Long-term tissue coverage of a biodegradable polylactide polymer-coated biolimus-eluting stent: comparative sequential assessment with optical coherence tomography until complete resorption of the polymer

Biolimus-eluting stents (BESs) with a biodegradable polymer in abluminal coating achieve more complete coverage at 9 months compared with sirolimus-eluting stents (SESs) with a durable polymer, as assessed by optical coherence tomography (OCT). Whether this advantage persists or augments after complete resorption of the polymer (>12 months) is unknown.

Serial analysis of the malapposed and uncovered struts of the new generation of everolimus-eluting bioresorbable scaffold with optical coherence tomography

The aim of this study is to assess the serial changes in strut apposition and coverage of the bioresorbable vascular scaffolds (BVS) and to relate this with the presence of intraluminal masses at 6 months with optical coherence tomography (OCT).

Delayed coverage in malapposed and side-branch struts with respect to well-apposed struts in drug-eluting stents: in vivo assessment with optical coherence tomography

Background—Pathology studies on fatal cases of very late stent thrombosis have described incomplete neointimal coverage as common substrate, in some cases appearing at side-branch struts. Intravascular ultrasound studies have described the association between incomplete stent apposition (ISA) and stent thrombosis, but the mechanism explaining this association remains unclear. Whether the neointimal coverage of nonapposed side-branch and ISA struts is delayed with respect to well-apposed struts is unknown. Methods and Results—Optical coherence tomography studies from 178 stents implanted in 99 patients from 2 randomized trials were analyzed at 9 to 13 months of follow-up. The sample included 38 sirolimus-eluting, 33 biolimus-eluting, 57 everolimus-eluting, and 50 zotarolimus-eluting stents. Optical coherence tomography coverage of nonapposed side-branch and ISA struts was compared with well-apposed struts of the same stent by statistical pooled analysis with a random-effects model. A total of 34 120 struts were analyzed. The risk ratio of delayed coverage was 9.00 (95% confidence interval, 6.58 to 12.32) for nonapposed side-branch versus well-apposed struts, 9.10 (95% confidence interval, 7.34 to 11.28) for ISA versus well-apposed struts, and 1.73 (95% confidence interval, 1.34 to 2.23) for ISA versus nonapposed side-branch struts. Heterogeneity of the effect was observed in the comparison of ISA versus well-apposed struts (H=1.27; I2=38.40) but not in the other comparisons. Conclusions—Coverage of ISA and nonapposed side-branch struts is delayed with respect to well-apposed struts in drug-eluting stents, as assessed by optical coherence tomography.

Vascular tissue reaction to acute malapposition in human coronary arteries: sequential assessment with optical coherence tomography

The vascular tissue reaction to acute incomplete stent apposition (ISA) is not well known. The aim of this study was to characterize the vascular response to acute ISA in vivo and to look for predictors of incomplete healing.

Optical projection tomography reveals dynamics of HEV growth after immunization with protein plus CFA and features shared with HEVs in acute autoinflammatory lymphadenopathy

The vascular-stromal compartment of lymph nodes is important for lymph node function, and high endothelial venules (HEVs) play a critical role in controlling the entry of recirculating lymphocytes. In autoimmune and autoinflammatory diseases, lymph node swelling is often accompanied by apparent HEV expansion and, potentially, targeting HEV expansion could be used therapeutically to limit autoimmunity. In previous studies using mostly flow cytometry analysis, we defined three differentially regulated phases of lymph node vascular-stromal growth: initiation, expansion, and the re-establishment of vascular quiescence and stabilization. In this study, we use optical projection tomography to better understand the morphologic aspects of HEV growth upon immunization with ovalbumin/CFA (OVA/CFA). We find HEV elongation as well as modest arborization during the initiation phase, increased arborization during the expansion phase, and, finally, vessel narrowing during the re-establishment of vascular quiescence and stabilization. We also examine acutely enlarged autoinflammatory lymph nodes induced by regulatory T cell depletion and show that HEVs are expanded and morphologically similar to the expanded HEVs in OVA/CFA-stimulated lymph nodes. These results reinforce the idea of differentially regulated, distinct phases of vascular-stromal growth after immunization and suggest that insights gained from studying immunization-induced lymph node vascular growth may help to understand how the lymph node vascular-stromal compartment could be therapeutically targeted in autoimmune and autoinflammatory diseases.

3D documentation of footwear impressions and tyre tracks in snow with high resolution optical surface scanning

The three-dimensional documentation of footwear and tyre impressions in snow offers an opportunity to capture additional fine detail for the identification as present photographs. For this approach, up to now, different casting methods have been used. Casting of footwear impressions in snow has always been a difficult assignment. This work demonstrates that for the three-dimensional documentation of impressions in snow the non-destructive method of 3D optical surface scanning is suitable. The new method delivers more detailed results of higher accuracy than the conventional casting techniques. The results of this easy to use and mobile 3D optical surface scanner were very satisfactory in different meteorological and snow conditions. The method is also suitable for impressions in soil, sand or other materials. In addition to the side by side comparison, the automatic comparison of the 3D models and the computation of deviations and accuracy of the data simplify the examination and delivers objective and secure results. The results can be visualized efficiently. Data exchange between investigating authorities at a national or an international level can be achieved easily with electronic data carriers.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.