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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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Accurate calculation of structured singular value is the key to robust stability analysis and control synthesis of a feedback system. The most commonly used tool in practice is the MATLAB Robust Control Toolbox where some upper and lower bounds of the structured singular value are calculated. Unfortunately, because of the discontinuities of the structured singular value with pure real perturbations, there is usually a large gap between the upper and the lower bounds obtained using this MATLAB toolbox when the system is subject to real parametric uncertainties. Motivated from the exact stability radius formula for unstructured real perturbations, we propose a modification of the real stability radius formula so that it can be applied to computing the stability radius with real block structured perturbations. Numerical simulations show that the proposed method can provide useful bounds when there are nontrivial real block structured uncertainties.