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Objective:To assess the agreement of manual measurement, semi-automatic measurement based on computer-aided diagnosis (CAD), and automatic measurement based on artificial intelligence (AI) in measuring diameters and volumes of solid pulmonary nodules.Methods:The clinical and low dose CT (LDCT) data of 165 participants in lung cancer screening of Sichuan Cancer Hospital from July 2018 to April 2020 were retrospectively analyzed. The largest nodule of each participant was selected to analyze, and its diameter and volume were measured by one junior and one senior radiologist using manual measurement, semi-automatic measurement based on CAD, and automatic measurement based on AI. Referring to Lung CT imaging reporting and data system (Lung-RADS, version 1.1), all nodules were classified into Lung-RADS 2, 3, 4A, 4B, 4X categories and low and high risk groups according to the diameter and volume measured by different measurement methods. Repeated-measures analysis of variance and paired t-test were used to compare the differences in the diameter and volume of lung nodules measured by different methods. The consistency of the three methods in measuring nodule diameter and volume was assessed by the correlation coefficient (ICC). Linear weighted Kappa coefficient was applied to assess the consistency of different measurement methods in Lung-RADS classification results; simple Kappa coefficient was applied to assess the consistency of different methods in high and low risk grouping results. Results:Difference in the diameters of pulmonary nodules measured by manual measurement, semi-automatic measurement based on CAD, and automatic measurement based on AI was statistically significant [(14.9±6.3) mm, (17.0±6.7) mm, (15.0±5.7) mm, F=88.39, P<0.001], and the pairwise comparisons showed that there was significant difference between semi-automatic measurement based on CAD and manual measurement method ( t=10.97, P<0.001), semi-automatic measurement based on CAD and automatic measurement based on AI ( t=10.07, P<0.001), but no significant difference between manual measurement method and automatic measurement based on AI method ( t=1.04, P=0.301). There was no significant difference in the measurement of pulmonary nodule volumes between the semi-automatic measurement and the automatic measurement method based on AI ( Z=0.70, P=0.482). The consistency of pulmonary nodules diameter measured by different measurement methods was high (ICC>0.75), and the consistency of semi-automatic and automatic measurement of lung nodule volume was high (ICC=0.927). The consistency of three methods for lung-RADS classification and high-and low-risk grouping according to nodule diameter was good (Kappa>0.80). The agreements between the semi-automatic measurement and the automatic measurement method for Lung-RADS classification and high-and low-risk grouping according to nodule volume were good (Kappa>0.80). Conclusion:In terms of diameter measurement of solid pulmonary nodules, automatic measurement based on AI is more consistent with manual measurement than semi-automatic measurement based on CAD. The agreement between automatic measurement and semi-automatic measurement is high in terms of volume measurement.
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Objective To explore the influence of iterative algorithm on image quality in ultralow-dose CT scan of lung.Methods The thoracic model was scanned using different parameter combinations.The tube voltage was chose with 80,100 kV in ultra-low dose group and the mAs was selected by 10,15,20,25 and 30 mAs.The control group selected the parameters of 120 kV,30 mAs.All the images were reconstructed with filtered back projection (FBP group) and iterative algorithm (IR group).The image noise and effective dose (E) were compared.Results When tube current and voltage were constant,the image noise of IR group was lower than that of FBP group,and the difference was statistically significant (t =1.102-8.070,P＜0.05).When the tube current was constant,the image noise of the 80 kV with FBP group was higher than that of 100 kV with FBP group,and the image noise of the 80 kV with IR group was lower than the 100 kV with FBP group(t =-8.639-7.841,P＜0.05).Compared with the conventional low-dose with FBP group,the image noise of each ultra-low-dose with FBP group was significantly increased,and the image noise of (80 kV,10 mAs),(80 kV,15 mAs),(80 kV,20 mAs) with IR group was significantly increased,and the image noise of (100 kV,15 mAs),(100 kV,20 mAs),(100 kV,25 mAs),(100 kV,30 mAs) with IR group was significantly reduced (t=-8.140-23.028,P＜0.05).There was no significant difference in image noise between the groups of (80 kV,25 mAs),(80 kV,30 mAs),(100 kV,10 mAs) with IR and the group of conventional low dose with FBP (P＞0.05).Compared with the conventional low dose group,the E of the groups of (80 kV,25 mAs),(80kV,30mAs),(100kV,10 mAs),(100kV,15mAs),(100kV,20mAs),(100kV,25 mAs),(100 kV,30 mAs) was decreased by 75.9％,71.0％,79.8％,70.4％,60.3％,50.2％,40.0％,respectively.Conclusions The image quality of the ultra-low dose protocol (100 kV,10mAs) with iterative algorithm is similar to that of the conventional low dose with FBP group,and the radiation dose could be significantly reduced.
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Objective To investigate the effect of CareDose 4D combined with Care kV on CT pulmonary ground glass nodule ( GGN) with respect to quality and radiation dose. Methods The thoracic model containing 6 GGN was performed by using 7 low-dose schemes. The CareDose 4D + Care kV was adopted in scheme 1. In schemes 2, 3 and 4, the tube voltage was 120 kV, and the tube current 30, 20 and 10 mAs respectively. In schemes 5, 6 and 7, the tube voltage was 100 kV, and the tube current was 30, 20 and 10 mAs, respectively. The image quality [ CT value, contrast noise ratio ( CNR) , noise value (SD) and subjective score] and effective dose (E) were compared. Results There was no statistically significant difference in CT value of GGN among different schemes (P>0. 05). The SD of scheme 1 was higher than those of schemes 2, 3 and 5, but lower than those f scheme 7, while the CNR of scheme 1 was lower than those of schemes 2, 3 and 5, but higher than that of scheme 7 ( t=13. 020, 9. 560, 8. 120,-5. 720, -7. 849, -5. 192, -4. 130, 1. 361,P<0. 05). SD and CNR of scheme 1 were not significantly different from those of scheme 4 and 6 ( P>0. 05) . The subjective scores of each GGN of schemes 1, 2, 3, 5 and 6 was over 3 points, but and the subjective scores of one GGN of each of schemes 4 and 7 were below 3 points. The value E of the scheme 1 was reduced by 63. 0％, 44. 4％, 38. 8％, and 9. 1％, compared with the schemes 2, 3, 5 and 6, respectively. Conclusions CareDose 4D combined with Care kV in low-dose lung CT scan can ensure the image quality of GGN and reduce the radiation dose effectively.
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Objective To explore application of automatic tube current modulation combined with iterative reconstruction in CT scanning ( non-enhanced and enhanced) of neck. Methods A total of 80 patients with CT scanning of neck were randomly divided into test group(n=40, automatic tube current modulation, iterative reconstruction ) and control group ( n = 40, 200 mAs, filtered-back-projection reconstruction ) . Subjective scores and objective evaluation of two groups were evaluated. Evaluation included image noise ( SD ) of thyroid gland, trapezius muscle, sternocleidomastoid muscle, submandibular gland, lateral pterygoid muscle and brain tissue. Effective dose ( E ) was compared. Results The E of non-enhanced and enhanced scanning in test group was lower than that of control group with the statistically significant difference(t = -2. 451, -2. 451, P <0. 05). The subjective scores of non-enhanced and enhanced scanning in test group were higher than those of control group with the statistically significant difference (Z = - 1.969, - 2.056, P < 0.05), while SD of thyroid gland, trapezius muscle, sternocleidomastoid muscle, submandibular gland in test group were lower than that of control group with the statistically significant difference ( t =2. 400,2. 516,2. 120,2. 411,4. 134,4. 674, 2. 711,2. 892, P<0. 05). There were no significant differences in SD of lateral pterygoid muscle, brain tissue of non-enhanced and enhanced scanning between two groups (P>0. 05). Conclusions Automatic tube current modulation combined with iterative reconstruction in CT scanning of neck could improve image quality, and reduce effectively radiation dose.
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Objective To explore the correlation between extratemporal hypometabolism on preoperative 18F-FDG PET imaging and the outcome after temporal lobectomy in temporal lobe epilepsy (TLE)patients.Methods A total of 96 patients with intractable TLE who underwent temporal lobectomy were recruited.The outcome was evaluated according to International League Against Epilepsy (ILAE) 2001 outcome classification (OC) criteria:OC 1-3 was considered as good outcome and OC4-6 as poor outcome.The follow-up period was more than 2 years.The 18F-FDG PET brain images were retrospectively analyzed.The preoperative extratemporal cortical hypometabolism and extratemporal subcortical hypometabolism occurred in basal ganglia and thalamus were taken as independent exposure factors of poor outcome and the odds ratios (OR) were calculated respectively.Results Thirteen of 96 cases had poor outcome.Extratemporal cortical hypometabolism was found in 12 of 83(14.5％) cases with good outcome and in 11 of 13 cases with poor outcome.Extratemporal subcortical hypometabolism was found in 25 of 83 (30.1％) cases with good outcome and in 10 of 13 cases with poor outcome.The occurrence of extratemporal hypometabolism was significantly higher in poor outcome group than that in good surgical outcome group (cortical:x2 =26.63 ;subcortical:x2 =8.70; both P＜0.05).The OR of extratemporal cortical hypometabolism was 32.54,with 95％ CI of 6.40-165.44,and that of extratemporal subcortical hypometabolism was 7.73,with 95％ CI of 1.96-30.52.Conclusion Extratemporal cortical hypometabolism and subcortical hypometabolism in TLE patients are associated with poor outcome of temporal lobectomy in TLE patients.