Diagnostic study on clinical feasibility of an AI-based diagnostic system as a second reader on mobile CT images: a preliminary result.

Background: Artificial intelligence (AI) has breathed new life into the lung nodules detection and diagnosis. However, whether the output information from AI will translate into benefits for clinical workflow or patient outcomes in a real-world setting remains unknown. This study was to demonstrate the feasibility of an AI-based diagnostic system deployed as a second reader in imaging interpretation for patients screened for pulmonary abnormalities in a clinical setting. Methods: The study included patients from a lung cancer screening program conducted in Sichuan Province, China using a mobile computed tomography (CT) scanner which traveled to medium-size cities between July 10th, 2020 and September 10th, 2020. Cases that were suspected to have malignant nodules by junior radiologists, senior radiologists or AI were labeled a high risk (HR) tag as HR-junior, HR-senior and HR-AI, respectively, and included into final analysis. The diagnosis efficacy of the AI was evaluated by calculating negative predictive value and positive predictive value when referring to the senior readers' final results as the gold standard. Besides, characteristics of the lesions were compared among cases with different HR labels. Results: In total, 251/3,872 patients (6.48%, male/female: 91/160, median age, 66 years) with HR lung nodules were included. The AI algorithm achieved a negative predictive value of 88.2% [95% confidence interval (CI): 62.2-98.0%] and a positive predictive value of 55.6% (95% CI: 49.0-62.0%). The diagnostic duration was significantly reduced when AI was used as a second reader (223±145.6 vs. 270±143.17 s, P<0.001). The information yielded by AI affected the radiologist's decision-making in 35/145 cases. Lesions of HR cases had a higher volume [309.9 (214.9-732.5) vs. 141.3 (79.3-380.8) mm3, P<0.001], lower average CT number [-511.0 (-576.5 to -100.5) vs. -191.5 (-487.3 to 22.5), P=0.010], and pure ground glass opacity rather than solid. Conclusions: The AI algorithm had high negative predictive value but low positive predictive value in diagnosing HR lung lesions in a clinical setting. Deploying AI as a second reader could help avoid missed diagnoses, reduce diagnostic duration, and strengthen diagnostic confidence for radiologists.

[Clinical Application of "Three-Low" Technique Combined with Artificial Intelligence Iterative Reconstruction Algorithm in Aortic CT Angiography].

Objective: To explore the application value of the "three-low" technique (low radiation dose, low contrast agent dosage and low contrast agent flow rate) combined with artificial intelligence iterative reconstruction (AIIR) in aortic CT angiography (CTA). Methods: A total of 33 patients who underwent aortic CTA were prospectively enrolled. Based on the time of their follow-up examinations, the imaging data were divided into Group A and Group B, with Group A being the control group (100 kV, 0.8 mL/kg, 5 mL/s) and Group B being the "three-low" technique group (70 kV, 0.5 mL/kg, 3 mL/s). In group A, the images were reconstructed by Karl iterative algorithm. Group B was divided into B1 and B2 subgroups, with their images being reconstructed by Karl iterative algorithm and AIIR, respectively. The CT and SD values of the ascending aorta, descending aorta, abdominal aorta, left common iliac artery and right common iliac artery were measured, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The subjective scoring of image quality was performed. The radiation dose parameters were documented. Results: Differences in the CT value, SD value, SNR and CNR of the three groups were statistically significant ( P<0.001). The CT value, SNR and CNR of group B2 were significantly higher than those of group B1, while the SD value of group B2 was significantly lower than that of group B1 ( P<0.017). There was no significant difference between the CT values of group A and those of group B2 ( P>0.017). The SD values, SNR and CNR in group B2 were better than those in group A ( P>0.017). There was significant difference in the subjective evaluation of image quality among the three groups ( P<0.05), but there was no significant difference between group A and group B2 ( P>0.017). The radiation dose and contrast medium dosage in group B decreased 84.14% and 37.08%, respectively, compared with those of group A. Conclusion: With the "three-low" technique combined with AIIR algorithm, the image quality of aortic CTA obtained is comparable to that of conventional dose scanning, while the radiation dose, contrast agent dosage and contrast agent flow rate of patients are significantly reduced.

[Altitudinal patterns of species richness and species range size of vascular plants in Xiaolong- shan Reserve of Qinling Mountain: a test of Rapoport' s rule].

Altitudinal patterns of species richness and species range size and their underlying mechanisms have long been a key topic in biogeography and biodiversity research. Rapoport's rule stated that the species richness gradually declined with the increasing altitude, while the species ranges became larger. Using altitude-distribution database from Xiaolongshan Reverse, this study explored the altitudinal patterns of vascular plant species richness and species range in Qinling Xiaolongshan Reserve, and examined the relationships between species richness and their distributional middle points in altitudinal bands for different fauna, taxonomic units and growth forms and tested the Rapoport's rule by using Stevens' method, Pagel's method, mid-point method and cross-species method. The results showed that the species richness of vascular plants except small-range species showed a unimodal pattern along the altitude in Qinling Xiaolongshan Reserve and the highest proportion of small-range species was found at the lower altitudinal bands and at the higher altitudinal bands. Due to different assemblages and examining methods, the relationships between species distributing range sizes and the altitudes were different. Increasing taxonomic units was easier to support Rapoport's rule, which was related to niche differences that the different taxonomic units occupied. The mean species range size of angiosperms showed a unimodal pattern along the altitude, while those of the gymnosperms and pteridophytes were unclearly regular. The mean species range size of the climbers was wider with the increasing altitude, while that of the shrubs which could adapt to different environmental situations was not sensitive to the change of altitude. Pagel's method was easier to support the Rapoport's rule, and then was Steven's method. On the contrary, due to the mid-domain effect, the results of the test by using the mid-point method showed that the mean species range size varied in a unimodal pattern along the altitude, which didn't support the Rapoport's rule, and because of the scatter-spot impact, the explanatory power of the cross-species method was much lower.

[The value of split-bolus 2-phase with virtual non-enhanced scan in CT urography].

OBJECTIVE: To investigate the value of split-bolus 2-phase with virtual non-enhanced scan in CT urography. METHODS: Eighty (80) patients with urinary obstruction were divided into two groups, group A was traditional CT urography scan, group B was split-bolus 2-phase with virtual non-enhanced scan. The scan sequence of group A included conventional scan first, then enhanced scan in arterial phase, parenchyma phase and excretion delayed phase after the injection of 100 mL contrast agent. The scan sequence of group B included conventional scan and enhanced scan following two bolus injection of contrast; the first injection of contrast was 40 mL, the second injection was 60 mL with 15-30 minutes delay, then enhanced scan was conducted in arterial and parenchymal phase, the parenchymal phase scan was performed with dual energy scanning sequence. The image quality of urinary collecting system, the detection of urinary obstructive lesion, and radiation dose were compared between the two groups. RESULTS: Between the two imaging methods, the imaging quality of urinary system did not show significant difference, but radiation dose was statistically significant difference. The radiation dose of split-bolus 2-phase with virtual non-enhanced scan was only 55% of traditional CTU scan. CONCLUSION: Split-bolus2 phase with virtual non-enhanced scan could obtain the same image quality as tranditional CTU, while reducing the approximately half the radiation dose.