Imaging and therapy with monoclonal antibodies in non-hematopoietic tumors.

Although radiolabelled monoclonal antibodies are useful in tumor imaging, in our opinion their most important role is in the evaluation of the capacity of newly developed monoclonal antibodies to localize in tumors specifically. Intravenous injections of monoclonal antibody fragments, labelled with beta-emitting radionuclides, can completely eradicate large human colon carcinoma xenografts in nude mice whereas this is not achieved by unconjugated monoclonal antibodies. New strategies are being developed to make radioimmunotherapy applicable to carcinoma patients.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Thrombin-sensitive dual fluorescence imaging and therapeutic agent for detection and treatment of synovial inflammation in murine rheumatoid arthritis.

We have developed a thrombin-sensitive polymeric photosensitizer prodrug (T-PS) to selectively image and eradicate inflammatory lesions in rheumatoid arthritis (RA). Thrombin is a serine protease up-regulated in synovial tissues of rheumatoid arthritis (RA) patients. T-PS consists of a polymeric backbone, to which multiple photosensitizer (PS) units are tethered via short thrombin-cleavable peptide linkers. Fluorescence emission and phototoxicity of the prodrug are efficiently quenched due to the interaction of neighboring photosensitizer units. The prodrug is passively delivered to the inflammation site via the enhanced permeability and retention (EPR) effect. Subsequent site-selective proteolytic cleavage of the peptide linkers restores its photoactivity by increasing the mutual distance between PS. Whole animal imaging in murine collagen-induced arthritis, an experimental model of RA revealed a dose-dependent fluorescence increase in arthritic paws after systemic prodrug injection. In addition, administration of T-PS resulted in much higher fluorescence selectivity for arthritic joints as compared to the free PS. Irradiation of the arthritic joints induced light dose dependent phototoxic effects such as apoptosis, vascular damage and local hemorrhage. Long-term observations showed complete regression of the latter. Irradiated non-arthritic tissues or non-irradiated arthritic tissues showed no histological effects after photodynamic therapy with T-PS. This illustrates that T-PS can localize inflammatory lesions with excellent selectivity and induce apoptosis and vascular shut down after irradiation.

Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond.

The complex structural organization of the white matter of the brain can be depicted in vivo in great detail with advanced diffusion magnetic resonance (MR) imaging schemes. Diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique-the mapping of apparent diffusion coefficient values-to the more complex, such as diffusion tensor imaging, q-ball imaging, diffusion spectrum imaging, and tractography. The type of structural information obtained differs according to the technique used. To fully understand how diffusion MR imaging works, it is helpful to be familiar with the physical principles of water diffusion in the brain and the conceptual basis of each imaging technique. Knowledge of the technique-specific requirements with regard to hardware and acquisition time, as well as the advantages, limitations, and potential interpretation pitfalls of each technique, is especially useful.

Endorectal Magnetic Resonance Imaging and Spectroscopy Are Useful for Selecting Candidates for Biopsy among Patients with Persistently Elevated Prostate Specific Antigen

To evaluate the efficacy of endorectal Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spetroscopic Imaging (MRSI) combined with total prostate-specific antigen (tPSA) and free prostate-specific antigen (fPSA) in selecting candidates for biopsy. Subjects and Methods: 246 patients with elevated tPSA (median: 7.81 ng/ml) underwent endorectal MRI and MRSI before Transrectal Ultrasound (TRUS) biopsy (10 peripheral + 2 central cores); patients with positive biopsies were treated with radical intention; those with negative biopsies were followed up and underwent MRSI before each additional biopsy if tPSA rose persistently. Mean follow-up: 27.6 months. We compared MRI, MRSI, tPSA, and fPSA with histopathology by sextant and determined the association between the Gleason score and MRI and MRSI. We determined the most accurate combination to detect prostate cancer (PCa) using receiver operating curves; we estimated the odds ratios (OR) and calculated sensitivity, specificity, and positive and negative predictive values. Results: No difference in tPSA was found between patients with and without PCa (p = 0.551). In the peripheral zone, the risk of PCa increased with MRSI grade; patients with high-grade MRSI had the greatest risk of PCa over time (OR = 328.6); the model including MRI, MRSI, tPSA, and fPSA was more accurate (Area under Curve: AUC = 95.7%) than MRI alone (AUC = 85.1%) or fPSA alone (AUC = 78.1%), but not than MRSI alone (94.5%). In the transitional zone, the model was less accurate (AUC = 84.4%). The association (p = 0.005) between MRSI and Gleason score was significant in both zones. Conclusions: MRSI is useful in patients with elevated tPSA. High-grade MRSI lesions call for repeated biopsies. Men with negative MRSI may forgo further biopsies because a significantly high Gleason lesion is very unlikely

EasyStrata: evaluation and visualization of stratified genome-wide association meta-analysis data.

The R package EasyStrata facilitates the evaluation and visualization of stratified genome-wide association meta-analyses (GWAMAs) results. It provides (i) statistical methods to test and account for between-strata difference as a means to tackle gene-strata interaction effects and (ii) extended graphical features tailored for stratified GWAMA results. The software provides further features also suitable for general GWAMAs including functions to annotate, exclude or highlight specific loci in plots or to extract independent subsets of loci from genome-wide datasets. It is freely available and includes a user-friendly scripting interface that simplifies data handling and allows for combining statistical and graphical functions in a flexible fashion. AVAILABILITY: EasyStrata is available for free (under the GNU General Public License v3) from our Web site www.genepi-regensburg.de/easystrata and from the CRAN R package repository cran.r-project.org/web/packages/EasyStrata/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Real-time Imaging and Mosaicking of Planar Surfaces

Laajojen pintojen kuvaaminen rajoitetussa työskentelytilassa riittävällä kuvatarkkuudella voi olla vaikeaa. Kuvaaminen on suoritettava osissa ja osat koottava saumattomaksi kokonaisnäkymäksi eli mosaiikkikuvaksi. Kuvauslaitetta käsin siirtelevän käyttäjän on saatava välitöntä palautetta, jotta mosaiikkiin ei jäisi aukkoja ja työ olisi nopeaa. Työn tarkoituksena oli rakentaa pieni, kannettava ja tarkka kuvauslaite paperi- ja painoteollisuuden tarpeisiin sekä kehittää palautteen antamiseen menetelmä, joka koostaaja esittää karkeaa mosaiikkikuvaa tosiajassa. Työssä rakennettiin kaksi kuvauslaitetta: ensimmäinen kuluttajille ja toinen teollisuuteen tarkoitetuista osista. Kuvamateriaali käsiteltiin tavallisella pöytätietokoneella. Videokuvien välinen liike laskettiin yksinkertaisella seurantamenetelmällä ja mosaiikkikuvaa koottiin kameroiden kuvanopeudella. Laskennallista valaistuksenkorjausta tutkittiin ja kehitetty menetelmä otettiin käyttöön. Ensimmäisessä kuvauslaitteessa on ongelmia valaistuksen ja linssivääristymien kanssa tuottaen huonolaatuisia mosaiikkikuvia. Toisessa kuvauslaitteessa nämä ongelmat on korjattu. Seurantamenetelmä toimii hyvin ottaen huomioon sen yksinkertaisuuden ja siihen ehdotetaan monia parannuksia. Työn tulokset osoittavat, että tosiaikainen mosaiikkikuvan koostaminen megapikselin kuvamateriaalista on mahdollista kuluttajille tarkoitetulla tietokonelaitteistolla.

Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.

An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.

Magnetic resonance imaging and BMB score in the evaluation of bone involvement in Gaucher’s disease patients

AbstractObjective:To evaluate by magnetic resonance imaging changes in bone marrow of patients undergoing treatment for type I Gaucher’s disease.Materials and Methods:Descriptive, cross-sectional study of Gaucher’s disease patients submitted to 3 T magnetic resonance imaging of femurs and lumbar spine. The images were blindly reviewed and the findings were classified according to the semiquantitative bone marrow burden (BMB) scoring system.Results:All of the seven evaluated patients (three men and four women) presented signs of bone marrow infiltration. Osteonecrosis of the femoral head was found in three patients, Erlenmeyer flask deformity in five, and no patient had vertebral body collapse. The mean BMB score was 11, ranging from 9 to 14.Conclusion:Magnetic resonance imaging is currently the method of choice for assessing bone involvement in Gaucher’s disease in adults due to its high sensitivity to detect both focal and diffuse bone marrow changes, and the BMB score is a simplified method for semiquantitative analysis, without depending on advanced sequences or sophisticated hardware, allowing for the classification of the disease extent and assisting in the treatment monitoring.

Cardiac magnetic resonance imaging and computed tomography in ischemic cardiomyopathy: an update

Abstract Ischemic cardiomyopathy is one of the major health problems worldwide, representing a significant part of mortality in the general population nowadays. Cardiac magnetic resonance imaging (CMRI) and cardiac computed tomography (CCT) are noninvasive imaging methods that serve as useful tools in the diagnosis of coronary artery disease and may also help in screening individuals with risk factors for developing this illness. Technological developments of CMRI and CCT have contributed to the rise of several clinical indications of these imaging methods complementarily to other investigation methods, particularly in cases where they are inconclusive. In terms of accuracy, CMRI and CCT are similar to the other imaging methods, with few absolute contraindications and minimal risks of adverse side-effects. This fact strengthens these methods as powerful and safe tools in the management of patients. The present study is aimed at describing the role played by CMRI and CCT in the diagnosis of ischemic cardiomyopathies.

Successful minimally invasive surgery for primary hyperparathyroidism: influence of preoperative imaging and intraoperative parathyroid hormone levels.

PURPOSE: Adenoma is the main parathyroid disorder leading to primary hyperparathyroidism (PHP). Minimally invasive parathyroidectomy (MIP) is recognized as a valid procedure for adenoma-related PHP. It requires precise preoperative localization combining Tc-99m-MIBI (methoxy-isobutyl-isonitrile) scintigraphy and single-photon emission computed tomography (SPECT) with x-ray computed tomography (CT) and intraoperative confirmation of successful excision by change in intact parathormone (iPTH) levels. The study aim was to assess the surgery success in relation to these two parameters. METHODS: All patients operated on for PHP from 2005 to mid-2014 at our institution were retrospectively reviewed. MIP was performed in case of precise preoperative adenoma localization on scintigraphy, absence of past cervical surgery, and absence of concomitant thyroid resection necessity. In these patients, iPTH levels were monitored intraoperatively. Confirmation criteria for iPTH values were a return to normal level or a decrease >50 % of basal iPTH level. RESULTS: There were 197 PHP operations during the study period: 118 MIP and 79 bilateral neck explorations (BNEs). The MIP success rate was 95 % (112/118) with a preoperative MIBI scan ± CT accurate in 94 % (111/118) of the patients and with correct iPTH in 90 % (106/118) of the cases. Among the 12 iPTH levels that did not meet the confirmation criteria, 10 returned to normal range by postoperative day 2. Treatment failure appeared in three patients (one BNE, two MIPs). CONCLUSIONS: Tc-99m-MIBI dual-phase scintigraphy with SPECT/CT is the key examination for functional and morphological parathyroid adenoma localization. If preoperative scintigraphy is obvious and intraoperative assessment is clear, one could possibly safely omit iPTH, as it may lead to unnecessary BNE in primary PHP.

Imaging and Characterisation of Dirt Particles in Pulp and Paper

Dirt counting and dirt particle characterisation of pulp samples is an important part of quality control in pulp and paper production. The need for an automatic image analysis system to consider dirt particle characterisation in various pulp samples is also very critical. However, existent image analysis systems utilise a single threshold to segment the dirt particles in different pulp samples. This limits their precision. Based on evidence, designing an automatic image analysis system that could overcome this deficiency is very useful. In this study, the developed Niblack thresholding method is proposed. The method defines the threshold based on the number of segmented particles. In addition, the Kittler thresholding is utilised. Both of these thresholding methods can determine the dirt count of the different pulp samples accurately as compared to visual inspection and the Digital Optical Measuring and Analysis System (DOMAS). In addition, the minimum resolution needed for acquiring a scanner image is defined. By considering the variation in dirt particle features, the curl shows acceptable difference to discriminate the bark and the fibre bundles in different pulp samples. Three classifiers, called k-Nearest Neighbour, Linear Discriminant Analysis and Multi-layer Perceptron are utilised to categorize the dirt particles. Linear Discriminant Analysis and Multi-layer Perceptron are the most accurate in classifying the segmented dirt particles by the Kittler thresholding with morphological processing. The result shows that the dirt particles are successfully categorized for bark and for fibre bundles.