Sodium ion transfer across micro water/1,2-DCE interface facilitated by liquid crystal crown ether

The sodium ion transfer across the micro-water/1,2-dichloroethane interface facilitated by a novel ionophore, liquid crystal crown ether was studied systematically. The sodium ion transfer facilitated by LCCE is controlled by diffusion studied by cyclic voltammetry. The diffusion coefficient of LCCE in 1,2-dichloroethane was calculated to be equal to (2.61 +/- 0.12) X 10(-6) cm(2)/s and the stability constant of the complex between Na+ and LCCE was determined as lg beta (o) = 5.7 in 1,2-dichloroethane.

DCE: the dynamic conditional execution in a multipath control independent architecture

This thesis presents DCE, or Dynamic Conditional Execution, as an alternative to reduce the cost of mispredicted branches. The basic idea is to fetch all paths produced by a branch that obey certain restrictions regarding complexity and size. As a result, a smaller number of predictions is performed, and therefore, a lesser number of branches are mispredicted. DCE fetches through selected branches avoiding disruptions in the fetch flow when these branches are fetched. Both paths of selected branches are executed but only the correct path commits. In this thesis we propose an architecture to execute multiple paths of selected branches. Branches are selected based on the size and other conditions. Simple and complex branches can be dynamically predicated without requiring a special instruction set nor special compiler optimizations. Furthermore, a technique to reduce part of the overhead generated by the execution of multiple paths is proposed. The performance achieved reaches levels of up to 12% when comparing a Local predictor used in DCE against a Global predictor used in the reference machine. When both machines use a Local predictor, the speedup is increased by an average of 3-3.5%.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Modelli compartimentali per l'analisi di segnali ottenuti tramite DCE MRI per studi di perfusione epatica

Il presente lavoro di tesi si inserisce all'interno di uno studio dal titolo: "Strategia di posizionamento multi-step come approccio pragmatico per ridurre il rischio di encefalopatia epatica post-TIPS (shunt trans-giugulare porto-sistemico intraepatico) in pazienti cirrotici con ascite refrattaria". Il progetto di tesi si è concentrato sull'analisi dei segnali ottenuti tramite DCE MRI, con lo scopo di implementare in ambiente MatLab due modelli differenti (Dual input - Mono compartment e Dual input - Dual compartment) che descrivono la cinetica del tracciante all'interno del sistema vascolare epatico e valutare l'efficacia dei parametri di perfusione associati nella descrizione delle variazioni in termini di microcircolazione introdotte dall'inserimento del TIPS. Inizialmente si sono voluti valutare, tramite simulazione, gli effetti in termini di amplificazione del rumore e stima dei parametri perfusionali dell'approssimazione lineare nella conversione da intensità di segnale MR a concentrazione di mezzo di contrasto. Successivamente, sempre attraverso simulazioni, per entrambi i modelli considerati è stato scelto uno schema di model-fitting e quindi testata l'affidabilità in termini di accuratezza e precisione delle stime dei parametri ottenute in funzione del livello di rumore associato alle curve di intensità di segnale. Parallelamente all'implementazione dei modelli per la stima di parametri di perfusione, sono stati realizzati dei phantom con l'obiettivo di simulare il parenchima epatico prima e dopo l'arrivo del mezzo di contrasto e poter testare la sequenza utilizzata durante l'acquisizione dei dati su paziente. Infine sono stati considerati gli esami di DCE MRI effettuati su un campione di nove pazienti pre e post-TIPS, utilizzando per l'analisi dei segnali entrambi i modelli implementati in fase di simulazione e successivamente valutando le variazioni nel valori associati ai parametri di perfusione introdotte dall'inserimento del TIPS.

Measurement of the vascular input function in mice for DCE-MRI

DCE-MRI is an important technique in the study of small animal cancer models because its sensitivity to vascular changes opens the possibility of quantitative assessment of early therapeutic response. However, extraction of physiologically descriptive parameters from DCE-MRI data relies upon measurement of the vascular input function (VIF), which represents the contrast agent concentration time course in the blood plasma. This is difficult in small animal models due to artifacts associated with partial volume, inflow enhancement, and the limited temporal resolution achievable with MR imaging. In this work, the development of a suite of techniques for high temporal resolution, artifact resistant measurement of the VIF in mice is described. One obstacle in VIF measurement is inflow enhancement, which decreases the sensitivity of the MR signal to the presence of contrast agent. Because the traditional techniques used to suppress inflow enhancement degrade the achievable spatiotemporal resolution of the pulse sequence, improvements can be achieved by reducing the time required for the suppression. Thus, a novel RF pulse which provides spatial presaturation contemporaneously with the RF excitation was implemented and evaluated. This maximizes the achievable temporal resolution by removing the additional RF and gradient pulses typically required for suppression of inflow enhancement. A second challenge is achieving the temporal resolution required for accurate characterization of the VIF, which exceeds what can be achieved with conventional imaging techniques while maintaining adequate spatial resolution and tumor coverage. Thus, an anatomically constrained reconstruction strategy was developed that allows for sampling of the VIF at extremely high acceleration factors, permitting capture of the initial pass of the contrast agent in mice. Simulation, phantom, and in vivo validation of all components were performed. Finally, the two components were used to perform VIF measurement in the murine heart. An in vivo study of the VIF reproducibility was performed, and an improvement in the measured injection-to-injection variation was observed. This will lead to improvements in the reliability of quantitative DCE-MRI measurements and increase their sensitivity.

DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data

Background DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity. Results Pixel-wise model-based quantitative parameters are estimated by fitting DCE-MRI data to several pharmacokinetic models using the Levenberg-Marquardt algorithm (LMA). DCE@urLAB also includes the semi-quantitative parametric and heuristic analysis approaches commonly used in practice. This software application has been programmed in the Interactive Data Language (IDL) and tested both with publicly available simulated data and preclinical studies from tumor-bearing mouse brains. Conclusions A user-friendly solution for applying pharmacokinetic and non-quantitative analysis DCE-MRI in preclinical studies has been implemented and tested. The proposed tool has been specially designed for easy selection of multi-pixel ROIs. A public release of DCE@urLAB, together with the open source code and sample datasets, is available at http://www.die.upm.es/im/archives/DCEurLAB/ webcite.

Památník Karla Havlíčka Borovského; k stoletým narozenínám neohroženého politického vůdce, pravého politického buditele a národního mučedníka.

Mode of access: Internet.

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

Fascicule technique pour la mise en œuvre du suivi "Paramètres Physico-Chimiques & Phytoplancton" du réseau de contrôle de surveillance DCE à La Réunion : Réseau Hydrologique du Littoral Réunionnais

De 2010 à 2012, le projet " Bon Etat : Actualisation de l’état des lieux du SDAGE, volet eaux côtières réunionnaises " (DEAL de La Réunion/Ifremer) a permis la mise en place de 4 groupes de travail DCE experts dont les travaux ont été synthétisés à travers 4 fascicules techniques définissant les conditions de mise en oeuvre des différents suivis du réseau de contrôle de la surveillance (RCS) DCE en milieu marin à la Réunion. Une première version du fascicule "Physico-chimie & phytoplancton", a été produite en 2012 et validée au niveau national par les référents DCE (Coordination "phytoplancton", Coordination "hydrologie", Coordination nationale DCE milieu Marin, responsable projet Quadrige). Une mise à jour a été proposée en 2015 (Office de l'eau Réunion/Ifremer) dans la double perspective des recommandations du GT DCE de la Réunion et des nouvelles campagnes de suivi du "Réseau Hydrologique du Littoral Réunionnais - RHLR". Ce fascicule a vocation à constituer le support technique des méthodes et des référentiels pour la réalisation du suivi "RHLR" du RCS DCE à La Réunion. Il précise les protocoles de prélèvement, d’analyse, de bancarisation, de synthèse et de diffusion des données. Il présente également les indicateurs associés aux différents éléments de qualité, adaptés à La Réunion

Expertise sur 3 masses d’eau de la Réunion (étangs de Saint-Paul et du Gol) et de Martinique (étang des Salines) : typologie et surveillance DCE

Trois masses d’eau situées sur le littoral de l’île de la Réunion et de la Martinique présentent des fonctionnements et des caractéristiques atypiques, ce qui pose actuellement des difficultés dans le cadre de l’application de la DCE. Les deux masses d’eau réunionnaises, l’étang du Gol et l’étang de Saint-Paul, sont actuellement identifiées en tant que plans d’eau au titre de la DCE. La masse d’eau martiniquaise, l’étang des Salines, est quant à elle identifiée en tant que masse d’eau de transition. L’objectif de cette étude est d’apporter une expertise, sur la base des données disponibles et des échanges avec les experts locaux et nationaux, concernant : · la typologie des masses d’eau, · les paramètres chimiques, physico-chimiques et biologiques pertinents à suivre dans le cadre de la surveillance DCE, · des pistes de travail pour consolider des grilles de diagnostic sur les masses d’eau. Cette expertise s’appuie également sur les retours d’expériences et les études réalisées dans le cadre de la mise en oeuvre de la DCE sur les lagunes des bassins Rhône Méditerranée et Corse, dont la morphologie et le fonctionnement se rapprochent des trois masses d’eau étudiées. L’analyse des données et études fournies sur les étangs réunionnais du Gol et de Saint-Paul conduit à poser la question de la pertinence de leur maintien dans le référentiel des masses d’eau au titre de la DCE. Si le choix est cependant fait de conserver ces étangs en tant que masses d’eau DCE, leurs caractéristiques correspondraient à la typologie des eaux de transition et à la gamme de salinité oligohaline. Des recommandations sont formulées en termes d’études complémentaires visant à préciser le fonctionnement hydrologique de ces étangs et de priorisation des suivis de leur qualité physico-chimique et biologique, pour aboutir à une surveillance DCE pérenne. Les recommandations formulées à partir des données fournies sur l’étang martiniquais des Salines concernent l’évaluation des pressions anthropiques pesant sur cette masse d’eau, la priorisation des suivis de sa qualité chimique, physico-chimique et biologique dans le cadre de la surveillance DCE. Des pistes sont également données pour l’élaboration et la consolidation de grilles de diagnostic adaptées à cet étang.

Reductive dechlorination of TCE and cis-DCE by zero-valent iron and iron-based bimetallic reductants

CEs are the most frequently detected pollutants in groundwater. Several studies have been shown iron-based bimetallic reductants as a good method toward to chlorinated ethylenes degradation. However, many fundamental issues surrounding the chemistry of this phenomena remains elusive. In this study, kinetics and compound specific isotope analysis for reductive dechlorination of TCE and cis-DCE by unamended iron and iron-based bimetal reductants was evaluated. Generally, all the bimetals reductants tested revealed to increase the reactivity of the degradation, in which palladium and nickel were the additional metals more reactive. Ethene and ethane were the major products of TCE degradation. It is supported the simultaneous hydrogenolysis and β-elimination reaction hypothesis, however, the first step of TCE degradation by Au/Fe undergoes preferably by β-elimination, while by unamended iron, Pt/Fe and Co/Fe goes preferably by hydrogenolysis. No apparent elucidation was obtained to explain the high reactivity on bimetals systems; Degradação do TCE e cis-DCE por ferro de valência zero e redutores bimetálicos à base de ferro Resumo: Etilenos clorados são os poluentes mais frequentemente detetados na água subterrânea. Vários estudos têm mostrado que redutores bimetálicos à base de ferro são um bom método para a degradação dos etilenos clorados. Porém, muitas questões fundamentais acerca da química deste fenómeno permanecem elusivas. Neste estudo foi avaliada a cinética e a análise isotópica de compostos específicos para a degradação do TCE e cis-DCE por ferro e redutores bimetálicos à base de ferro. Genericamente, os redutores bimetálicos mostraram aumentar a reatividade da degradação, sendo paládio e níquel os metais adicionais mais reativos. Os produtos principais da degradação do TCE foram eteno e etano. É apoiada a hipótese da simultaneidade de hidrogenólise e β-eliminação, porém, o primeiro passo da degradação do TCE por Au/Fe é realizada preferencialmente por β-eliminação, enquanto por ferro, Pt/Fe e Co/Fe é realizada preferencialmente por hidrogenólise. Não houve uma elucidação aparente para explicar a reatividade nos sistemas bimetálicos.