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Objective:To investigate the feasibility of using spectral CT chest enhancement venous phase images to obtain virtual non-contrast (VNC) images and virtual arterial phase images to achieve one phase scan instead of three phase scans.Methods:Imaging data of 100 patients who underwent spectral CT chest plain and dual-phase enhancement scans at the First Affiliated Hospital of Kunming Medical University from January to May 2022 were analyzed retrospectively. The venous phase images of all patients were post-processed to obtain virtual non contrast (VNC) and 40 keV virtual mono-energy images (VMI) for simulated arterial phase images (Vart). Image quality and lesion detection were compared between true non-contrast (TNC) and VNC images, and conventional arterial phase (CIart) and Vart images by paired t-test, Wilcoxon test and McNemar test. Objective evaluation indexes of image quality included thoracic aorta, all levels of pulmonary artery, T4 vertebral bone cancellous, chest wall fat CT value, background noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR); the subjective score of image quality was assessed by double-blind method on a 5-point scale; the assessment of lesion detection included the detection rate of calcified foci and pulmonary nodules size, density, volume, percentage of solid components and imaging characteristics. Results:Except for chest wall fat and T4 vertebral bone cancellous, the differences in CT values between VNC and TNC images were not statistically significant ( P>0.05); Except for right upper pulmonary artery and right lower pulmonary artery, the differences in background noise values and SNR between TNC images and VNC images were statistically significant ( P<0.05). Compared with CIart images, the CT values of chest wall fat were lower in Vart images ( P<0.05), and the CT values of the remaining sites were significantly higher ( P<0.05); the background noise values of all sites on Vart images were smaller than those on CIart images, and the SNR and CNR values were higher than those on CIart images ( P<0.05).The differences of subjective scores of images quality were not statistically significant between TNC and VNC images, between CIar and Vart images ( P>0.05). Taking TNC as the standard, the overall detection rate of VNC for calcification was 88.53% (301/340). Except for the short diameter of partially solid nodules, the differences of qualitative and quantitative assessment indexes of lung nodules between TNC and VNC images were not statistically significant ( P>0.05). Conclusions:Spectral CT chest venous phase 40 keV VMI can simulate arterial phase images in the diagnosis of vascular lesions, and venous phase VNC basically meets the standard of conventional plain scan, so it is feasible to replace plain scan, arterial phase and venous phase images in a certain range.
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Objective:To investigate the optimal monoenergetic level of virtual monoenergetic images (VMI) in transplanted renal artery on a dual-layer spectral detector CT.Methods:A retrospective study was performed on 16 renal transplant patients who underwent transplanted renal angiography on a dual-layer spectral detector CT in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from June 2020 to April 2021. Conventional 120 kVp polyenergetic images (PI) were reconstructed, and virtual monoenergetic images (VMIs) in range of 40-200 keV with interval of 10 keV were reconstructed, too. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 120 kVp PI and VMIs were measured. Meanwhile, the subjective scores of the display of transplanted renal artery were performed on volume rendering images of 120 kVp PI and VMIs. Spearman correlation analysis was used to explore the correlation between energy levels and SNR or CNR. Rank sum tests were performed to compare the parameters of image quality between the VMI which had the highest SNR and CNR, and the other VMIs, or 120 kVp PI.Results:Among the VMIs, SNR or CNR was negatively correlated with energy levels ( r =-0.86 and -0.88, all P<0.001). The SNR [22.80(18.57, 34.16)] and CNR [35.38(25.97, 39.01)] of 40 keV VMI were the highest, and significantly higher than that of 120 kVp PI and 50-200 keV VMIs, all the differences were statistically significant (all P<0.05). The subjective scores of 40 keV VMI and 120 kVp PI were 5 (5, 5) and 4 (3, 5), respectively. The score of 40 keV VMI was significantly higher than that of 120 kVp PI ( Z=-2.60, P=0.009). There were no significant differences in subjective scores between 40 keV VMI and 50-70 keV VMIs ( Z=-1.00, -1.41, -1.73, P=0.317, 0.157, 0.083), but the subjective score of 40 keV VMI was higher than that of 80-200 keV VMIs and the differences were statistically significant (all P<0.05). Conclusions:As for the images of transplanted renal angiography on a dual-layer spectral detector CT, the image quality of 40 keV VMI was best, thus 40 keV was the optimal monoenergetic level.
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OBJECTIVE: To compare quantitative and qualitative image quality parameters in pediatric abdominopelvic dual-energy CT (DECT) using noise-optimized virtual monoenergetic image (VMI) and conventional VMI at different kiloelectron volt (keV) levels. MATERIALS AND METHODS: Thirty-six consecutive abdominopelvic DECT scans were retrospectively included. Noise-optimized VMI and conventional VMI were reconstructed at seven energy levels, from 40 keV to 100 keV at 10 keV intervals. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the liver, pancreas, and aorta were objectively measured and compared. Image quality was evaluated subjectively regarding image noise, image blurring of solid organ, bowel image quality and severity of beam-hardening artifacts. Optimal monoenergetic levels in keV for both algorithms were determined based on overall image quality score. RESULTS: The maximal CNR and SNR values for all investigated organs were observed at 40 keV in noise-optimized VMI (CNR and SNR of liver, pancreas, aorta in order [CNR; 20.93, 17.34, 46.75: SNR; 37.39, 33.80, 63.21]), at 60–70 keV and at 70 keV in conventional VMI (CNR; 8.12, 5.67, 15.97: SNR; 19.57, 16.66, 26.65). In qualitative image analysis, noise-optimized VMI and conventional VMI showed the best overall image quality scores at 60 keV and at 70 keV, respectively. Noise-optimized VMI at 60 keV showed superior CNRs, SNRs, and overall image quality scores compared to conventional VMI at 70 keV (p < 0.001). CONCLUSION: Optimal energy levels for noise-optimized VMI and conventional VMI were 60 keV and at 70 keV, respectively. Noise-optimized VMI shows superior CNRs, SNRs and subjective image quality over conventional VMI, at the optimal energy level.
Subject(s)
Aorta , Artifacts , Liver , Noise , Pancreas , Retrospective Studies , Signal-To-Noise RatioABSTRACT
OBJECTIVE: To evaluate the accuracy of emphysema volume (EV) and airway measurements (AMs) produced by various iterative reconstruction (IR) algorithms and virtual monoenergetic images (VME) at both low- and standard-dose settings. MATERIALS AND METHODS: Computed tomography (CT) images were obtained on phantom at both low- (30 mAs at 120 kVp) and standard-doses (100 mAs at 120 kVp). Each CT scan was reconstructed using filtered back projection, hybrid IR (iDose4; Philips Healthcare), model-based IR (IMR-R1, IMR-ST1, IMR-SP1; Philips Healthcare), and VME at 70 keV (VME70). The EV of each air column and wall area percentage (WA%) of each airway tube were measured in all algorithms. Absolute percentage measurement errors of EV (APEvol) and AM (APEWA%) were then calculated. RESULTS: Emphysema volume was most accurately measured in IMR-R1 (APEvol in low-dose, 0.053 ± 0.002; APEvol in standard-dose, 0.047 ± 0.003; all p 0.05). VME70 showed a significantly higher APEvol than iDose4, IMR-R1, and IMR-ST1 (all p < 0.004). VME70 also showed a significantly higher APEWA% compared with the other algorithms (all p < 0.001). CONCLUSION: IMR was the most accurate technique for measurement of both EV and airway wall thickness. However, VME70 did not show a significantly better accuracy compared with other algorithms.