Automated estimation of image quality for coronary computed tomographic angiography using machine learning.

OBJECTIVES: Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA). METHODS: The machine learning method was trained using 75 CCTA studies by mapping features (noise, contrast, misregistration scores, and un-interpretability index) to an IQ score based on manual ground truth data. The automated method was validated on a set of 50 CCTA studies and subsequently tested on a new set of 172 CCTA studies against visual IQ scores on a 5-point Likert scale. RESULTS: The area under the curve in the validation set was 0.96. In the 172 CCTA studies, our method yielded a Cohen's kappa statistic for the agreement between automated and visual IQ assessment of 0.67 (p < 0.01). In the group where good to excellent (n = 163), fair (n = 6), and poor visual IQ scores (n = 3) were graded, 155, 5, and 2 of the patients received an automated IQ score > 50 %, respectively. CONCLUSION: Fully automated assessment of the IQ of CCTA data sets by machine learning was reproducible and provided similar results compared with visual analysis within the limits of inter-operator variability. KEY POINTS: • The proposed method enables automated and reproducible image quality assessment. • Machine learning and visual assessments yielded comparable estimates of image quality. • Automated assessment potentially allows for more standardised image quality. • Image quality assessment enables standardization of clinical trial results across different datasets.

Climate Change Mitigation, Air Pollution, and Environmental Justice in California.

Climate change mitigation policies can have significant co-benefits for air quality, including benefits to disadvantaged communities experiencing substantial air pollution. However, the effects of these mitigation policies have rarely been evaluated with respect to their influence on disadvantaged communities. Here we assess the air pollution and environmental justice implications of California's cap-and-trade mitigation program through analysis of (1) the sources of air pollution in disadvantaged communities, (2) emissions-reduction offset usage under the cap-and-trade program, and (3) the relationship between reductions in greenhouse gas emissions and reductions in co-pollutant emissions. Our analysis suggests that the cap-and-trade program has limited impacts, including limited disproportionate impacts, on air quality in disadvantaged communities. The sources of most air pollution in these communities have not been subject to the cap-and-trade program, and the use of emissions-reduction offsets is only marginally higher in disadvantaged communities than in other communities. Furthermore, reductions in greenhouse gas emissions imply smaller proportional reductions in co-pollutant emissions. While climate policies lead to important air quality co-benefits in some contexts, especially through reduced coal usage, targeted air quality policies and regulations may be more effective for reducing air pollution in disadvantaged communities in California and throughout the state.

Coronary Artery Calcium Progression Is Associated With Coronary Plaque Volume Progression: Results From a Quantitative Semiautomated Coronary Artery Plaque Analysis.

OBJECTIVES: The aim of this study was to determine whether coronary artery calcium (CAC) progression was associated with coronary plaque progression on coronary computed tomographic angiography. BACKGROUND: CAC progression and coronary plaque characteristics are associated with incident coronary heart disease. However, natural history of coronary atherosclerosis has not been well described to date, and the understanding of the association between CAC progression and coronary plaque subtypes such as noncalcified plaque progression remains unclear. METHODS: Consecutive patients who were referred to our clinic for evaluation and had serial coronary computed tomography angiography scans performed were included in the study. Coronary artery plaque (total, fibrous, fibrous-fatty, low-attenuation, densely calcified) volumes were calculated using semiautomated plaque analysis software. RESULTS: A total of 211 patients (61.3 ± 12.7 years of age, 75.4% men) were included in the analysis. The mean interval between baseline and follow-up scans was 3.3 ± 1.7 years. CAC progression was associated with a significant linear increase in all types of coronary plaque and no plaque progression was observed in subjects without CAC progression. In multivariate analysis, annualized and normalized total plaque (ß = 0.38; p < 0.001), noncalcified plaque (ß = 0.35; p = 0.001), fibrous plaque (ß = 0.56; p < 0.001), and calcified plaque (ß = 0.63; p = 0.001) volume progression, but not fibrous-fatty (ß = 0.03; p = 0.28) or low-attenuation plaque (ß = 0.11; p = 0.1) progression, were independently associated with CAC progression. Plaque progression did not differ between the sexes. A significantly increased total and calcified plaque progression was observed in statin users. CONCLUSIONS: In a clinical practice setting, progression of CAC was significantly associated with an increase in both calcified and noncalcified plaque volume, except fibrous-fatty and low-attenuation plaque. Serial CAC measurements may be helpful in determining the need for intensification of preventive treatment.