Simulation of pharmacokinetic models

Teoretická část projektu se zabývá rozborem farmakokinetických dějů a základními vlastnostmi matematických modelů užívaných ve farmakokinetice. Tento popis je zaměřen především na modely využívané pro perfúzní zobrazovací metody. Cílem projektu je vytvořit algoritmus pro simulaci vybraných modelů na základě zadaných parametrů a algoritmus sloužící k proložení experimentálně měřených dat vybraným modelem s výpočtem základních farmakokinetických parametrů. Dalším krokem řešení je realizace grafického rozhraní, které umožní plně využívat vytvořené algoritmy v uživatelsky přístupnějším prostředí. Výstupem práce je program, který lze využít k získání parametrů reálných dat a jako názorná ukázka vlivu těchto parametrů na průběh zvolených funkcí.The theoretical part of this project is occupied with analysis of pharmacokinetic actions and also basic attributes of mathematical models used in pharmacokinetics. This description is mainly focused on models used for perfusion imaging methods. The aim of this project is to create an algorithm that simulates chosen models based on assigned parameters and also an algorithm that serves to fit experimentally measured data with a chosen model with a calculation of basic pharmacokinetic parameters. The next step of this solution is graphic interface realization which enables a full use of created algorithm in more accessible surroundings for the user. The result of this work is a program that can be used to obtain real data parameters and as well as a visual sample of the influence of these parameters on a process in a chosen functions.

Effect of increased left ventricle mass on ischemia assessment in electrocardiographic signals: rabbit isolated heart study

Detailed quantitative analysis of the effect of left ventricle (LV) hypertrophy on myocardial ischemia manifestation in ECG is still missing. The associations between both phenomena can be studied in animal models. In this study, rabbit isolated hearts with spontaneously increased LV mass were used to evaluate the effect of such LV alteration on ischemia detection criteria and performance. Electrophysiological effects of increased LV mass were evaluated on sixteen New Zealand rabbit isolated hearts under non-ischemic and ischemic conditions by analysis of various electrogram (EG) parameters. To reveal hearts with increased LV mass, LV weight/heart weight ratio was proposed. Standard paired and unpaired statistical tests and receiver operating characteristics analysis were used to compare data derived from different groups of animals, monitor EG parameters during global ischemia and evaluate their ability to discriminate between unchanged and increased LV as well as non-ischemic and ischemic state. Successful evaluation of both increased LV mass and ischemia is lead-dependent. Particularly, maximal deviation of QRS and area under QRS associated with anterolateral heart wall respond significantly to even early phase (the 1st-3rd min) of ischemia. Besides ischemia, these parameters reflect increased LV mass as well (with sensitivity reaching approx. 80%). However, the sensitivity of the parameters to both phenomena may lead to misinterpretations, when inappropriate criteria for ischemia detection are selected. Particularly, use of cut-off-based criteria defined from control group for ischemia detection in hearts with increased LV mass may result in dramatic reduction (approx. 15%) of detection specificity due to increased number of false positives. Nevertheless, criteria adjusted to particular experimental group allow achieving ischemia detection sensitivity of 89–100% and specificity of 94–100%, respectively. It was shown that response of the heart to myocardial ischemia can be successfully evaluated only when taking into account heart-related factors (such as LV mass) and other methodological aspects (such as recording electrodes position, selected EG parameters, cut-off criteria, etc.). Results of this study might be helpful for developing new clinical diagnostic strategies in order to improve myocardial ischemia detection in patients with LV hypertrophy

Segmentation of Electrocardiographic Signals Using Deep Learning Methods

The thesis deals with deep learning methods for the segmentation of surface and intracardiac electrocardiographic recording with focus on atrial activity. The theoretical part introduces current segmentation aproaches of electrocardiographic signals. Issues related to the development of deep learning models in context of standard ECG databases were also discussed. We proposed a pipeling for processing multimodal electrophysiology data from interventional procedures in order to build reliable training datasets. A deep model for segmentation of intracardiac recordings based on a modified residual architecture was proposed. A series of experiments was conducted to evaluate the effect of both model and dataset properties on segmentation quality. The annotation methodology of recordings with atrial fibrillation proved to be a crucial factor. Properties of loss function and type of data augmentation were revealed as secondary important parameters. A novel P wave segmentation method for incomplete references was proposed in the thesis. The approach was inspired by the deep contrast learning. It was modified to distinguish local segments of signals at different levels of abstraction of the extracted feature maps. Results were analyzed using standard quality metrics and post-hoc visual analysis. In some cases, a statistical comparison of experiments for different settings was performed. The results of the work showed that it is possible to use intracardiac signals for embedding a vector representation of local atrial activation into deep models

Delineation of experimental ECG data

Tato práce se zabývá návrhem algoritmu pro detekci komplexu QRS a nalezení hranic jednotlivých vln v cyklu EKG. Součástí práce je teoretický rozbor elektrofyziologie srdce a metod běžně užívaných pro detekci i rozměření signálu EKG. Z uvedených metod je realizován algoritmus založený na spojité vlnkové tranformaci. Detektor QRS i algoritmus pro rozměření jsou otestovány na standardní databázi signálů CSE vůči manuálně i automaticky stanoveným referenčním bodům. Dosažené výsledky jsou porovnány s dalšími obdobnými metodami. Diplomová práce se dále zabývá úpravou realizovaného algoritmu pro experimentální záznamy EKG z izolovaného králičího srdce podle Langendorffa. Jsou představena specifika snímání těchto dat a na základě časové a frekvenční analýzy jsou navrženy a realizovány dílčí modifikace algoritmu. Ověření účinnosti zvolených změn je pro velký rozsah záznamů provedeno na výběrové testovací databázi. Úspěšnost algoritmu je vyhodnocena na základě manuálně anotovaných referenčních bodů.This thesis deals with a proposition of an algorithm for QRS complex and typical ECG waves boundaries detection. It incorporates a literature research focused on heart electrophysiology and commonly used methods for ECG fiducial points detection and delineation. Out of the presented methods an algorithm based on a continuous wavelet transform is implemented. Detection and delineation algorithm is tested on CSE standard signal database towards references determined both manually and automatically. Obtained results are compared to other congenerous methods. The diploma thesis is further concerned with an algorithm modification for experimental electrocardiograms of isolated rabbit hearts. Recording specifics of these data are introduced. Additionally, based on time and frequency analysis, particular modifications of the algorithm are proposed and realized. Due to a large extent of records functionality is verified on randomly selected database samples. Efficiency of the modified algorithm is evaluated through manually annotated references.