Objective To investigate the utility of dual-energy computed tomography(DECT)virtual non-contrast(VNC)images instead of true non-contrast(TNC)images in the quantitative analysis of emphysema.Methods A retrospective selection was con-ducted on 59 patients who underwent chest CT plain scan plus dual-phase enhanced scan on APEX-CT.VNC images of arterial phase(VNCart)and venous phase(VNCven)were generated on AW4.7 workstation.Volume CT dose index(CTDIvol)and dose length product(DLP)were recorded respectively.In a double-blind manner,two physicians graded the severity of each patient's emphysema according to the Fleischner Society's emphysema visual classification system.The"digital lung"detection and analysis platform was used to quantitatively measure emphysema at three thresholds(-950 HU,-930 HU and-910 HU),and the difference in meas-urement results between VNC images and TNC images was compared.Quantitative differences in low attenuation volume(LAV),percentage of low attenuation area(LAA%)and mean lung density(MLD)at the-950 HU threshold were compared using Bland-Altman plots.Results Using TNC images as the standard,there was no significant difference in the results of the visual classifica-tion evaluation of emphysema between TNC and VNC images(χ2=2.80,P=0.247).In quantitative measurement,there was no significant difference in total lung volume(TLV)(χ2=3.26,P=0.196)between the three groups images.Compared to TNC ima-ges,there were no statistically significant differences in LAV,LAA%and MLD of VNCven images at 15th percentile lung density(Perc 15%)and different thresholds(P>0.05).Compared to the TNC mode,the VNC mode could reduce the effective dose(ED)by approximately 32.6%.Conclusion The use of DECT VNCven images on chest has the potential to replace TNC for the quantitative analysis of emphysema,thereby streamlining scans and reducing radiation dose.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Objective To investigate the utility of dual-energy computed tomography(DECT)virtual non-contrast(VNC)images instead of true non-contrast(TNC)images in the quantitative analysis of emphysema.Methods A retrospective selection was con-ducted on 59 patients who underwent chest CT plain scan plus dual-phase enhanced scan on APEX-CT.VNC images of arterial phase(VNCart)and venous phase(VNCven)were generated on AW4.7 workstation.Volume CT dose index(CTDIvol)and dose length product(DLP)were recorded respectively.In a double-blind manner,two physicians graded the severity of each patient's emphysema according to the Fleischner Society's emphysema visual classification system.The"digital lung"detection and analysis platform was used to quantitatively measure emphysema at three thresholds(-950 HU,-930 HU and-910 HU),and the difference in meas-urement results between VNC images and TNC images was compared.Quantitative differences in low attenuation volume(LAV),percentage of low attenuation area(LAA%)and mean lung density(MLD)at the-950 HU threshold were compared using Bland-Altman plots.Results Using TNC images as the standard,there was no significant difference in the results of the visual classifica-tion evaluation of emphysema between TNC and VNC images(χ2=2.80,P=0.247).In quantitative measurement,there was no significant difference in total lung volume(TLV)(χ2=3.26,P=0.196)between the three groups images.Compared to TNC ima-ges,there were no statistically significant differences in LAV,LAA%and MLD of VNCven images at 15th percentile lung density(Perc 15%)and different thresholds(P>0.05).Compared to the TNC mode,the VNC mode could reduce the effective dose(ED)by approximately 32.6%.Conclusion The use of DECT VNCven images on chest has the potential to replace TNC for the quantitative analysis of emphysema,thereby streamlining scans and reducing radiation dose.

Objective To explore the value of deep learning image reconstruction(DLIR)algorithm to improve the quality of low keV monochromatic portal vein images of energy spectrum CT.Methods Fifty patients who underwent enhanced upper abdominal energy spectrum CT scan were selected.Mixed-model adaptive statistical iterative reconstruction-Veo(50%ASIR-V)algorithm and high-deep learning image reconstruction(DLIR-H)algorithm were used to obtain monochromatic images at 40-70 keV(with intervals of 10 keV).The CT and standard deviation(SD)values of the portal vein trunk,left and right branches,and erector spinae muscle were measured in the transverse position,and the signal-to-noise ratio(SNR)and portal vein contrast-to-noise ratio(CNR)were calculated for objective evaluation.The portal vein image quality between the two algorithms and different energy was subjectively scored by two physicians.Results In terms of objective evaluation:compared with 50%ASIR-V,the CNR and SNR of portal vein in monochromatic DLIR-H images at the same keV between 40-70 keV energy levels were increased while the SD value was decreased(P＜0.05),and the CT value was unchanged;there was no statistical difference in the magnitude of change in CNR between the two algorithms at different energy levels(P＞0.05);there was a statistically significant difference in the magnitude of change in SNR and SD value(P＜0.05)and the magnitude of change was the largest at 40 keV;comparison between different energy levels of DLIR-H,the CNR and SD value of 40 keV DLIR-H were the highest(P＜0.05),and there was no significant difference in the SNR(P＞0.05).In terms of subjective evaluation:there was no significant difference between the subjective scores of the two algorithms at the same keV from 40-70 keV(P＞0.05),and the two reconstruction algorithms at 40 keV and 50 keV had the highest subjective scores between different keV.Conclusion The DLIR algorithm can reduce the noise of low keV monochromatic images,improve the image quality of portal vein.

Objective To explore the effect of deep learning image reconstruction(DLIR)algorithm combined with"double low"[low voltage(kV)and low contrast agent dosage]technique on the image quality of coronary computed tomography angiography(CCTA)in overweight patients compared with adaptive statistical iterative reconstruction(ASIR-V)and filtered back projection(FBP).Methods Fifty-two patients with body mass index(BMI)between 25.1 kg/m2and 28 kg/m2 who underwent CCTA scanning were prospectively selected,all of whom scanned on a GE Revolution APEX-CT with a tube voltage of 80 kV,a smart mA(500-1 300 mA),a noise index of 30,and a contrast dosage of 0.5 mL/kg;four groups of images were reconstructed for each patient,FBP,50％ASIR-V,DLIR-M,and DLIR-H.The CT and SD values of the aorta(AO)root,the proximal segment of the right coronary artery(RCA),the left circumflex(LCX),the left anterior descending branch(LAD)and the pericardial fat were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.Two doctors experienced in the diagnosis of cardiovascular disease were selected to subjectively score the reconstructed images using a double-blind method.The SD value,SNR value,CNR value and subjective scores of images in the four groups were compared.Results In the objective image quality evaluation,there were statistically significant differences in SD value,SNR value and CNR value of reconstructed images in the four groups(P＜0.05).As the four groups of reconstruction algorithms FBP,50％ASIR-V,DLIR-M,and DLIR-H were changed sequentially,the image SD value gradually decreased,the SNR value and CNR value gradually increased,and the DLIR-H group had the lowest SD value and the highest SNR and CNR values.In the subjective image quality evaluation,the subjective scores of the two doctors had good consistency(Kappa value=0.900),and the difference between them was statistically significant(P＜0.001).The subjective scores of DLIR-M and DLIR-H groups were higher.Conclusion DLIR algorithm combined with"double-low"technique can significantly improve the CCTA image quality of overweight patients,which is better than 50％ASIR-V and FBP.

Objective To explore the clinical value of adaptive statistical iterative reconstruction(ASIR)combined with automatic tube current modulation in low dose scan of chest CT.Methods 80 patients who underwent chest CT scan were randomly divided into four groups,with a noise index(NI)of 14,16,18,and 20,respectively.Automatic tube current modulation technique for chest CT scan was adopted for all patients.The standard dose group,with a NI of 14,was reconstructed with FBP.While the low-dose groups,with a NI of 16,18 and 20,were reconstructed with four ASIR levels(20% ASIR,40% ASIR,60% ASIR and 80% ASIR) in each group.The volume CT dose index(CTDIvol),dose length product(DLP)and effective dose(ED)were recorded of the four groups.The signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated of the different reconstruction groups. Two radiologists with more than five years of work experience blindly scored the subjective image quality.Results Effective dose of the four groups with different NI were(3.29 ± 1.21)mSv,(3.10 ± 1.07)mSv,(2.20 ± 0.82)mSv and(1.97 ± 1.21)mSv,respectively. In all the reconstruction groups,when NI was constant,the greater the ASIR,the lower the SD.When ASIR percentage was constant, the SD was increased and the SNR was reduced along with NI rising up.When the parameters were set as NI 18 and ASIR 60%,the SD would be smaller and SNR would be higher than that of a standard dose group.In aspect of the scores from subjective image quality evaluation,there was no significant difference(P> 0.05).The average ED was decreased by about 33.2% when compared to the standard dose group.Conclusion Combining automatic tube current modulation with ASIR has a certain clinical practicality.When the NI is set at 18 and ASIR is 60%,the image quality can be optimal for not only satisfying the requirements of clinical diagnosis, but also reducing radiation dose in chest CT scanning.

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