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Novel Reconstruction and Quantification Methods for Oxygen-17 Magnetic Resonance Imaging at Clinical Field Strengths

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Novel Reconstruction and Quantification Methods for Oxygen-17 Magnetic Resonance Imaging at Clinical Field Strengths Novel Reconstruction and Quantification Methods for Oxygen-17 Magnetic Resonance Imaging at Clinical Field Strengths Inaugural-Dissertation zur Erlangung des Doktorgrades der Fakultät für Mathematik und Physik der Albert-Ludwigs-Universität Freiburg im Breisgau vorgelegt von M.Sc. Dmitry Kurzhunov aus Kasan, Russland Juli 2017 This thesis is dedicated to my beloved parents: to my father, a physicist by profession and vocation, who opened the fascinating world of physics to me, guided me and helped me develop my potentials; and to my mother, who always supported me in my endeavors and motivated me to become happy and successful. Посвящается моим любимым родителям: моему папе, физику по профессии и по призванию, который открыл для меня захватывающий мир физики, а также направлял меня и помогал мне в раскрытии и развитии моего потенциала; и моей маме, которая всегда поддерживала меня в моих начинаниях и мотивировала мои стремления к счастью и успеху. Everybody has a capacity for a happy life Lev Landau Supervisor: Prof. Dr. Michael Bock Referee: Prof. Dr. Günter Reiter Examiners: Prof. Dr. Jens Timmer Prof. Dr. Oskar von der Lühe Examination day 19.09.1989 ABSTRACT Oxygen metabolism, which is altered by many neurodegenerative diseases such as Alzheimer’s disease or Parkinson’s disease and in brain tumor regions, is quantified by the cerebral metabolic rate of oxygen consumption (CMRO2). Positron emission tomography (PET) with the oxygen 15 isotope O is considered the gold standard for CMRO2 mapping in humans; however, it is rarely used due to the short isotope half-life of only 2 min, which requires costly on-site production. An alternative method is a direct dynamic 17O magnetic resonance imaging (MRI) with inhalation of 17 17 17 isotopically enriched O gas. In O MRI, signal changes from H2 O molecules are observed during and after inhalation of 17O gas, and the pharmacokinetic model is applied to quantify 17 CMRO2. CMRO2 measurements with O MRI are challenging due to low natural abundance of 17 * O isotope of 0.037 %, fast effective transversal relaxation (T2 ), and low signal-to-noise ratio (SNR) of 17O magnetic resonance (MR) images. Thus, it was previously only possible at ultra-high field (UHF; B0 ≥ 4 T) MRI systems. The aim of this work is to develop novel reconstruction, 17 quantification, and simulation methods to enable CMRO2 measurement with O MRI in a clini- cal 3 T MRI system. First, a flexible simulation framework with two types of phantoms (analytical brain tumor and numerical brain phantoms) was developed to find optimal imaging parameters such as readout bandwidth, and spatial (훥푥) and temporal (훥푡) resolutions. Optimal acquisition parameters found in the simulations were consistent with those previously used in 17O MRI at UHF. Therefore, 150 ≤ BW≤ 175 Hz/pixel, 8.0 ≤ 훥푥 ≤ 10 mm, and 훥푡 = 60 sec were used in four 17O MRI ex- periments with 17O gas inhalation. In these experiments, a rebreathing circuit which allows for re- inhalation of the stored 17O gas in subsequent inhalation cycles was implemented for efficient usage of rare and expensive 17O gas. To analyze the influence of the different model parameters on the identifiability of CMRO2, a profile likelihood (PL) analysis was performed for different settings of the model parameters. In particular, the 17O enrichment fraction of the inhaled 17O gas, 훼, was investigated assuming con- stant and linearly varying models. Identifiability was analyzed for white matter (WM) and grey matter (GM) brain regions separately, and the dependency on different priors was studied. Prior knowledge about only one 훼-related parameter was sufficient to resolve the CMRO2 non- identifiability, and the CMRO2 values (0.72 – 0.99 µmol/gtissue/min in WM, 1.02 – 1.78 15 µmol/gtissue/min in GM) were in good agreement with the results of O-PET studies. In particu- lar, the proposed advanced quantification model with non-constant α values significantly im- proved model fitting. The profile likelihood analysis showed that CMRO2 can be measured relia- bly in a 17O gas MRI experiment if the 17O enrichment fraction is used as prior information for the model calculations. A new method called DIrect Estimation of 17O ImageS (DIESIS) was suggested to correct for partial volume effects (PVEs), which are present in 17O MR images due low spatial resolution of * 8 to 10 mm and blurring from fast T2 decay of about 2 ms. DIESIS avoids full reconstruction of i Abstract MR images and directly estimates the 17O MR images from the measured data based on parcella- tion (i.e., segmentation of the 3D image to a predefined number of volumes) of the 3D 1H MR image. It is an alternative to conventional Kaiser-Bessel (KB) gridding method, where 17O signal has to be averaged over large brain regions to get the SNR sufficient for CMRO2 quantification 17 by the model fitting of the O signal-time curves. DIESIS provided correction of PVEs: CMRO2 decreased by 6 – 19% in WM and increased by 29 – 46 % in GM compared to KB gridding, thus 15 getting close to the CMRO2 values from O-PET studies. To test the feasibility of pixel-wise CMRO2 quantification (mapping) in a clinical 3 T MRI system, a new iterative reconstruction was proposed, which uses the edge information contained in a co- registered 1H MR image to construct a non-homogeneous anisotropic diffusion (AD) filter. AD- constrained reconstruction of 17O MR images was compared to conventional KB with and with- out Hanning filtering, and to iterative reconstruction with a total variation constraint. AD- constrained reconstruction provided 17O images with improved resolution of fine brain structures both in the numerical brain phantom and in two in vivo data sets of one healthy volunteer, and it resulted in higher SNR and provided CMRO2 maps, which were comparable with maps acquired at 9.4 T. The results of this work show feasibility of 17O MRI in clinical 3 T MRI systems and provide a 17 solid basis for clinical translation of O MRI for non-invasive CMRO2 quantification in tumor patients. ii ZUSAMMENFASSUNG Hirntumore und neurodegenerative Erkrankungen wie z.B. Alzheimer oder Parkinson zeigen einen veränderten Sauerstoffmetabolismus. Die Positronenemissionstomographie (15O-PET) mit dem Sauerstoffisotop 15O stellt den Goldstandard zur ortsaufgelösten Bestimmung der zerebralen 15 Sauerstoffumsatzrate (CMRO2) im Menschen dar. Aufgrund der kurzen Halbwertszeit von O (ca. 2 min) muss das Radiopharmakon vor Ort mit einem Zyklotron produziert werden, so dass die Verwendung von 15O-PET heute nur auf wenige Forschungszentren beschränkt ist. Eine al- ternative Methode zu PET bietet die Magnetresonanztomographie (MRT) mit dem nicht radioak- 17 17 17 tiven Sauerstoffisotop O. Bei der O-MRT werden die Signaländerungen von H2 O detektiert, welches nach der Gabe von angereichertem 17O-Gas im Zuge des Sauerstoffmetabolismus bzw. der oxidativen Phosphorylierung entsteht. Durch Anpassen eines pharmakokinetischen Modells 17 an den H2 O-Signalverlauf erhält man abschließend die CMRO2-Werte. Aufgrund der niedrigen natürlichen Häufigkeit des 17O-Isotops von 0,037% und dessen schneller effektiver transversaler * Relaxation (T2 ) ist das Signal-Rausch-Verhältnis (engl., SNR) klein und somit die Sensitivität der 17O-MRT im Vergleich zur 1H-MRT um fünf Größenordnungen geringer. Deswegen wurde 17O- MRT bisher nur an MR-Tomographen mit ultrahohen Magnetfeldern (B0 ≥ 4 T) durchgeführt. Das Ziel dieser Arbeit ist die Entwicklung eines Simulationsframeworks sowie neuartiger Quanti- fizierungsmethoden und Rekonstruktionsalgorithmen, um CMRO2 verlässlich an einem klini- schen 3 T MR-Tomographen bestimmen zu können. Zur Bestimmung der optimalen Aufnahmebandbreite (BW) sowie der zeitlichen (훥푡) und räumli- chen (훥푥) Auflösung wurde zunächst ein flexibles Simulationsframework entwickelt, bestehend aus zwei unterschiedlichen Phantomtypen (einem analytischen Hirntumorphantom und einem numerischen Hirnphantom). Die optimierten Simulationsparameter stimmten mit den Parame- tern der Ultrahoch-Messungen überein, daher wurden für alle vier durchgeführten 17O- Inhalationsexperimenten die folgenden Parameter gewählt: 150 ≤ BW ≤ 175 Hz/Pixel, 8,0 ≤ 훥푥 ≤ 10 mm und 훥푡 = 60 s, unter Verwendung des entwickelten Rückatemsystems. Um den Einfluss unterschiedlicher Modelparameter auf die Identifizierbarkeit des CMRO2 zu untersuchen, wurde die Profile-Likelihood-Analyse für unterschiedliche Parametereinstellungen durchgeführt, wobei der 17O-Anreicherungsgrad 훼 in zwei unterschiedlichen Modellen als kon- stant bzw. linear-verändert angenommen wurde. In Abhängigkeit unterschiedlichen Vorwissens wurde die Identifizierbarkeit der CMRO2-Bestimmung in grauen (GM) und weißen (WM) Hirn- regionen evaluiert. Es wurde gezeigt, dass Vorwissen von nur einem 훼-abhängigen Parameters notwendig ist, um CMRO2 verlässlich zu bestimmen. Die quantifizierten CMRO2-Raten (0,72 – 0,99 µmol/gtissue/min im WM, 1,02 – 1,78 µmol/gtissue/min im GM) waren in guter Über- einstimmung mit den Ergebnissen von 15O-PET Untersuchungen. Dabei zeigte das Modell die beste Übereinstimmung mit den gemessenen Werten, bei dem ein nichtkonstanter Verlauf von 훼 angenommen wurde. Die Profile-Likelihood-Analyse hat gezeigt, dass der CMRO2 mit Hilfe von 17O-MRT Inhalationsmessungen zuverlässig bestimmt werden kann. iii Zusammenfassung Zur Korrektur von Partialvolumeneffekten in den 17O-MR-Bildern, die aufgrund der geringen * räumlichen Auflösung von 8 bzw. 10 mm und kurzer T2 -Zeiten von ca. 2 ms vorhanden sind, wurde die neuartige Methode DIrect Estimation of
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