Publications

Accurate volumetric assessment in non-small cell lung cancer (NSCLC) is critical for adequately informing treatments. In this study we assessed the clinical relevance of a semiautomatic computed tomography (CT)-based segmentation method using the competitive region-growing based algorithm, implemented in the free and public available 3D-Slicer software platform. We compared the 3D-Slicer segmented volumes by three independent observers, who segmented the primary tumour of 20 NSCLC patients twice, to manual slice-by-slice delineations of five physicians. Furthermore, we compared all tumour contours to the macroscopic diameter of the tumour in pathology, considered as the "gold standard". The 3D-Slicer segmented volumes demonstrated high agreement (overlap fractions > 0.90), lower volume variability (p = 0.0003) and smaller uncertainty areas (p = 0.0002), compared to manual slice-by-slice delineations. Furthermore, 3D-Slicer segmentations showed a strong correlation to pathology (r = 0.89, 95%CI, 0.81-0.94). Our results show that semiautomatic 3D-Slicer segmentations can be used for accurate contouring and are more stable than manual delineations. Therefore, 3D-Slicer can be employed as a starting point for treatment decisions or for high-throughput data mining research, such as Radiomics, where manual delineating often represent a time-consuming bottleneck.

This paper investigates a diffeomorphic point-set registration based on non-stationary mixture models. The goal is to improve the non-linear registration of anatomical structures by representing each point as a general non-stationary kernel that provides information about the shape of that point. Our framework generalizes work done by others that use stationary models. We achieve this by integrating the shape at each point when calculating the point-set similarity and transforming it according to the calculated deformation. We also restrict the non-rigid transform to the space of symmetric diffeomorphisms. Our algorithm is validated in synthetic and human datasets in two different applications: fiber bundle and lung airways registration. Our results shows that non-stationary mixture models are superior to Gaussian mixture models and methods that do not take into account the shape of each point.

We propose a top-down fully automatic 3D vertebra segmentation algorithm using global shape-related as well as local appearance-related prior information. The former is brought into the system by a global statistical shape model built from annotated training data, i.e., annotated CT volumes. The latter is handled by a machine learning-based component, i.e., a boundary detector, providing a strong discriminative model for vertebra surface appearance by making use of local context-encoding features. This boundary detector, which is essentially a probabilistic boosting-tree classifier, is also learnt from annotated training data. Contextual information is taken into account by representing vertebra surface candidate voxels with high-dimensional vectors of 3D steerable features derived from the observed volume intensities. Our system does not only consider the body of the individual vertebrae but also the spinal processes. Before segmentation, the image parts depicting individual vertebrae are spatially normalized with respect to their bounding box information in terms of translation, orientation, and scale leading to more accurate results. We evaluate segmentation accuracy on 7 CT volumes each depicting 22 vertebrae. The results indicate a symmetric point-to-mesh surface error of 1.37 ± 0.37 mm, which matches the current state-of-the-art.

Amyloid deposits from several human diseases have been found to contain membrane lipids. Co-aggregation of lipids and amyloid proteins in amyloid aggregates, and the related extraction of lipids from cellular membranes, can influence structure and function in both the membrane and the formed amyloid deposit. Co-aggregation can therefore have important implications for the pathological consequences of amyloid formation. Still, very little is known about the mechanism behind co-aggregation and molecular structure in the formed aggregates. To address this, we study in vitro co-aggregation by incubating phospholipid model membranes with the Parkinson’s disease-associated protein, α-synuclein, in monomeric form. After aggregation, we find spontaneous uptake of phospholipids from anionic model membranes into the amyloid fibrils. Phospholipid quantification, polarization transfer solid-state NMR and cryo-TEM together reveal co-aggregation of phospholipids and α-synuclein in a saturable manner with a strong dependence on lipid composition. At low lipid to protein ratios, there is a close association of phospholipids to the fibril structure, which is apparent from reduced phospholipid mobility and morphological changes in fibril bundling. At higher lipid to protein ratios, additional vesicles adsorb along the fibrils. While interactions between lipids and amyloid-protein are generally discussed within the perspective of different protein species adsorbing to and perturbing the lipid membrane, the current work reveals amyloid formation in the presence of lipids as a co-aggregation process. The interaction leads to the formation of lipid-protein co-aggregates with distinct structure, dynamics and morphology compared to assemblies formed by either lipid or protein alone.

INTRODUCTION: Smaller hippocampal volumes similar to those found in schizophrenia (SZ) are frequently observed to a lesser extent in non-psychotic first-degree relatives of patients with the illness, compared to control subjects. In this study, subdivisions of the hippocampal formation and their association with verbal and visual learning and memory were assessed in persons at familial high risk (FHR) for SZ.

The stratum corneum (SC) is an effective permeability barrier. One strategy to increase drug delivery across skin is to increase the hydration. A detailed description of how hydration affects skin permeability requires characterization of both macroscopic and molecular properties and how they respond to hydration. We explore this issue by performing impedance experiments on excised skin membranes in the frequency range 1 Hz to 0.2 MHz under the influence of a varying gradient in water activity (aw). Hydration/dehydration induces reversible changes of membrane resistance and effective capacitance. On average, the membrane resistance is 14 times lower and the effective capacitance is 1.5 times higher when the outermost SC membrane is exposed to hydrating conditions (aw = 0.992), as compared to the case of more dehydrating conditions (aw = 0.826). Molecular insight into the hydration effects on the SC components is provided by natural-abundance (13)C polarization transfer solid-state NMR and x-ray diffraction under similar hydration conditions. Hydration has a significant effect on the dynamics of the keratin filament terminals and increases the interchain spacing of the filaments. The SC lipids are organized into lamellar structures with \~ 12.6 nm spacing and hexagonal hydrocarbon chain packing with mainly all-trans configuration of the acyl chains, irrespective of hydration state. Subtle changes in the dynamics of the lipids due to mobilization and incorporation of cholesterol and long-chain lipid species into the fluid lipid fraction is suggested to occur upon hydration, which can explain the changes of the impedance response. The results presented here provide information that is useful in explaining the effect of hydration on skin permeability.

A new technique has been developed using NMR chemical shift imaging (CSI) to monitor water penetration and molecular transport in initially dry polymer tablets that also contain small low-molecular weight compounds to be released from the tablets. Concentration profiles of components contained in the swelling tablets could be extracted via the intensities and chemical shift changes of peaks corresponding to protons of the components. The studied tablets contained hydrophobically modified poly(acrylic acid) (HMPAA) as the polymer component and griseofulvin and ethanol as hydrophobic and hydrophilic, respectively, low-molecular weight model compounds. The water solubility of HMPAA could be altered by titration with NaOH. In the pure acid form, HMPAA tablets only underwent a finite swelling until the maximum water content of the polymer-rich phase, as confirmed by independent phase studies, had been reached. By contrast, after partial neutralization with NaOH, the polyacid became fully miscible with water. The solubility of the polymer affected the water penetration, the polymer release, and the releases of both ethanol and griseofulvin. The detailed NMR CSI concentration profiles obtained highlighted the clear differences in the disintegration/dissolution/release behavior for the two types of tablet and provided insights into their molecular origin. The study illustrates the potential of the NMR CSI technique to give information of importance for the development of pharmaceutical tablets and, more broadly, for the general understanding of any operation that involves the immersion and ultimate disintegration of a dry polymer matrix in a solvent.

Friedreich ataxia (FRDA) is a common inherited ataxia, caused by an expanded GAA repeat sequence in the Frataxin (FXN) gene. The proprioceptive system, which enters the cerebellum through the cerebellar peduncles, is a primary focus of pathology. In this study, we investigate the relationship of clinical and genetic data with diffusion-tensor imaging (DTI) indices reflecting white matter integrity of the cerebellar peduncles. Nine FRDA patients underwent DTI. After between-subject registration using tract-based spatial statistics, a white matter atlas was used for computing average values of DTI indices in the regions of interest. These were the inferior, middle and superior cerebellar peduncles (ICP, MCP, SCP). For Bonferroni correction, significance threshold was set to p 0.0056. We found that radial diffusivity (D(⊥)) within the ICP significantly correlated with scores on the Friedreich Ataxia Rating Scale (FARS, Spearman’s ρ = 0.883, p = 0.0016, all two-sided) and, at trend level, with number of trinucleotide repeats (ρ = 0.812, p = 0.008). D(⊥) in the SCP correlated with scores on the Scale for the Assessment and Rating of Ataxia (SARA, ρ = 0.867, p = 0.0025). These findings support the role of DTI, and especially D(⊥), as an informative biomarker in FRDA.