Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

Image processing for displacement measurements

Since the invention of photography humans have been using images to capture, store and analyse the act that they are interested in. With the developments in this field, assisted by better computers, it is possible to use image processing technology as an accurate method of analysis and measurement. Image processing's principal qualities are flexibility, adaptability and the ability to easily and quickly process a large amount of information. Successful examples of applications can be seen in several areas of human life, such as biomedical, industry, surveillance, military and mapping. This is so true that there are several Nobel prizes related to imaging. The accurate measurement of deformations, displacements, strain fields and surface defects are challenging in many material tests in Civil Engineering because traditionally these measurements require complex and expensive equipment, plus time consuming calibration. Image processing can be an inexpensive and effective tool for load displacement measurements. Using an adequate image acquisition system and taking advantage of the computation power of modern computers it is possible to accurately measure very small displacements with high precision. On the market there are already several commercial software packages. However they are commercialized at high cost. In this work block-matching algorithms will be used in order to compare the results from image processing with the data obtained with physical transducers during laboratory load tests. In order to test the proposed solutions several load tests were carried out in partnership with researchers from the Civil Engineering Department at Universidade Nova de Lisboa (UNL).

Synthesis of Polymeric Nanoparticles for biomedical delivery applications

Polymeric nanoparticles (PNPs) have attracted considerable interest over the last few years due to their unique properties and behaviors provided by their small size. Such materials could be used in a wide range of applications such as diagnostics and drug delivery. Advantages of PNPs include controlled release, protection of drug molecules and its specific targeting, with concomitant increasing of the therapeutic index. In this work, novel sucrose and cholic acid based PNPs were prepared from different polymers, namely polyethylene glycol (PEG), poly(D,L-lactic-co-glycolic acid) (PLGA) and PLGA-co-PEG copolymer. In these PNP carriers, cholic acid will act as a drug incorporation site and the carbohydrate as targeting moiety. The uptake of nanoparticles into cells usually involves endocytotic processes, which depend primarily on their size and surface characteristics. These properties can be tuned by the nanoparticle preparation method. Therefore, the nanoprecipitation and the emulsion-solvent evaporation method were applied to prepare the PNPs. The influence of various parameters, such as concentration of the starting solution, evaporation method and solvent properties on the nanoparticle size, size distribution and morphology were studied. The PNPs were characterized by using atomic force microscopy (AFM), scanning electron microscopy (SEM) and dynamic light scattering (DLS) to assess their size distribution and morphology. The PNPs obtained by nanoprecipitation ranged in size between 90 nm and 130 nm with a very low polydispersity index (PDI < 0.3). On the other hand, the PNPs produced by the emulsion-solvent evaporation method revealed particle sizes around 300 nm with a high PDI value. More detailed information was found in AFM and SEM images, which demonstrated that all these PNPs were regularly spherical. ζ-potential measurements were satisfactory and evidenced the importance of sucrose moiety on the polymeric system, which was responsible for the obtained negative surface charge, providing colloidal stability. The results of this study show that sucrose and cholic acid based polymeric conjugates can be successfully used to prepare PNPs with tunable physicochemical characteristics. In addition, it provides novel information about the materials used and the methods applied. It is hoped that this work will be useful for the development of novel carbohydrate based nanoparticles for biomedical applications, specifically for targeted drug delivery.

Structural connectivity based on diffusion Kurtosis imaging

Structural connectivity models based on Diffusion Tensor Imaging (DTI) are strongly affected by the technique’s inability to resolve crossing fibres, either intra- or inter-hemispherical connections. Several models have been proposed to address this issue, including an algorithm aiming to resolve crossing fibres which is based on Diffusion Kurtosis Imaging (DKI). This technique is clinically feasible, even when multi-band acquisitions are not available, and compatible with multi-shell acquisition schemes. DKI is an extension of DTI enabling the estimation of diffusion tensor and diffusion kurtosis metrics. In this study we compare the performance of DKI and DTI in performing structural brain connectivity. Six healthy subjects were recruited, aged between 25 and 35 (three females). The MRI experiments were performed using a 3T Siemens Trio with a 32-channel head coil. The scans included a T1-weighted sequence (1mm3), and a DWI with b-values 0, 1000 and 2000 s:mm

Mechanisms underlying intracellular delivery

AuNPs are versatile systems used for different biomedical application including imaging, drug and gene delivery. These systems support the intracellular transport of active molecules, a step that is considered one of the crucial problems in drug delivery. Nevertheless, in order to design optimal multifunctional AuNPs for specific and efficient nanomedicine applications, the mechanism by which AuNPs interact with living cells must be fully understand. The main goal of this work consisted in the assessment of the cellular uptake mechanism of 14 nm spherical AuNPs by A549 cells, through fluorescent spectroscopy and microscopy, in combination with quantitative analysis by ICP-MS. TAMRA labeled AuNPs were characterized by UV-visible and fluorescent spectroscopy and the final hydrodynamic diameter of 22.5 ± 0.33 nm was obtained by DLS. Regarding the cellular uptake studies, the AuNPs presented a fast cellular uptake kinetics reaching a saturation point after 6 hours of incubation in A549 cells. Further investigation concerning the internalization mechanism of this AuNPs was evaluated using specific inhibitors for different endocytic pathways. Optimal inhibition was achieved using chlorpromazine, inhibitor of clathrin-mediated endocytosis, resulting in a 23.5 % inhibition of AuNPs after 1 hour of incubation. This preliminary result obtained by fluorescent spectroscopy suggests that these AuNPs were predominantly uptake by clathrin-mediated endocytosis, meaning that other endocytic pathways must be involved in the cellular uptake of this AuNPs. In what cell viability is concern, the prepared AuNPs and the endocytic inhibitors revealed no significant effect on the cell viability in A549 cell line.