Particle exposure scenarios for research and production activities involving nanomaterials

Nanomaterials with structures in the nanoscale (1 to 100 nm) often have chemical, physical and bioactive characteristics different from those of larger entities of the same material. This is interesting for industry but raises questions about the health of exposed people. However, little is known so far about the exposure of workers to inhalable airborne nanomaterials. We investigated several activities in research laboratories and industry to learn about relevant exposure scenarios. Work process analyses were combined with measurements of airborne particle mass concentrations and number−size distributions. Background levels in research settings were mostly low, while in industrial production, levels were sometimes elevated, especially in halls near busy roads or in the presence of diesel fork lifts without particle filters. Peak levels were found in an industrial setting dealing with powders (up to 80,000 particles/cm³ and up to 15 mg/m³). Mostly low concentrations were found for activities involving liquid applications. However, centrifugation and lyophilization of nanoparticle containing solutions resulted in very high particle number concentrations (up to 300,000 particles/cm³), whereas no increases were seen for the same activities conducted with nanoparticle−free liquids. No significant increases of particle concentrations were found for processes involving nanoparticles bound to surfaces. Also no increases were observed in laboratories that were visualizing properties and structures of small amounts of nanomaterials. Conclusion: When studying exposure scenarios for airborne nanomaterials, the focus should not only be on processes involving nano−powders, but also on processes involving intensively treated nanoparticle−containing liquids. Acknowledgement: We thank Chantal Imhof, MSc and Guillaume Ferraris, MSc for their contributions.

Recent advances in remote sensing image processing

Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.

Model-based iterative reconstruction in pediatric chest CT: assessment of image quality in a prospective study of children with cystic fibrosis.

BACKGROUND: The potential effects of ionizing radiation are of particular concern in children. The model-based iterative reconstruction VEO(TM) is a technique commercialized to improve image quality and reduce noise compared with the filtered back-projection (FBP) method. OBJECTIVE: To evaluate the potential of VEO(TM) on diagnostic image quality and dose reduction in pediatric chest CT examinations. MATERIALS AND METHODS: Twenty children (mean 11.4 years) with cystic fibrosis underwent either a standard CT or a moderately reduced-dose CT plus a minimum-dose CT performed at 100 kVp. Reduced-dose CT examinations consisted of two consecutive acquisitions: one moderately reduced-dose CT with increased noise index (NI = 70) and one minimum-dose CT at CTDIvol 0.14 mGy. Standard CTs were reconstructed using the FBP method while low-dose CTs were reconstructed using FBP and VEO. Two senior radiologists evaluated diagnostic image quality independently by scoring anatomical structures using a four-point scale (1 = excellent, 2 = clear, 3 = diminished, 4 = non-diagnostic). Standard deviation (SD) and signal-to-noise ratio (SNR) were also computed. RESULTS: At moderately reduced doses, VEO images had significantly lower SD (P < 0.001) and higher SNR (P < 0.05) in comparison to filtered back-projection images. Further improvements were obtained at minimum-dose CT. The best diagnostic image quality was obtained with VEO at minimum-dose CT for the small structures (subpleural vessels and lung fissures) (P < 0.001). The potential for dose reduction was dependent on the diagnostic task because of the modification of the image texture produced by this reconstruction. CONCLUSIONS: At minimum-dose CT, VEO enables important dose reduction depending on the clinical indication and makes visible certain small structures that were not perceptible with filtered back-projection.

Automated identification of minimal myocardial motion for improved image quality on MR angiography at 3 T

OBJECTIVE: Imaging during a period of minimal myocardial motion is of paramount importance for coronary MR angiography (MRA). The objective of our study was to evaluate the utility of FREEZE, a custom-built automated tool for the identification of the period of minimal myocardial motion, in both a moving phantom at 1.5 T and 10 healthy adults (nine men, one woman; mean age, 24.9 years; age range, 21-32 years) at 3 T. CONCLUSION: Quantitative analysis of the moving phantom showed that dimension measurements approached those obtained in the static phantom when using FREEZE. In vitro, vessel sharpness, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were significantly improved when coronary MRA was performed during the software-prescribed period of minimal myocardial motion (p < 0.05). Consistent with these objective findings, image quality assessments by consensus review also improved significantly when using the automated prescription of the period of minimal myocardial motion. The use of FREEZE improves image quality of coronary MRA. Simultaneously, operator dependence can be minimized while the ease of use is improved.

3D coronary vessel wall imaging utilizing a local inversion technique with spiral image acquisition.

Current 2D black blood coronary vessel wall imaging suffers from a relatively limited coverage of the coronary artery tree. Hence, a 3D approach facilitating more extensive coverage would be desirable. The straightforward combination of a 3D-acquisition technique together with a dual inversion prepulse can decrease the effectiveness of the black blood preparation. To minimize artifacts from insufficiently suppressed blood signal of the nearby blood pools, and to reduce residual respiratory motion artifacts from the chest wall, a novel local inversion technique was implemented. The combination of a nonselective inversion prepulse with a 2D selective local inversion prepulse allowed for suppression of unwanted signal outside a user-defined region of interest. Among 10 subjects evaluated using a 3D-spiral readout, the local inversion pulse effectively suppressed signal from ventricular blood, myocardium, and chest wall tissue in all cases. The coronary vessel wall could be visualized within the entire imaging volume.