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In Dynamic Contrast Enhanced MRI there are several steps from the initial signal to obtaining the pharmacokinetic parameters for tumor characterization. The aim of this work was to validate the steps in the flow of data focusing on T1-mapping, Contrast Agent (CA)-quantification and the pharmacokinetical (PK) model, using a digital phantom of a head. In the Digital Phantom tissues are assigned necessary values to obtain both a regular and contrast enhanced (using Parker AIF) representation and simulating an SPGR signal. The data analysis was performed in a software called MICE, as well as the Digital Phantom developed at the department of Radiation Sciences at Umeå University. The method of variable flip angles for the T1-mapping was analyzed with respect to SNR and number of flip angles, finding that the median value in each tissue is correct and stable. A "two point" inversion recovery sequence was tested with optimal combination of inversion times for white matter and CSF and obtaining correct T1-values when the inversion times were close to the tissue T1, otherwise with large deviations seen. Three different methods for CA-quantification were analyzed and a large underestimation was found assuming a linearity between signal and CA-concentration mainly for vessels at about 60%, but also for other tissue such as white matter at about 15%, improving when the assumption was removed. Still there was a noticeable underestimation of 30% and 10% and the quantification was improved further, achieving a near perfect agreement with the reference concentration, taking the T2*-effect into account. Applying Kety-model, discarding the vp-term, Ktrans was found to be stable with respect to noise in the tumor rim but ve noticeably underestimated with about 50%. The effect of different bolus arrival time, shifting the AIF required in the PK-model with respect to the CA-concentration, was tested with values up to 5 s, obtaining up to about 5% difference in Ktrans as well as the effect of a vascular transport function obtained by the means of an effective mean transit time up to 5 s and up to about 5% difference in Ktrans.

Magnetic resonance imaging (MRI) of the liver is an important non-invasive tool for diagnosing liver disease. A key application is dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). With the use of the hepatocyte specific contrast agent (CA) Gd-EOB-DTPA it is now possible to evaluate the liver function. Beyond traditional qualitative evaluation of the DCE-MRI images, parametric quantitative techniques are on the rise which yields more objective evaluations. Systems biology is a gradually expanding field using mathematical modeling to gain deeper mechanistic understanding in complex biological systems. The aim of this thesis to combine these two fields in order to derive a physiologically accurate minimal whole body model that can be used to quantitatively evaluate liver function using clinical DCE-MRI examinations.  The work is based on two previously published sources of data using Gd-EOB-DTPA in healthy humans; i) a region of interest analysis of the liver using DCE-MRI ii) a pre-clinical evaluation of the contrast agent using blood sampling.  The modeling framework consists of a system of ordinary differential equations for the contrast agent dynamics and non-linear models for conversion of contrast agent concentrations to relaxivity values in the DCE-MRI image volumes. Using a χ2-test I have shown that the model, with high probability, can fit the experimental data for doses up to twenty times the clinically used one, using the same parameters for all doses. The results also show that some of the parameters governing the hepatocyte flux of CA can be numerically identifiable. Future applications with the model might be as a basis for regional liver function assessment. This can lead to disease diagnosis and progression evaluation for physicians as well as support for surgeons planning liver resection.

Tato dizertační práce představuje metodu zobrazování perfúze magnetickou rezonancí, jež je výkonným nástrojem v diagnostice, především v onkologii. Po ukončení sběru časové sekvence T1-váhovaných obrazů zaznamenávajících distribuci kontrastní látky v těle začíná fáze zpracování dat, která je předmětem této dizertace. Je zde představen teoretický základ fyziologických modelů a modelů akvizice pomocí magnetické rezonance a celý řetězec potřebný k vytvoření obrazů odhadu parametrů perfúze a mikrocirkulace v tkáni. Tato dizertační práce je souborem uveřejněných prací autora přispívajícím k rozvoji metodologie perfúzního zobrazování a zmíněného potřebného teoretického rozboru.

<p> </p><p>Acquired data from dynamic contrast enhanced MRI measurements can be used to non-invasively assess tumour vascular characteristics through pharmacokinetic modelling. The modelling requires an arterial input function which is the concentration of contrast agent in the blood reaching the volume of interest as a function of time. The aim of this work is testing and optimizing a turboFLASH sequence to appraise its suitability for measuring the arterial input function by measuring phase.</p><p>Contrast concentration measurements in a phantom were done with both phase and relaxivity techniques. The results were compared to simulations of the experiment conditions to compare the conformance. The results using the phase technique were promising, and the method was carried on to in-vivo testing. The in-vivo data displayed a large signal loss which motivated a new phantom experiment to examine the cause of this signal reduction. Dynamic measurements were made in a phantom with pulsatile flow to mimic a blood vessel with a somewhat modified turboFLASH sequence. The conclusions drawn from analyzing the data were used to further improve the sequence and this modified turboFLASH sequence was tested in an in-vivo experiment. The obtained concentration curve showed significant improvement and was deemed to be a good representation of the true blood concentration.</p><p>The conclusion is that phase measurements can be recommended over relaxivity based measurements. This recommendation holds for using a slice selective saturation recovery turboFLASH sequence and measuring the arterial input function in the neck. Other areas of application need more thorough testing.</p><p> </p>

MRI is a versatile tool for systematically assessing anatomical and functional changes in small animal models of human disease. Its noninvasive nature makes MRI an ideal candidate for longitudinal evaluation of disease progression in mice; however achieving the desired level of statistical power can be expensive in terms of imaging time. This is particularly true for cancer studies, where dynamic contrast-enhanced (DCE-) MRI, which involves the repeated acquisition of anatomical images before, during, and after the injection of a paramagnetic contrast agent, is used to monitor changes in tumor vasculature. A means of reducing the overall time required to scan multiple cohorts of animals in distinct experimental groups is therefore highly desirable. Multiple-mouse MRI, in which several animals are simultaneously scanned in a common MRI system, has been successfully used to improve study throughput. However, to best utilize the next generation of small-animal MRI systems that will be equipped with an increased number of receive channels, a paradigm shift from simultaneously scanning as many animals as possible to scanning a more manageable number, at a faster rate, must be considered. Given a small-animal MRI system with 16 available receive channels, the simulations described in this work explore the tradeoffs between the number of animals scanned at once and the number of array elements dedicated to each animal for maximizing throughput. An array system consisting of 15 receive and 5 transmit coils allows throughput-optimized acceleration of a DCE-MRI protocol by a combination of multi-animal and parallel imaging techniques. The array system was designed and fabricated for use on a 7.0-T / 30-cm MRI system, and tested for high-throughput imaging performance in phantoms. Results indicate that up to a nine-fold throughput improvement is possible without sacrificing image quality compared to standard single-animal imaging hardware. A DCE-MRI study throughput improvement of just over six times that achieved with conventional single-mouse imaging was realized. This system will lower the barriers for DCE-MRI in preclinical research and enable more thorough sampling of disease pathologies that progress rapidly over time. / text

Acquired data from dynamic contrast enhanced MRI measurements can be used to non-invasively assess tumour vascular characteristics through pharmacokinetic modelling. The modelling requires an arterial input function which is the concentration of contrast agent in the blood reaching the volume of interest as a function of time. The aim of this work is testing and optimizing a turboFLASH sequence to appraise its suitability for measuring the arterial input function by measuring phase. Contrast concentration measurements in a phantom were done with both phase and relaxivity techniques. The results were compared to simulations of the experiment conditions to compare the conformance. The results using the phase technique were promising, and the method was carried on to in-vivo testing. The in-vivo data displayed a large signal loss which motivated a new phantom experiment to examine the cause of this signal reduction. Dynamic measurements were made in a phantom with pulsatile flow to mimic a blood vessel with a somewhat modified turboFLASH sequence. The conclusions drawn from analyzing the data were used to further improve the sequence and this modified turboFLASH sequence was tested in an in-vivo experiment. The obtained concentration curve showed significant improvement and was deemed to be a good representation of the true blood concentration. The conclusion is that phase measurements can be recommended over relaxivity based measurements. This recommendation holds for using a slice selective saturation recovery turboFLASH sequence and measuring the arterial input function in the neck. Other areas of application need more thorough testing.

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