Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

Initiation and limitation of Ly-49A NK cell receptor acquisition by T cell factor-1.

The establishment of clonally variable expression of MHC class I-specific receptors by NK cells is not well understood. The Ly-49A receptor is used by approximately 20% of NK cells, whereby most cells express either the maternal or paternal allele and few express simultaneously both alleles. We have previously shown that NK cells expressing Ly-49A were reduced or almost absent in mice harboring a single or no functional allele of the transcription factor T cell factor-1 (TCF-1), respectively. In this study, we show that enforced expression of TCF-1 in transgenic mice yields an expanded Ly-49A subset. Even though the frequencies of Ly-49A(+) NK cells varied as a function of the TCF-1 dosage, the relative abundance of mono- and biallelic Ly-49A cells was maintained. Mono- and biallelic Ly-49A NK cells were also observed in mice expressing exclusively a transgenic TCF-1, i.e., expressing a fixed amount of TCF-1 in all NK cells. These findings suggest that Ly-49A acquisition is a stochastic event due to limiting TCF-1 availability, rather than the consequence of clonally variable expression of the endogenous TCF-1 locus. Efficient Ly-49A acquisition depended on the expression of a TCF-1 isoform, which included a domain known to associate with the TCF-1 coactivator beta-catenin. Indeed, the proximal Ly-49A promoter was beta-catenin responsive in reporter gene assays. We thus propose that Ly-49A receptor expression is induced from a single allele in occasional NK cells due to a limitation in the amount of a transcription factor complex requiring TCF-1.

Phosphorus acquisition and internal utilization efficiency in tropical maize genotypes

The objective of this work was to determine the relative importance of phosphorus acquisition efficiency (PAE - plant P uptake per soil available P), and phosphorus internal utilization efficiency (PUTIL - grain yield per P uptake) in the P use efficiency (PUE - grain yield per soil available P), on 28 tropical maize genotypes evaluated at three low P and two high P environments. PAE was almost two times more important than PUTIL to explain the variability observed in PUE, at low P environments, and three times more important at high P environments. These results indicate that maize breeding programs, to increase PUE in these environments, should use selection index with higher weights for PAE than for PUTIL. The correlation between these two traits showed no significance at low or at high P environments, which indicates that selection in one of these traits would not affect the other. The main component of PUTIL was P quotient of utilization (grain yield per grain P) and not the P harvest index (grain P per P uptake). Selection to reduce grain P concentration should increase the quotient of utilization and consequently increase PUTIL.

Effect of data acquisition accuracy on timing of stand harvests and expected net present value

Abstract

Gadolinium-enhanced pulmonary magnetic resonance angiography in the diagnosis of acute pulmonary embolism: a prospective study on 48 patients.

OBJECTIVE: Gadolinium-enhanced pulmonary magnetic resonance angiography (MRA) can be an option in patients with a history of previous adverse reaction to iodinated contrast material and renal insufficiency. Radiation is also avoided. The aim of this study is to prospectively compare the diagnostic value of MRA with that of a diagnostic strategy, taking into account catheter angiography, computed tomography angiography (CTA), and lung scintigraphy [ventilation-perfusion (VQ)]. MATERIAL AND METHODS: Magnetic resonance angiography was done in 48 patients with clinically suspected pulmonary embolism (PE) using fast gradient echo coronal acquisition with gadolinium. Interpretation was done with native coronal images and multiplanar maximum intensity projection reconstructions. Results were compared to catheter angiography (n=15), CTA (n=34), VQ (n=45), as well as 6-12 months clinical follow-ups, according to a sequenced reference tree. RESULTS: The final diagnosis of PE was retained in 11 patients (23%). There were two false negatives and no false positive results with MRA. Computed tomography angiography resulted in no false negatives or false positives. Magnetic resonance angiography had a sensitivity of 82% and a specificity of 100%. CONCLUSION: In our study, pulmonary MRA had a sensitivity of 82% and a specificity of 100% for the diagnosis of PE, with slightly less sensitivity than CTA. In the diagnostic algorithm of PE, pulmonary MRA should be considered as an alternative to CTA when iodine contrast injection or radiation is a significant matter.

Study of OSEM with different subsets in grating-based X-ray differential phase-contrast imaging.

Impressive developments in X-ray imaging are associated with X-ray phase contrast computed tomography based on grating interferometry, a technique that provides increased contrast compared with conventional absorption-based imaging. A new "single-step" method capable of separating phase information from other contributions has been recently proposed. This approach not only simplifies data-acquisition procedures, but, compared with the existing phase step approach, significantly reduces the dose delivered to a sample. However, the image reconstruction procedure is more demanding than for traditional methods and new algorithms have to be developed to take advantage of the "single-step" method. In the work discussed in this paper, a fast iterative image reconstruction method named OSEM (ordered subsets expectation maximization) was applied to experimental data to evaluate its performance and range of applicability. The OSEM algorithm with different subsets was also characterized by comparison of reconstruction image quality and convergence speed. Computer simulations and experimental results confirm the reliability of this new algorithm for phase-contrast computed tomography applications. Compared with the traditional filtered back projection algorithm, in particular in the presence of a noisy acquisition, it furnishes better images at a higher spatial resolution and with lower noise. We emphasize that the method is highly compatible with future X-ray phase contrast imaging clinical applications.

Towards a diffusion image processing validation and accuracy prediction framework

Validation is the main bottleneck preventing theadoption of many medical image processing algorithms inthe clinical practice. In the classical approach,a-posteriori analysis is performed based on someobjective metrics. In this work, a different approachbased on Petri Nets (PN) is proposed. The basic ideaconsists in predicting the accuracy that will result froma given processing based on the characterization of thesources of inaccuracy of the system. Here we propose aproof of concept in the scenario of a diffusion imaginganalysis pipeline. A PN is built after the detection ofthe possible sources of inaccuracy. By integrating thefirst qualitative insights based on the PN withquantitative measures, it is possible to optimize the PNitself, to predict the inaccuracy of the system in adifferent setting. Results show that the proposed modelprovides a good prediction performance and suggests theoptimal processing approach.

Multi-source composite kernels for urban image classification

This letter presents advanced classification methods for very high resolution images. Efficient multisource information, both spectral and spatial, is exploited through the use of composite kernels in support vector machines. Weighted summations of kernels accounting for separate sources of spectral and spatial information are analyzed and compared to classical approaches such as pure spectral classification or stacked approaches using all the features in a single vector. Model selection problems are addressed, as well as the importance of the different kernels in the weighted summation.

Groupe thérapeutique de gestion des émotions: un territoire d'acquisition des compétences chez les patients avec trouble de la personnalité borderline

Dans cet article, nous présenterons le modèle biopsychosocial du trouble de ln personnalité borderline et le mettrons en lien avec les critères développés dans les manuels diagnostiques (DSM-IV-TR, CIM-10). Seront ensuite e:rplicité les principaux cadres de prise en charge de la thérapie comportementale- dialectique (TCD), tels que conçus par Marsha M. Linehan. Le modèle des dimensions de l'ouverture émotionnelle permettra d'enrichir la conceptualisation des émotions de la TCD. Nous insisterons particulièrement sur le groupe thérapeutique de Gestion des Émotions, inspiré des principes constitutifs de la TCD. Les premiers résultats d'une étude pilote et la présentation d'une étude randomisée contrôlée seront discutés, en tenant compte des exigences cliniques et des considérations méthodologiques de l'évaluation des psychothérapies.