Comparing nonrigid registration techniques for motion corrected MR prostate diffusion imaging.

PURPOSE: T2-weighted magnetic resonance imaging (MRI) is commonly used for anatomical visualization in the pelvis area, such as the prostate, with high soft-tissue contrast. MRI can also provide functional information such as diffusion-weighted imaging (DWI) which depicts the molecular diffusion processes in biological tissues. The combination of anatomical and functional imaging techniques is widely used in oncology, e.g., for prostate cancer diagnosis and staging. However, acquisition-specific distortions as well as physiological motion lead to misalignments between T2 and DWI and consequently to a reduced diagnostic value. Image registration algorithms are commonly employed to correct for such misalignment. METHODS: The authors compare the performance of five state-of-the-art nonrigid image registration techniques for accurate image fusion of DWI with T2. RESULTS: Image data of 20 prostate patients with cancerous lesions or cysts were acquired. All registration algorithms were validated using intensity-based as well as landmark-based techniques. CONCLUSIONS: The authors' results show that the "fast elastic image registration" provides most accurate results with a target registration error of 1.07 ± 0.41 mm at minimum execution times of 11 ± 1 s.

Mammalian target of rapamycin and its downstream signalling components are activated in psoriatic skin.

BACKGROUND: Mammalian target of rapamycin (mTOR) signalling integrates signals leading to cellular growth, proliferation and differentiation. Disturbance of this tightly regulated interplay leads to malignancies, as reflected by altered mTOR signalling in epidermal tumours. As psoriatic keratinocytes also show features of perturbed cell growth and differentiation, the question arises as to whether mTOR signalling also plays a role in the pathogenesis of psoriasis. OBJECTIVES: To investigate the activation status of mTOR signalling components in psoriasis. METHODS: Biopsies from lesional and nonlesional skin of patients with psoriasis (n = 10), as well as samples from healthy donors (n = 3), were analysed by immunohistochemistry and Western blot, utilizing antibodies detecting phosphorylated mTOR, phospho-S6 kinase and phospho-S6 ribosomal protein. RESULTS: We found mTOR and its downstream signalling molecule, the ribosomal protein S6, to be activated in lesional psoriatic skin. While mTOR is activated throughout the whole epidermis, with particularly strong activation in the basal layer, S6 is active in suprabasal layers of differentiating keratinocytes. CONCLUSIONS: Altogether these results suggest a role for mTOR signalling in the epidermal changes leading to the psoriatic phenotype. mTOR inhibition might be a mode of action to explore in developing innovative antipsoriatic drugs.

The effect of regularization in motion compensated PET image reconstruction: a realistic numerical 4D simulation study.

Following continuous improvement in PET spatial resolution, respiratory motion correction has become an important task. Two of the most common approaches that utilize all detected PET events to motion-correct PET data are the reconstruct-transform-average method (RTA) and motion-compensated image reconstruction (MCIR). In RTA, separate images are reconstructed for each respiratory frame, subsequently transformed to one reference frame and finally averaged to produce a motion-corrected image. In MCIR, the projection data from all frames are reconstructed by including motion information in the system matrix so that a motion-corrected image is reconstructed directly. Previous theoretical analyses have explained why MCIR is expected to outperform RTA. It has been suggested that MCIR creates less noise than RTA because the images for each separate respiratory frame will be severely affected by noise. However, recent investigations have shown that in the unregularized case RTA images can have fewer noise artefacts, while MCIR images are more quantitatively accurate but have the common salt-and-pepper noise. In this paper, we perform a realistic numerical 4D simulation study to compare the advantages gained by including regularization within reconstruction for RTA and MCIR, in particular using the median-root-prior incorporated in the ordered subsets maximum a posteriori one-step-late algorithm. In this investigation we have demonstrated that MCIR with proper regularization parameters reconstructs lesions with less bias and root mean square error and similar CNR and standard deviation to regularized RTA. This finding is reproducible for a variety of noise levels (25, 50, 100 million counts), lesion sizes (8 mm, 14 mm diameter) and iterations. Nevertheless, regularized RTA can also be a practical solution for motion compensation as a proper level of regularization reduces both bias and mean square error.

[Beyond immunopathogenesis. Insulin resistance and "epidermal dysfunction"]. / Jenseits der Immunpathogenese. Insulinresistenz und "epidermale Dysfunktion".

Insulin is a central player in the regulation of metabolic as well as non-metabolic cells: inefficient signal transduction (insulin resistance) not only represents the cornerstone in the pathogenesis of type 2 diabetes mellitus, but also drives atherosclerosis through inducing endothelial dysfunction. Last but not least epidermal homeostasis depends on insulin. We summarize the effects of insulin on proliferation and differentiation of human keratinocytes as well as the relevance of cytokine-induced insulin resistance for alterations in epidermal homeostasis characteristic for psoriasis. Kinases involved in both insulin- as well as cytokine-receptor signaling represent potential targets for innovative therapeutics. Such small molecules would primarily normalize "epidermal dysfunction", thus complementing the immunomodulatory strategies of today's biologics.

Nonrigid motion modeling of the liver from 3-D undersampled self-gated golden-radial phase encoded MRI.

Magnetic resonance imaging (MRI) has been commonly used for guiding and planning image guided interventions since it provides excellent soft tissue visualization of anatomy and allows motion modeling to predict the position of target tissues during the procedure. However, MRI-based motion modeling remains challenging due to the difficulty of acquiring multiple motion-free 3-D respiratory phases with adequate contrast and spatial resolution. Here, we propose a novel retrospective respiratory gating scheme from a 3-D undersampled high-resolution MRI acquisition combined with fast and robust image registrations to model the nonrigid deformation of the liver. The acquisition takes advantage of the recently introduced golden-radial phase encoding (G-RPE) trajectory. G-RPE is self-gated, i.e., the respiratory signal can be derived from the acquired data itself, and allows retrospective reconstructions of multiple respiratory phases at any arbitrary respiratory position. Nonrigid motion modeling is applied to predict the liver deformation of an average breathing cycle. The proposed approach was validated on 10 healthy volunteers. Motion model accuracy was assessed using similarity-, surface-, and landmark-based validation methods, demonstrating precise model predictions with an overall target registration error of TRE = 1.70 ± 0.94 mm which is within the range of the acquired resolution.

Thoracic respiratory motion estimation from MRI using a statistical model and a 2-D image navigator.

Respiratory motion models have potential application for estimating and correcting the effects of motion in a wide range of applications, for example in PET-MR imaging. Given that motion cycles caused by breathing are only approximately repeatable, an important quality of such models is their ability to capture and estimate the intra- and inter-cycle variability of the motion. In this paper we propose and describe a technique for free-form nonrigid respiratory motion correction in the thorax. Our model is based on a principal component analysis of the motion states encountered during different breathing patterns, and is formed from motion estimates made from dynamic 3-D MRI data. We apply our model using a data-driven technique based on a 2-D MRI image navigator. Unlike most previously reported work in the literature, our approach is able to capture both intra- and inter-cycle motion variability. In addition, the 2-D image navigator can be used to estimate how applicable the current motion model is, and hence report when more imaging data is required to update the model. We also use the motion model to decide on the best positioning for the image navigator. We validate our approach using MRI data acquired from 10 volunteers and demonstrate improvements of up to 40.5% over other reported motion modelling approaches, which corresponds to 61% of the overall respiratory motion present. Finally we demonstrate one potential application of our technique: MRI-based motion correction of real-time PET data for simultaneous PET-MRI acquisition.

Fast generation of 4D PET-MR data from real dynamic MR acquisitions.

We have implemented and evaluated a framework for simulating simultaneous dynamic PET-MR data using the anatomic and dynamic information from real MR acquisitions. PET radiotracer distribution is simulated by assigning typical FDG uptake values to segmented MR images with manually inserted additional virtual lesions. PET projection data and images are simulated using analytic forward projections (including attenuation and Poisson statistics) implemented within the image reconstruction package STIR. PET image reconstructions are also performed with STIR. The simulation is validated with numerical simulation based on Monte Carlo (GATE) which uses more accurate physical modelling, but has 150× slower computation time compared to the analytic method for ten respiratory positions and is 7000× slower when performing multiple realizations. Results are validated in terms of region of interest mean values and coefficients of variation for 65 million coincidences including scattered events. Although some discrepancy is observed, agreement between the two different simulation methods is good given the statistical noise in the data. In particular, the percentage difference of the mean values is 3.1% for tissue, 17% for the lungs and 18% for a small lesion. The utility of the procedure is demonstrated by simulating realistic PET-MR datasets from multiple volunteers with different breathing patterns. The usefulness of the toolkit will be shown for performance investigations of the reconstruction, motion correction and attenuation correction algorithms for dynamic PET-MR data.

[Co-morbidities in psoriasis vulgaris]. / Komorbiditäten bei Psoriasis vulgaris.

Epidemiologic data document not only a higher prevalence of joint involvement among psoriasis patients than previously thought, but also an association with numerous other diseases, including depression, smoking, alcoholism, Crohn's disease, and metabolic syndrome. The resulting increased cardiovascular mortality is of particular clinical importance, and its pathogenetic link as a complication of the psoriatic inflammation is well recognized. Thus, we need to re-invent the management of psoriasis: Dermatologists are not only the sentinel regarding the early diagnosis of psoriatic arthritis, but also of metabolic complications such as dyslipidemia or diabetes. Moreover, they need to keep in mind interactions between (systemic) anti-psoriatic drugs and the co-medication of their patients as well as possible consequences of these co-medications on the course of psoriasis. To successfully accomplish this mission, a comprehensive management concept and ground-breaking research are urgently needed.

Does linezolid inhibit its own metabolism? Population pharmacokinetics as a tool to explain the observed nonlinearity in both healthy volunteers and septic patients.

Few studies investigating the population pharmacokinetics of linezolid in critically ill patients have been reported, yielding controversial results. Therefore, a population pharmacokinetic analysis using NONMEM was performed to thoroughly understand the pharmacokinetics of unbound linezolid in plasma. Data were obtained from 10 healthy volunteers and 24 septic patients. Intensive sampling was performed after single and multiple dosing. The pharmacokinetics of unbound linezolid was best described by a two-compartment model with an absorption rate constant (K(A), 1.81 h(-1)), clearance (CL, 11.1 l/h), volumes of distribution (V(2) and V(3), 20.0 and 28.9 liters, respectively), and intercompartmental clearance Q, 75.0 l/h). However, clearance was inhibited over time to 76.4% of its original value, dependent on the concentration in an empirical inhibition compartment. Overall, imprecision of parameter estimates was low to moderate. Comparison of goodness of fit graphics and of the predictive performance revealed that the presented model was superior to previously published models using linear elimination or parallel linear and Michaelis-Menten elimination and also to other of our own investigated model alternatives. The observed nonlinearity in linezolid pharmacokinetics might be a result of an inhibition of the formation of the major linezolid metabolite due to the inhibition of respiratory chain enzyme activity. To our knowledge, this study presents the first attempt to mechanistically explain the observed nonlinearity in linezolid pharmacokinetics. Finally, simulations demonstrated that the model might also serve as a tool to predict concentration-time profiles of linezolid, thus providing a rationale for a more targeted antimicrobial therapy.