In patients without significant angiographic coronary artery disease, the result of stress MPS is a predictor of long-term prognosis. Quantitative analysis of MPS allows definition of patients with a higher likelihood to develop clinical events or symptoms.

In Punctuated Equilibrium Theory (PET), information processing under the constraints of limited attention and bounded rationality leads to stick-slip dynamics in policy outcomes. Empirical work in this field often focuses on the macro level. Using the case of nuclear energy policy in the United States as proof of concept, we demonstrate how decisive budget changes in a specific policy subsystem can be linked to attention of Congress and the president. We utilize a mixed-methods data-mining approach: Maximum likelihood estimation is used to analyze the distribution of the nuclear energy RD&D budget. Then attention data of both Congress and the president are structured by means of cluster analysis and principal component analysis. Finally, these data are used in a generalized linear model to predict specific budget shifts. The article is designed as a proof of concept: In the case of nuclear energy policy, we are able to predict budget shifts without violating the assumptions of PET. More importantly: we can demonstrate that attention is not only affecting the final policy outcome but also the corridor of the possible.

Gated myocardial perfusion SPECT allows calculation of enddiastolic and end-systolic volumes (EDV and ESV, respectively) and left ventricular ejection fraction (LVEF). The quantification algorithms QGS (quantitative gated SPECT), 4D-MSPECT, and CARE heart show a good correlation with cardiac MRI. Nevertheless, differences in contour finding suggest algorithm-specific effects if heart axes vary. The effect of tilting heart axes on gated SPECT was quantified as a possible source of error. Methods: Sixty men underwent gated SPECT (450 MBq of 99m Tc-tetrofosmin or sestamibi, 8 gates/cycle). After correct reorientation (R 0 ), datasets were tilted by 5°, 10°, 15°, 20°, 30°, and 45°along both long axes (R 5 , R 10 , R 15 , R 20 , R 30 , and R 45 , respectively). EDV, ESV, and LVEF were calculated using QGS, 4D-MSPECT, and CARE heart. Because a 15°tilt could be a maximum possible misreorientation in routine, R 0 and R 15 results were analyzed in detail. Absolute-difference values between results of tilted and correctly reoriented datasets were calculated for all tilts and algorithms. Results: QGS and CARE heart succeeded for R 0 and R 15 in all cases, whereas 4D-MSPECT failed to find the basal plane in 1 case (patient B). R 2 values between paired R 15 /R 0 results were 0.992 (QGS), 0.796 (4D-MSPECT; R 2 5 0.919 in n 5 59 after exclusion of the failed case), and 0.916 (CARE heart) for EDV; 0.994 (QGS), 0.852 (4D-MSPECT; R 2 5 0.906 in n 5 59), and 0.899 (CARE heart) for ESV; and 0.988 (QGS), 0.814 (4D-MSPECT; R 2 5 0.810 in n 5 59), and 0.746 (CARE heart) for LVEF. Concerning all levels of misreorientation, 1 patient was excluded for all algorithms because of multiple problems in contour finding; additionally for 4D-MSPECT patient B was excluded. In the 45°g roup, QGS succeeded in 58 of 59 cases, 4D-MSPECT in 58 of 58, and CARE heart in 33 of 59. Mean absolute differences for EDV ranged from 5.1 6 4.1 to 12.8 6 10.5 mL for QGS, from 6.7 6 6.3 to 34.2 6 20.7 mL for 4D-MSPECT, and from 5.4 6 5.6 to 25.2 6 16.1 mL for CARE heart (tilts between 5°and 45°). Mean absolute differences for ESV ranged from 4.1 6 3.7 to 8.0 6 9.4 mL for QGS, from 5.6 6 8.0 to 10.0 6 10.5 mL for 4D-MSPECT, and from 5.4 6 5.6 to 25.5 6 16.1 mL for CARE heart. Mean absolute differences for LVEF ranged from 1.1% 6 1.0% to 2.2% 6 1.8% for QGS, from 4.0% 6 3.5% to 8.0% 6 7.1% for 4D-MSPECT, and from 3.4% 6 2.9% to 9.2% 6 6.0% for CARE heart. Conclusion: Despite tilted heart axes, QGS showed stable results even when using tilts up to 45°. 4D-MSPECT and CARE heart results varied with reorientation of the heart axis, implying that published validation results apply to correctly reoriented data only.

End-diastolic volume, ESV and LVEF calculated from gated SPECT using EXINI agree with cMRI over a wide range of values. Correlation between both the methods was good for EDV and ESV, and acceptable for LVEF. No relevant influence of image quality or SRS on the accuracy of EXINI results was found.

Considerable differences between SSS/SRS obtained with QPS and 4D-MSPECT were found when using M-NDB. Even using identical patients and identical I-NDB, the algorithms still gave substantial different results.