Background: High-resolution, low-noise detectors with minimal dead-space at chest-wall could improve posterior coverage and microcalcification visibility in dedicated cone-beam breast CT (CBBCT). However, their smaller field-of-view necessitates laterally-shifted detector geometry to enable optimizing the air-gap for x-ray scatter rejection. Objective: To evaluate laterally-shifted detector geometry for CBBCT with clinical projection datasets that provide for anatomical structures and lesions. Methods: CBBCT projection datasets (n=17 breasts) acquired with a 40x30-cm detector (1024x768-pixels, 0.388-mm pixels) were truncated along the fan-angle to emulate 20.3x30-cm, 22.2x30-cm and 24.1x30-cm detector formats and correspond to 20, 120, 220-pixels overlap in conjugate views, respectively. Feldkamp-Davis-Kress (FDK) algorithm with three different weighting schemes were used for reconstruction. Visual analysis for artifacts and quantitative analysis of root-mean-squared-error (RMSE), absolute difference between truncated and 40x30cm reconstructions (Diff), and its power spectrum (PS Diff) were performed. Results: Artifacts were observed for 20.3x30-cm, but not for other formats. The 24.1x30-cm provided the best quantitative results with RMSE and Diff (both in units of μ, cm-1) of 4.39x10-3 ±1.98x10-3 and 4.95x10-4 ±1.34x10-4 , respectively. The PS Diff (>0.3 cycles/mm) was in the order of 10-14 μ 2 mm 3 and was spatial-frequency independent. Conclusions: Laterally-shifted detector CBBCT with at least 220-pixels overlap in conjugate views (24.1x30-cm detector format), provides quantitatively accurate and artifact-free reconstruction.
The Northeastern United States experienced some of its coldest and snowiest conditions ever recorded during the winter of 2014-2015. The snowfall and extreme temperatures created significant challenges for local health departments attempting to continue critical services and respond to storm-related needs of the community. This report from the field aims to describe the impact of the severe weather on local health departments' operations, to examine the disruption to public health services, and to document public health support provided to vulnerable populations during the 2014-2015 winter season. Our findings show that the severe weather exposed major challenges in continuity of public health operations across health departments of various sizes and highlighted some key issues as well as effective strategies, such as collaborations with community-based organizations, to identify and address the needs of the most vulnerable during the winter storms. (Disaster Med Public Health Preparedness. 2018;page 1 of 3).
In this paper, using Defrise Phantoms, we present our investigations of the axial limitations of an analytical cone-beam reconstruction algorithm (FDK), and the iterative ordered-subset transmission reconstruction (OSTR) iterative algorithm, for an axially extended version of the Philips Brightview XCT cone beam CT (CBCT) geometry. Simulations were preformed for head size and body size Defrise Phantoms of different axial dimensions to investigate limitations on axial extent as a function of these. OSTR yielded overall better axial performance than FDK. It may be possible to reconstruct a larger axial extent for brain studies; however, patients with larger body sizes pose more of a problem.
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