ObjectivesTo evaluate the clinical value of noise-based tube current reduction method with iterative reconstruction for obtaining consistent image quality with dose optimization in prospective electrocardiogram (ECG)-triggered coronary CT angiography (CCTA).Materials and MethodsWe performed a prospective randomized study evaluating 338 patients undergoing CCTA with prospective ECG-triggering. Patients were randomly assigned to fixed tube current with filtered back projection (Group 1, n = 113), noise-based tube current with filtered back projection (Group 2, n = 109) or with iterative reconstruction (Group 3, n = 116). Tube voltage was fixed at 120 kV. Qualitative image quality was rated on a 5-point scale (1 = impaired, to 5 = excellent, with 3–5 defined as diagnostic). Image noise and signal intensity were measured; signal-to-noise ratio was calculated; radiation dose parameters were recorded. Statistical analyses included one-way analysis of variance, chi-square test, Kruskal-Wallis test and multivariable linear regression.ResultsImage noise was maintained at the target value of 35HU with small interquartile range for Group 2 (35.00–35.03HU) and Group 3 (34.99–35.02HU), while from 28.73 to 37.87HU for Group 1. All images in the three groups were acceptable for diagnosis. A relative 20% and 51% reduction in effective dose for Group 2 (2.9 mSv) and Group 3 (1.8 mSv) were achieved compared with Group 1 (3.7 mSv). After adjustment for scan characteristics, iterative reconstruction was associated with 26% reduction in effective dose.ConclusionNoise-based tube current reduction method with iterative reconstruction maintains image noise precisely at the desired level and achieves consistent image quality. Meanwhile, effective dose can be reduced by more than 50%.

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Purpose: To investigate the characteristics of cervicocephalic spotty calcium (SC) and coronary atherosclerosis in patients with acute ischemic stroke (AIS) and to assess the predictive value of SC for coronary atherosclerosis using combined coronary and cervicocephalic CTA.Materials and Methods: Patients with AIS (n = 70) confirmed by brain MRI or CT and patients with asymptomatic carotid atherosclerosis (n = 58) confirmed by carotid ultrasonography were enrolled in our study. Subjects in both groups underwent combined coronary and cervicocephalic CTA. SC was used to evaluate cervicocephalic atherosclerosis. Coronary artery stenosis (CAS) ≥ 50% by segment and coronary artery calcium score (CACS) were used to evaluate coronary atherosclerosis. The SC frequency and the difference in coronary atherosclerosis between the two groups were compared, and the correlation between SC and coronary atherosclerosis was analyzed. Independent factors for CAS ≥ 50% were assessed via logistic regression analysis. Receiver operating characteristic curve analysis was performed to evaluate the added value of SC for predicting CAS ≥ 50%.Results: Both SC and the CACS were significantly higher in the Stroke group than in the Control group (total SC count: 6.83 ± 4.34 vs. 2.98 ± 2.87, P < 0.05; CACS: 477.04 ± 798.01 vs. 136.31 ± 205.65, P < 0.05). There were significant differences in the presence of CAS ≥ 50% (61.4 vs. 27.6%, P < 0.001). SC and coronary atherosclerosis were significantly correlated for both the CACS and CAS ≥ 50% (r = 0.746 and 0.715, respectively; P < 0.001). SC was an independent predictor for CAS ≥ 50%.Conclusion: SC correlates significantly with the CACS and could serve as an independent predictor of CAS ≥ 50% in patients with AIS, which suggests that combined cerebrovascular and cardiovascular assessments are of importance for such patients.

Background: Multimodal CT imaging can evaluate cerebral hemodynamics and stroke etiology, playing an important role in predicting prognosis. This study aimed to summarize the comprehensive image characteristics of wake-up stroke (WUS), and to explore its value in prognostication.Methods: WUS patients with anterior circulation large vessel occlusion were recruited into this prospective study. According to the 90-day modified Rankin Scale (mRS), all patients were divided into good outcome (mRS 0–2) or bad (mRS 3–6). Baseline clinical information, multimodal CT imaging characteristics including NECT ASPECTS, clot burden score (CBS), collateral score, volume of penumbra and ischemic core on perfusion were compared. Multivariate logistic regression analysis was further used to analyze predictive factors for good prognosis. Area under curve (AUC) was calculated from the receiver operating characteristic (ROC) curve to assess prognostic value.Results: Forty WUS were analyzed in this study, with 20 (50%) achieving good outcome. Upon univariable analysis, the good outcome group demonstrated higher ASPECTS, higher CBS, higher rate of good collateral filling and lower penumbra volume when compared with the poor outcome group. Upon logistic regression analysis, poor outcome significantly correlated with penumbra volume (OR: 1.023, 95% CI = 1.003–1.043) and collateral score (OR: 0.140, 95% CI = 0.030–0.664). AUC was 0.715 for penumbra volume (95% CI, 0.550–0.846) and 0.825 for good collaterals (95% CI, 0.672–0.927) in predicting outcome.Conclusions:Penumbra volume and collateral score are the most relevant baseline imaging characters in predicting outcome of WUS patients. These imaging characteristics might be instructive to treatment selection. As the small sample size of current study, further studies with larger sample size are needed to confirm these observations.

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