Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography.

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

Characterisation of anatomical properties of the human basal ganglia using magnetic resonance imaging

The detailed in-vivo characterization of subcortical brain structures is essential not only to understand the basic organizational principles of the healthy brain but also for the study of the involvement of the basal ganglia in brain disorders. The particular tissue properties of basal ganglia - most importantly their high iron content, strongly affect the contrast of magnetic resonance imaging (MRI) images, hampering the accurate automated assessment of these regions. This technical challenge explains the substantial controversy in the literature about the magnitude, directionality and neurobiological interpretation of basal ganglia structural changes estimated from MRI and computational anatomy techniques. My scientific project addresses the pertinent need for accurate automated delineation of basal ganglia using two complementary strategies: ? Empirical testing of the utility of novel imaging protocols to provide superior contrast in the basal ganglia and to quantify brain tissue properties; ? Improvement of the algorithms for the reliable automated detection of basal ganglia and thalamus Previous research demonstrated that MRI protocols based on magnetization transfer (MT) saturation maps provide optimal grey-white matter contrast in subcortical structures compared with the widely used Tl-weighted (Tlw) images (Helms et al., 2009). Under the assumption of a direct impact of brain tissue properties on MR contrast my first study addressed the question of the mechanisms underlying the regional specificities effect of the basal ganglia. I used established whole-brain voxel-based methods to test for grey matter volume differences between MT and Tlw imaging protocols with an emphasis on subcortical structures. I applied a regression model to explain the observed grey matter differences from the regionally specific impact of brain tissue properties on the MR contrast. The results of my first project prompted further methodological developments to create adequate priors for the basal ganglia and thalamus allowing optimal automated delineation of these structures in a probabilistic tissue classification framework. I established a standardized workflow for manual labelling of the basal ganglia, thalamus and cerebellar dentate to create new tissue probability maps from quantitative MR maps featuring optimal grey-white matter contrast in subcortical areas. The validation step of the new tissue priors included a comparison of the classification performance with the existing probability maps. In my third project I continued investigating the factors impacting automated brain tissue classification that result in interpretational shortcomings when using Tlw MRI data in the framework of computational anatomy. While the intensity in Tlw images is predominantly

Quantitative performance of a quadrupole-orbitrap-MS in targeted LC-MS determinations of small molecules.

High-resolution mass spectrometry (HRMS) has been associated with qualitative and research analysis and QQQ-MS with quantitative and routine analysis. This view is now challenged and for this reason, we have evaluated the quantitative LC-MS performance of a new high-resolution mass spectrometer (HRMS), a Q-orbitrap-MS, and compared the results obtained with a recent triple-quadrupole MS (QQQ-MS). High-resolution full-scan (HR-FS) and MS/MS acquisitions have been tested with real plasma extracts or pure standards. Limits of detection, dynamic range, mass accuracy and false positive or false negative detections have been determined or investigated with protease inhibitors, tyrosine kinase inhibitors, steroids and metanephrines. Our quantitative results show that today's available HRMS are reliable and sensitive quantitative instruments and comparable to QQQ-MS quantitative performance. Taking into account their versatility, user-friendliness and robustness, we believe that HRMS should be seen more and more as key instruments in quantitative LC-MS analyses. In this scenario, most targeted LC-HRMS analyses should be performed by HR-FS recording virtually "all" ions. In addition to absolute quantifications, HR-FS will allow the relative quantifications of hundreds of metabolites in plasma revealing individual's metabolome and exposome. This phenotyping of known metabolites should promote HRMS in clinical environment. A few other LC-HRMS analyses should be performed in single-ion-monitoring or MS/MS mode when increased sensitivity and/or detection selectivity will be necessary.