Test beam measurement of the first prototype of the fast silicon pixel monolithic detector for the TT-PET project

The TT-PET collaboration is developing a PET scanner for small animals with 30 ps time-of-flight resolution and sub-millimetre 3D detection granularity. The sensitive element of the scanner is a monolithic silicon pixel detector based on state-of-the-art SiGe BiCMOS technology. The first ASIC prototype for the TT-PET was produced and tested in the laboratory and with minimum ionizing particles. The electronics exhibit an equivalent noise charge below 600 e- RMS and a pulse rise time of less than 2 ns, in accordance with the simulations. The pixels with a capacitance of 0.8 pF were measured to have a detection efficiency greater than 99% and, although in the absence of the post-processing, a time resolution of approximately 200 ps

The statistical importance of a study for a network meta-analysis estimate.

BACKGROUND In pairwise meta-analysis, the contribution of each study to the pooled estimate is given by its weight, which is based on the inverse variance of the estimate from that study. For network meta-analysis (NMA), the contribution of direct (and indirect) evidence is easily obtained from the diagonal elements of a hat matrix. It is, however, not fully clear how to generalize this to the percentage contribution of each study to a NMA estimate. METHODS We define the importance of each study for a NMA estimate by the reduction of the estimate's variance when adding the given study to the others. An equivalent interpretation is the relative loss in precision when the study is left out. Importances are values between 0 and 1. An importance of 1 means that the study is an essential link of the pathway in the network connecting one of the treatments with another. RESULTS Importances can be defined for two-stage and one-stage NMA. These numbers in general do not add to one and thus cannot be interpreted as 'percentage contributions'. After briefly discussing other available approaches, we question whether it is possible to obtain unique percentage contributions for NMA. CONCLUSIONS Importances generalize the concept of weights in pairwise meta-analysis in a natural way. Moreover, they are uniquely defined, easily calculated, and have an intuitive interpretation. We give some real examples for illustration

Structural and magnetic properties of [\lbrackErTb]\rbrackmultilayers

Abstract.: We have investigated the structural and magnetic properties of $\lbrack$ Er|Tb $\rbrack$ multilayers by different scattering methods. Diffuse X-ray scattering under grazing incidence reveals the interface structure in $\lbrack$ Er|Tb $\rbrack$ bilayers and trilayers, indicating vertically correlated roughness between the Er and Tb interfaces. The magnetic properties of $\lbrack$ ErnEr|TbnTb $\rbrack$ superlattices have been studied as a function of the superlattice composition (indices denote the number of atomic layers). Coupled ferromagnetic structures exist in all investigated samples. The phase transition temperature varies with the Tb layer thickness. Modulated magnetic order is short range for all samples beside the $\lbrack$ Er20|Tb5 $\rbrack$ superlattice, the sample with the smallest Tb layer thickness. We observe dipolar antiferromagnetic coupling between single ferromagnetic Tb layers in all samples, with the onset of this ordering depending on the Tb layer thickness. Due to competing interactions, exchange coupling is limited to the interface near region. Therefore long range modulated magnetic order is observed in the $\lbrack$ Er20|Tb5 $\rbrack$ superlattice only, where the interface regions overlap. The distinct differences to the magnetic structure of an Er0.8Tb0.2 alloy film are explained by a highly anisotropic arrangement of neighbouring atoms due to the correlated roughnes

Prevalence of evidence of inconsistency and its association with network structural characteristics in 201 published networks of interventions

BACKGROUND: Network meta-analysis (NMA) has attracted growing interest in evidence-based medicine. Consistency between different sources of evidence is fundamental to the reliability of the NMA results. The purpose of the present study was to estimate the prevalence of evidence of inconsistency and describe its association with different NMA characteristics. METHODS: We updated our collection of NMAs with articles published up to July 2018. We included networks with randomised clinical trials, at least four treatment nodes, at least one closed loop, a dichotomous primary outcome, and available arm-level data. We assessed consistency using the design-by-treatment interaction (DBT) model and testing all the inconsistency parameters globally through the Wald-type chi-squared test statistic. We estimated the prevalence of evidence of inconsistency and its association with different network characteristics (e.g., number of studies, interventions, intervention comparisons, loops). We evaluated the influence of the network characteristics on the DBT p-value via a multivariable regression analysis and the estimated Pearson correlation coefficients. We also evaluated heterogeneity in NMA (consistency) and DBT (inconsistency) random-effects models. RESULTS: We included 201 published NMAs. The p-value of the design-by-treatment interaction (DBT) model was lower than 0.05 in 14% of the networks and lower than 0.10 in 20% of the networks. Networks including many studies and comparing few interventions were more likely to have small DBT p-values (less than 0.10), which is probably because they yielded more precise estimates and power to detect differences between designs was higher. In the presence of inconsistency (DBT p-value lower than 0.10), the consistency model displayed higher heterogeneity than the DBT model. CONCLUSIONS: Our findings show that inconsistency was more frequent than what would be expected by chance, suggesting that researchers should devote more resources to exploring how to mitigate inconsistency. The results of this study highlight the need to develop strategies to detect inconsistency (because of the relatively high prevalence of evidence of inconsistency in published networks), and particularly in cases where the existing tests have low power

Predictive Value of \u3csup\u3e18\u3c/sup\u3eF-Florbetapir and \u3csup\u3e18\u3c/sup\u3eF-FDG PET for Conversion from Mild Cognitive Impairment to Alzheimer Dementia

© 2020 by the Society of Nuclear Medicine and Molecular Imaging. The present study examined the predictive values of amyloid PET, 18F-FDG PET, and nonimaging predictors (alone and in combination) for development of Alzheimer dementia (AD) in a large population of patients with mild cognitive impairment (MCI). Methods: The study included 319 patients with MCI from the Alzheimer Disease Neuroimaging Initiative database. In a derivation dataset (n = 159), the following Cox proportional-hazards models were constructed, each adjusted for age and sex: amyloid PET using 18F-florbetapir (pattern expression score of an amyloid-β AD conversion-related pattern, constructed by principle-components analysis); 18F-FDG PET (pattern expression score of a previously defined 18F-FDG-based AD conversion-related pattern, constructed by principle-components analysis); nonimaging (functional activities questionnaire, apolipoprotein E, and mini-mental state examination score); 18F-FDG PET + amyloid PET; amyloid PET + nonimaging; 18F-FDG PET + nonimaging; and amyloid PET + 18F-FDG PET + nonimaging. In a second step, the results of Cox regressions were applied to a validation dataset (n = 160) to stratify subjects according to the predicted conversion risk. Results: On the basis of the independent validation dataset, the 18F-FDG PET model yielded a significantly higher predictive value than the amyloid PET model. However, both were inferior to the nonimaging model and were significantly improved by the addition of nonimaging variables. The best prediction accuracy was reached by combining 18F-FDG PET, amyloid PET, and nonimaging variables. The combined model yielded 5-y free-of-conversion rates of 100%, 64%, and 24% for the low-, medium- and high-risk groups, respectively. Conclusion:18F-FDG PET, amyloid PET, and nonimaging variables represent complementary predictors of conversion from MCI to AD. Especially in combination, they enable an accurate stratification of patients according to their conversion risks, which is of great interest for patient care and clinical trials

On composite likelihood in bivariate meta-analysis of diagnostic test accuracy studies

The composite likelihood (CL) is amongst the computational methods used for estimation of the generalized linear mixed model (GLMM) in the context of bivariate meta-analysis of diagnostic test accuracy studies. Its advantage is that the likelihood can be derived conveniently under the assumption of independence between the random effects, but there has not been a clear analysis of the merit or necessity of this method. For synthesis of diagnostic test accuracy studies, a copula mixed model has been proposed in the biostatistics literature. This general model includes the GLMM as a special case and can also allow for flexible dependence modelling, different from assuming simple linear correlation structures, normality and tail independence in the joint tails. A maximum likelihood (ML) method, which is based on evaluating the bi-dimensional integrals of the likelihood with quadrature methods has been proposed, and in fact it eases any computational difficulty that might be caused by the double integral in the likelihood function. Both methods are thoroughly examined with extensive simulations and illustrated with data of a published meta-analysis. It is shown that the ML method has non-convergence issues or computational difficulties and at the same time allows estimation of the dependence between study-specific sensitivity and specificity and thus prediction via summary receiver operating curves

A monolithic ASIC demonstrator for the Thin Time-of-Flight PET scanner

Time-of-flight measurement is an important advancement in PET scanners to improve image reconstruction with a lower delivered radiation dose. This article describes the monolithic ASIC for the TT-PET project, a novel idea for a high-precision PET scanner for small animals. The chip uses a SiGe Bi-CMOS process for timing measurements, integrating a fully-depleted pixel matrix with a low-power BJT-based front-end per channel, integrated on the same 100 µm thick die. The target timing resolution of the scanner is 30 ps RMS for electrons from the conversion of 511 keV photons. The system will include 1.6 million channels across almost 2000 different chips. A full-featured demonstrator chip with a 3×10 matrix of 500×500 µm2 pixels was fabricated to validate each block. Its design and experimental results are presented here. © 2019 CERN