 1),27.55 ± 7.38(剂量 2),23.88 ± 6.98(剂量 3);100 kV: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,70 千伏和 100 千伏之间的 DR 没有差异(剂量 1:58.76% vs. 58.33%;剂量 2:73.33% vs. 70.83%;剂量 3:75.42% vs. 75.42%,均 p > 0.05)。剂量 2 及以上时,GGN 的 DR 显著增加(70 kV:38.12%(剂量 1),60.63%(剂量 2),64.38%(剂量 3);100 kV:37.50%(剂量 1),59.38%(剂量 2),66.25%(剂量 3))。一般来说,在较高强度水平(> 50%)和 100 kV 下使用 ASiR-V 可提供更好(更低)的直流和 SP。70 千伏和 100 千伏扫描的检测率相似。在相同的 ASiR-V 水平下,70 kV 图像的噪声性能更好,而 100 kV 和更高 ASiR-V 水平的图像在保留结节形态方面更好(DC 和 SP 更低);0.33mSv 以上的剂量水平可提供高灵敏度的结节检测,尤其是模拟磨玻璃结节。
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来源期刊
Cancer Imaging
Cancer Imaging ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
7.00
自引率
0.00%
发文量
66
审稿时长
>12 weeks
期刊介绍: Cancer Imaging is an open access, peer-reviewed journal publishing original articles, reviews and editorials written by expert international radiologists working in oncology. The journal encompasses CT, MR, PET, ultrasound, radionuclide and multimodal imaging in all kinds of malignant tumours, plus new developments, techniques and innovations. Topics of interest include: Breast Imaging Chest Complications of treatment Ear, Nose & Throat Gastrointestinal Hepatobiliary & Pancreatic Imaging biomarkers Interventional Lymphoma Measurement of tumour response Molecular functional imaging Musculoskeletal Neuro oncology Nuclear Medicine Paediatric.
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Multi-parameter MRI radiomics model in predicting postoperative progressive cerebral edema and hemorrhage after resection of meningioma. Correction: New frontiers in domain-inspired radiomics and radiogenomics: increasing role of molecular diagnostics in CNS tumor classification and grading following WHO CNS-5 updates. Role of [18F]FDG PET/CT in the management of follicular cell-derived thyroid carcinoma. Differentiation of pathological subtypes and Ki-67 and TTF-1 expression by dual-energy CT (DECT) volumetric quantitative analysis in non-small cell lung cancer. Ultrasound-guided intra-tumoral administration of directly-injected therapies: a review of the technical and logistical considerations.
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