Detection of Endoleaks Following Thoracic and Abdominal Aortic Endovascular Aortic Repair—: A Comparison of Standard and Dynamic 4D-Computed Tomography Angiography

Purpose: Endoleaks are a common complication after endovascular aortic repair (EVAR) and thoracic endovascular aortic repair (TEVAR). The detection and correct classification of endoleaks is essential for the further treatment of affected patients. However, standard computed tomography angiography (CTA) provides no hemodynamic information on endoleaks, which can result in misclassification in complex cases. The aim of this study was to compare standard CTA (sCTA) with dynamic, dual-energy CTA (dCTA) for detection and classification of endoleaks following EVAR or TEVAR. Materials and Methods: This retrospective evaluation compared 69 sCTA diagnostic examinations performed on 50 different patients with 89 dCTA diagnostic examinations performed on 69 different patients. Results: In total, 15.9% of sCTA examinations and 49.4% of dCTA examinations led to the detection of endoleaks. With sCTA, 20.0% of patients were diagnosed with endoleaks, while with dCTA, 37.7% of patients were diagnosed with endoleaks. With sCTA, mainly Type 1 endoleaks were detected, whereas, with dCTA, the types of detected endoleaks were more evenly distributed. In comparison with the literature, the frequencies of endoleak types detected with dCTA better reflect the natural distribution than the frequencies detected with standard CTA. Conclusion: Based on the retrospective comparative evaluation, dCTA could pose a valuable supplementary diagnostic tool resulting in a more accurate and realistic detection and classification of suspected endoleaks

PMAS: The Potsdam Multi Aperture Spectrophotometer. II. The Wide Integral Field Unit PPak

PPak is a new fiber-based Integral Field Unit (IFU), developed at the Astrophysical Institute Potsdam, implemented as a module into the existing PMAS spectrograph. The purpose of PPak is to provide both an extended field-of-view with a large light collecting power for each spatial element, as well as an adequate spectral resolution. The PPak system consists of a fiber bundle with 331 object, 36 sky and 15 calibration fibers. The object and sky fibers collect the light from the focal plane behind a focal reducer lens. The object fibers of PPak, each 2.7 arcseconds in diameter, provide a contiguous hexagonal field-of-view of 74 times 64 arcseconds on the sky, with a filling factor of 60%. The operational wavelength range is from 400 to 900nm. The PPak-IFU, together with the PMAS spectrograph, are intended for the study of extended, low surface brightness objects, offering an optimization of total light-collecting power and spectral resolution. This paper describes the instrument design, the assembly, integration and tests, the commissioning and operational procedures, and presents the measured performance at the telescope.Comment: 14 pages, 21 figures, accepted at PAS

Glycemic Control and Alveolar Bone Loss Progression in Type 2 Diabetes

This study tested the hypothesis that the risk for alveolar bone loss is greater, and bone loss progression more severe, for subjects with poorly controlled (PC) type 2 diabetes mellitus (type 2 DM) compared to those without type 2 DM or with better controlled (BC) type 2 DM. The PC group had glycosylated hemoglobin (HbA1) ≥ 9%; the BC group had HbA1 < 9%. Data from the longitudinal study of the oral health of residents of the Gila River Indian Community were analyzed. Of the 359 subjects, aged 15 to 57 with less than 25% radiographic bone loss at baseline, 338 did not have type 2 DM, 14 were BC, and 7 were PC. Panoramic radiographs were used to assess interproximal bone level. Bone scores (scale 0–4) corresponding to bone loss of 0%, 1% to 24%, 25% to 49%, 50% to 74%, or ≥ 75% were used to identify the worst bone score (WBS) in the dentition. Change in worst bone score at follow‐up, the outcome, was specified on a 4‐category ordinal scale as no change, or a 1‐, 2‐, 3‐, or 4‐category increase over baseline WBS (WBS1). Poorly controlled diabetes, age, calculus, time to follow‐up examination, and WBS1 were statistically significant explanatory variables in ordinal logistic regression models. Poorly controlled type 2 DM was positively associated with greater risk for a change in bone score (compared to subjects without type 2 DM) when the covariates were included in the model. The cumulative odds ratio (COR) at each threshold of the ordered response was 11.4 (95% CI = 2.5, 53.3). When contrasted with subjects with BC type 2 DM, the COR for those in the PC group was 5.3 (95% CI = 0.8, 53.3). The COR for subjects with BC type 2 DM was 2.2 (95% CI = 0.7, 6.5), when contrasted to those without type 2 DM. These results suggest that poorer glycemic control leads to both an increased risk for alveolar bone loss and more severe progression over those without type 2 DM, and that there may be a gradient, with the risk for bone loss progression for those with better controlled type 2 DM intermediate to the other 2 groups. Ann Periodontol 1998;3:30–39.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142262/1/aape0030.pd

Hyper-Local Weather Predictions with the Enhanced General Urban Area Microclimate Predictions Tool

This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. For the further development and demonstration of GUMP, the Embry–Riddle Aeronautical University (ERAU) campus was used as a test environment. Local weather sensors provided data to train ML models, and CFD models of urban- and suburban-like areas of ERAU’s campus were created and iterated through with a wide assortment of inlet wind speed and direction combinations. ML weather sensor predictions were combined with best-fit CFD models from a database of CFD flow fields, providing flight operational areas with a fully expressed wind flow field. This field defined a risk map for uncrewed aircraft operators based on flight plans and individual flight performance metrics. The potential applications of GUMP are significant due to the immediate availability of weather predictions and its ability to easily extend to arbitrary urban and suburban locations

Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy

The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or classifying mitotic figures (MFs). Recent progress in the field of artificial intelligence has allowed the development of high-performance algorithms that may improve standardization of the MC. As algorithmic predictions are not flawless, computer-assisted review by pathologists may ensure reliability. In the present study, we compared partial (MC-ROI preselection) and full (additional visualization of MF candidates and display of algorithmic confidence values) computer-assisted MC analysis to the routine (unaided) MC analysis by 23 pathologists for whole-slide images of 50 canine cutaneous mast cell tumors (ccMCTs). Algorithmic predictions aimed to assist pathologists in detecting mitotic hotspot locations, reducing omission of MFs, and improving classification against imposters. The interobserver consistency for the MC significantly increased with computer assistance (interobserver correlation coefficient, ICC = 0.92) compared to the unaided approach (ICC = 0.70). Classification into prognostic stratifications had a higher accuracy with computer assistance. The algorithmically preselected hotspot MC-ROIs had a consistently higher MCs than the manually selected MC-ROIs. Compared to a ground truth (developed with immunohistochemistry for phosphohistone H3), pathologist performance in detecting individual MF was augmented when using computer assistance (F1-score of 0.68 increased to 0.79) with a reduction in false negatives by 38%. The results of this study demonstrate that computer assistance may lead to more reproducible and accurate MCs in ccMCTs

Non‐Insulin Dependent Diabetes Mellitus and Alveolar Bone Loss Progression Over 2 Years

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141702/1/jper0076.pd

Broadband acoustic invisibility and illusions

Rendering objects invisible to impinging acoustic waves (cloaking) and creating acoustic illusions (holography) has been attempted using active and passive approaches. While most passive methods are inflexible and applicable only to narrow frequency bands, active approaches attempt to respond dynamically, interfering with broadband incident or scattered wavefields by emitting secondary waves. Without prior knowledge of the primary wavefield, the signals for the secondary sources need to be estimated and adapted in real time. This has thus far impeded active cloaking and holography for broadband wavefields. We present experimental results of active acoustic cloaking and holography without prior knowledge of the wavefield so that objects remain invisible and illusions intact even for broadband moving sources. This opens previously inaccessible research directions and facilitates practical applications including architectural acoustics, education, and stealth

High-Redshift Quasars Found in Sloan Digital Sky Survey Commissioning Data IV: Luminosity Function from the Fall Equatorial Stripe Sampl

This is the fourth paper in a series aimed at finding high-redshift quasars from five-color imaging data taken along the Celestial Equator by the SDSS. during its commissioning phase. In this paper, we use the color-selected sample of 39 luminous high-redshift quasars presented in Paper III to derive the evolution of the quasar luminosity function over the range of 3.6<z<5.0, and -27.5<M_1450<-25.5 (Omega=1, H_0=50 km s^-1 Mpc^-1). We use the selection function derived in Paper III to correct for sample incompleteness. The luminosity function is estimated using three different methods: (1) the 1/V_a estimator; (2) a maximum likelihood solution, assuming that the density of quasars depends exponentially on redshift and as a power law in luminosity and (3) Lynden-Bell's non-parametric C^- estimator. All three methods give consistent results. The luminous quasar density decreases by a factor of ~ 6 from z=3.5 to z=5.0, consistent with the decline seen from several previous optical surveys at z<4.5. The luminosity function follows psi(L) ~ L^{-2.5} for z~4 at the bright end, significantly flatter than the bright end luminosity function psi(L) \propto L^{-3.5} found in previous studies for z<3, suggesting that the shape of the quasar luminosity function evolves with redshift as well, and that the quasar evolution from z=2 to 5 cannot be described as pure luminosity evolution. Possible selection biases and the effect of dust extinction on the redshift evolution of the quasar density are also discussed.Comment: AJ accepted, with minor change