[en] Objective: To investigate the image quality and diagnostic accuracy using 64-slice spiral computed tomography (64-CTA) scanner in patients with suspected coronary artery disease. Methods: Sixty eight patients with chest pain or post PTCA underwent CT coronary angiography (CTA) and selected coronary angiography (SCA). The SCA results were served as 'gold standard' to evaluate the diagnostic accuracy of CTA, while the sensitivity, positive predictive value (PPV) and negative predictive value (NPV) were calculated, respectively. Results: 64-slice spiral CT could clearly demonstrate the coronary arterial trunk and branchs with stenosis, calcifications abnormal orifise origination and bridge vascular disease; especially with high accuracy in revealing calcification and even with quantification. The sensitivity, specificity, PPV and NPV of the degree of stenosis more than 75% for coronary artery segments evaluated by CTA were significantly higher than those of the degree of stenosis less than 50% for coronary artery segments (P<0.01). Conclusion: CTA is a safe, simple and reliable noninvasive method for screening coronary artery disease in patients with chest pain. Moreover, 64-slice spiral CT could demonstrate not only the more delicate delineation of coronary arterial changes with 3D reconstruction and volume renderting but also the presence and quantity of calcium deposited on the vascular wall. (authors)

[en] Objective: To evaluate the diagnostic accuracy of coronary in-stent restenosis using 64- slice multislice computed tomography (MSCT) coronary angiography. Methods: Fifty nine patients after stent implantation with 112 coronary stents were examined with 64-section MSCT. Scanning was undertaken by electrocardiographically gated, but an automatic bolus-tracking method. For image reconstruction, an edgeenhancing kernel (B46f)was applied. All segments within stent were assessed by two observers in consensus, and were graded according to the following scheme: patient stent, in-stent intimal hyperplasia (lumen reduction <50%), in-stent restenosis ( =>50%). Consensus reading was compared with those of coronary angiography. Results: 109 stented lesions (97.3%) were classified as evaluable in MSCT. Overall, 10 of 12 in-stent restenosis were correctly detected by MSCT. Sensitivity, specificity, positive predictive value, and negative predictive value were 83.3%, 99%, 90.9%, and 97.3%, respectively. Conclusion: 64-MSCT has high diagnostic accuracy for detecting in-stent restenosis, indicating and suggesting as a useful tool for the follow up after coronary stenting. (authors)

[en] The formation of Cu film on Fe (001) surface by depositing Cu₁₃ clusters was investigated via the molecular dynamics simulation. The incident energy range of Cu₁₃ clusters was from 0.1 to 10.0 eV/atom, and the deposition rate was 1 clusters/ps. The temperature of substrate was 300, 700 and 1000 K, respectively. The effects of incident energy of cluster and substrate temperature on the growth mode, surface roughness, defects distribution and epitaxy degree of film were studied. The simulation results show that the incident energy of Cu₁₃ clusters plays a dominant role in the growth mode of film. In addition, when the incident energy of Cu₁₃ clusters is 7.5 eV/atom and the substrate temperature is 300 K, the Cu film formed on Fe (001) surface is smoother, few defects and better epitaxy degree. (authors)

[en] Laser heating provides an effective method to produce thermally reduced graphene oxide (rGO), it can also pattern the designed layout on the surface of graphene oxide (GO) during the reduction process. In this work, we demonstrated a flexible strain sensor based on the morphologically modulated laser-patterned reduced graphene oxide (LPG) film with a one-step process. Compared with the strain sensor using flat patterned rGO (0%–1.2%) and curved-grid patterned rGO (CGPG) (0%–4.1%), the strain sensor based on rectangular-grid patterned rGO (RGPG) have highest gauge factor (GF), up to 133 under 2.7% of physical deformation. Meanwhile, the RGPG strain sensors exhibit extraordinary linearity in a relatively large range of deformation (0%–2.7%) and excellent endurance for over 1000 stretching-releasing circles. The RGPG strain sensor was used to monitor human fatigue. By analyzing eye blinking frequency and duration, it is possible to evaluate the fatigue level. We anticipate that the RGPG based strain sensor, prepared via a relatively simple and cost-effective process, may open up a broad spectrum of practical applications, such as driver fatigue evaluation and smart monitoring of human body movements. (paper)