Advanced Methods of Perfusion Analysis in MRI

Tato doktorská práce se zabývá problematikou kvantitativní analýzy pomocí MRI a použití exogenní kontrastní látky. Jedná se o dvě metody, Dynamic contrast-enhanced MRI (DCE-MRI) a Dynamic susceptibility contrast MRI (DSC-MRI), které jsou většinou zpracovávány samostatně. Jedná se o unikátní metody, které poskytují cenné informace, avšak nejsou odbornou veřejností dostatečně přijímány kvůli nespolehlivosti odhadů parametrů a nejsou tak běžně používány ve vyšetřovacích protokolech. Tato dizertační práce si klade za cíl zlepšit spolehlivost metody DCE a odhady parametrů DSC. Práce se zejména zaměřuje na řešení problému kvantifikace při extravazaci kontrastní látky v DSC analýze a dále na nestabilitu DCE odhadů v případě použití pokročilých DCE farmakokinetických modelů s větším počtem parametrů. S použitím nových přístupů zpracování z literatury pro zpracování simultánně měřených DCE a DSC dat je možno odhadnout nové parametry vyšetřované tkáně - relaxivitu vaskulárního a intersticiálního prostoru. Pro tuto metodiku byl původně použit 2CXM model. V této práci je tato metodika testována s dalšími typy modelů, přičemž je kladen důraz na jejich spolehlivost v rámci spojení DCE a DSC. Bylo zjištěno, že model ATH je pro tento účel vhodnější než 2CXM. Metoda byla rozšířena o alternující dekonvoluci a dále na plně simultánní DCE-DSC odhad. Algoritmus byl testován na umělých a reálných datech. Výsledky analýz ukazují, že navržený dekonvoluční postup zlepšuje přesnost odhadu jak DCE, tak i DSC parametrů v porovnání se sekvenčním odhadem a zvyšuje tak významně potenciál a spolehlivost DCE a DSC metod.This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI.

Design of Flow, Temperature and Pressure Measuring System

Tato diplomová práce se zabývá řešením systému pro měření neelektrických veličin - teploty, tlaku a průtoku. Měřen je tlak v levé komoře izolovaného králičího srdce. Dále je měřen průtok a teplota perfuzního roztoku pro srdce. Práce se také zabývá tvorbou programu pro řídící mikrokontrolér a pro LabVIEW, které je používáno pro zobrazování a exportování dat. Text obsahuje i technickou dokumentaci pro výrobu přípravku.This master’s thesis contains complete design of the complex measuring system for temperature, pressure and flow. Objects of measuring are pressure in rabbit’s heart ventricle, flow of the saline through the heart and the temperatures of physiological solution. Work is interested in programming of microcontroller and program for LabVIEW environment, which is used to view and export relevant data related to measuring. Text also contains technical documentation of functional sample of measuring system.

Design of Hearing Aids in LabVIEW

Práce obsahuje blokové schéma sluchadla pro podporu sluchu, anatomický popis sluchového orgánu člověka a fyzikální popis některých vybraných veličin, týkajících se zvuku a sluchu. Jsou rozebrány vyšetřovací metody pro určení stupně poškození sluchu a několik typů algoritmů pro kompenzaci degenerace či poruchy sluchu. Dále je vytvořen interaktivní program sluchadla, který má implementovány různé rovnice pro ekvalizaci zvuku.This thesis contains the block diagram of hearing aid, anatomy description of human hearing system and description of most important physical values in this problematics of hearing and sound. There are analyzed several types of hearing tests for diagnosis of the hearing loss level and some types of algorithms, which fit the frequency characteristic of patient's hearing loss too. Further this thesis contains interactive program of hearing aid, which has implemented equations for sound equalization.

Advanced Methods of Perfusion Analysis in MRI

This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI

Effects of motion correction, sampling rate and parametric modelling in dynamic contrast enhanced MRI of the temporomandibular joint in children affected with juvenile idiopathic arthritis

The temporomandibular joint (TMJ) is typically involved in 45–87% of children with Juvenile Idiopathic Arthritis (JIA). Accurate diagnosis of JIA is difficult as various clinical tests, including MRI, disagree. The purpose of this study is to optimize the methodological aspects of Dynamic Contrast Enhanced (DCE) MRI of the TMJ in children. In this cross-sectional study, including data from 73 JIA affected children, aged 6–15 years, effects of motion correction, sampling rate and parametric modelling on DCE-MRI data is investigated. Consensus among three radiologists determined the regions of interest. Quantitative perfusion parameters were estimated using four perfusion models; the Adiabatic Approximation to Tissue Homogeneity (AATH), Distributed Capillary Adiabatic Tissue Homogeneity (DCATH), Gamma Capillary Transit Time (GCTT) and Two Compartment Exchange (2CXM) models. Effects of motion correction were evaluated by a sum of least squares between corrected raw data and the GCTT model. The effect of systematically down sampling the raw data was tested. The sum of least squares was computed across all pharmacokinetic models. Relative difference perfusion parameters between the left and right TMJ were used for an unsupervised k-means based stratification of the data based on a principal component analysis, as well as for a supervised random forest classification. Diagnostic sensitivity and specificity were computed relative to structural image scorings. Paired sample t-tests, as well as ANOVA tests, were used (significant threshold: p < 0.05) with Tukeys post hoc test. High-level elastic motion correction provides the best least square fit to the GCTT model (percental improvement: 72–84%). A 4 s sampling rate captures more of the potentially disease relevant signal variations. The various parametric models all leave comparable residues (relative standard deviation: 3.4%). In further evaluation of DCE-MRI as a potential diagnostic tool for JIA a high-level elastic motion correction scheme should be adopted, with a sampling rate of at least 4 s. Results suggest that DCE-MRI data can be a valuable part in JIA diagnostics in the TMJ

Effects of motion correction, sampling rate and parametric modelling in dynamic contrast enhanced MRI of the temporomandibular joint in children affected with juvenile idiopathic arthritis

The temporomandibular joint (TMJ) is typically involved in 45–87% of children with Juvenile Idiopathic Arthritis (JIA). Accurate diagnosis of JIA is difficult as various clinical tests, including MRI, disagree. The purpose of this study is to optimize the methodological aspects of Dynamic Contrast Enhanced (DCE) MRI of the TMJ in children. In this cross-sectional study, including data from 73 JIA affected children, aged 6–15 years, effects of motion correction, sampling rate and parametric modelling on DCE-MRI data is investigated. Consensus among three radiologists determined the regions of interest. Quantitative perfusion parameters were estimated using four perfusion models; the Adiabatic Approximation to Tissue Homogeneity (AATH), Distributed Capillary Adiabatic Tissue Homogeneity (DCATH), Gamma Capillary Transit Time (GCTT) and Two Compartment Exchange (2CXM) models. Effects of motion correction were evaluated by a sum of least squares between corrected raw data and the GCTT model. The effect of systematically down sampling the raw data was tested. The sum of least squares was computed across all pharmacokinetic models. Relative difference perfusion parameters between the left and right TMJ were used for an unsupervised k-means based stratification of the data based on a principal component analysis, as well as for a supervised random forest classification. Diagnostic sensitivity and specificity were computed relative to structural image scorings. Paired sample t-tests, as well as ANOVA tests, were used (significant threshold: p < 0.05) with Tukeys post hoc test. High-level elastic motion correction provides the best least square fit to the GCTT model (percental improvement: 72–84%). A 4 s sampling rate captures more of the potentially disease relevant signal variations. The various parametric models all leave comparable residues (relative standard deviation: 3.4%). In further evaluation of DCE-MRI as a potential diagnostic tool for JIA a high-level elastic motion correction scheme should be adopted, with a sampling rate of at least 4 s. Results suggest that DCE-MRI data can be a valuable part in JIA diagnostics in the TMJ

Time-Efficient Perfusion Imaging Using DCE- and DSC-MRI

Dynamic contrast enhanced MRI (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI) are perfusion imaging techniques used mainly for clinical and preclinical measurement of vessel permeability and capillary blood flow, respectively. It is advantageous to apply both methods to exploit their complementary information about the perfusion status of the tissue. We propose a novel acquisition method that combines advantages of the current simultaneous and sequential acquisition. The proposed method consists of a DCE-MRI acquisition interrupted by DSC-MRI acquisition. A new method for processing of the DCE-MRI data is proposed which takes the interleaved acquisition into account. Analysis of both the DCE- and DSC-MRI data is reformulated so that they are approximated by the same pharmacokinetic model (constrained distributed capillary adiabatic tissue homogeneity model). This provides a straightforward evaluation of the methodology as some of the estimated DCE- and DSC-MRI perfusion parameters should be identical. Evaluation on synthetic data showed an acceptable precision and no apparent bias introduced by the interleaved character of the DCE-MRI acquisition. Intravascular perfusion parameters obtained from clinical glioma data showed a fairly high correlation of blood flow estimates from DCE- and DSC-MRI, however, an unknown scaling factor was still present mainly because of the tissue-specific r2*$r_2^*$ relaxivity. The results show validity of the proposed acquisition method. They also indicate that simultaneous processing of both DCE- and DSC-MRI data with joint estimation of some perfusion parameters (included in both DCE- and DSC-MRI) might be possible to increase the reliability of the DCE- and DSC-MRI methods alone

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge

PURPOSE: has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize measurement. METHODS: A framework was created to evaluate values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants\u27 values, the applied software, and a standard operating procedure. These were evaluated using the proposed score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge

purpose: Ktrans$${K}^{\mathrm{trans}}$$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for Ktrans$${K}^{\mathrm{trans}}$$ quantification are standardized. the ISMRM open science initiative for perfusion imaging-dynamic contrast-enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize Ktrans$${K}^{\mathrm{trans}}$$ measurement. methods: a framework was created to evaluate Ktrans$${K}^{\mathrm{trans}}$$ values produced by DCE-MRI analysis pipelines to enable benchmarking. the perfusion MRI community was invited to apply their pipelines for Ktrans$${K}^{\mathrm{trans}}$$ quantification in glioblastoma from clinical and synthetic patients. submissions were required to include the entrants' Ktrans$${K}^{\mathrm{trans}}$$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIPIgold$$\mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}}$$ score defined with accuracy, repeatability, and reproducibility components. results: across the 10 received submissions, the OSIPIgold$$\mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}}$$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). manual arterial input function selection markedly affected the reproducibility and showed greater variability in Ktrans$${K}^{\mathrm{trans}}$$ analysis than automated methods. furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. conclusions: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within Ktrans$${K}^{\mathrm{trans}}$$ estimation, providing a framework for ongoing benchmarking against the scores presented. through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology