TY - JOUR A1 - Schadt, Fabian A1 - Israel, Ina A1 - Samnick, Samuel T1 - Development and Validation of a Semi-Automated, Preclinical, MRI-Template Based PET Image Data Analysis Tool for Rodents JF - Frontiers in Neuroinformatics N2 - AimIn PET imaging, the different types of radiotracers and accumulations, as well as the diversity of disease patterns, make the analysis of molecular imaging data acquired in vivo challenging. Here, we evaluate and validate a semi-automated MRI template-based data analysis tool that allows preclinical PET images to be aligned to a self-created PET template. Based on the user-defined volume-of-interest (VOI), image data can then be evaluated using three different semi-quantitative parameters: normalized activity, standardized uptake value, and uptake ratio. Materials and MethodsThe nuclear medicine Data Processing Analysis tool (NU_DPA) was implemented in Matlab. Testing and validation of the tool was performed using two types of radiotracers in different kinds of stroke-related brain diseases in rat models. The radiotracers used are 2-[\(^{18}\)F]fluoro-2-deoxyglucose ([\(^{18}\)F]FDG), a metabol\(^{68}\)Ga]Ga-Fucoidan, a target-selective radioligand specifically binding to p-selectin. After manual image import, the NU_DPA tool automatically creates an averaged PET template out of the acquired PET images, to which all PET images are then aligned onto. The added MRI template-based information, resized to the lower PET resolution, defines the VOI and also allows a precise subdivision of the VOI into individual sub-regions. The aligned PET images can then be evaluated semi-quantitatively for all regions defined in the MRI atlas. In addition, a statistical analysis and evaluation of the semi-quantitative parameters can then be performed in the NU_DPA tool. ResultsUsing ischemic stroke data in Wistar rats as an example, the statistical analysis of the tool should be demonstrated. In this [\(^{18}\)F]FDG-PET experiment, three different experimental states were compared: healthy control state, ischemic stroke without electrical stimulation, ischemic stroke with electrical stimulation. Thereby, statistical data evaluation using the NU_DPA tool showed that the glucose metabolism in a photothrombotic lesion can be influenced by electrical stimulation. ConclusionOur NU_DPA tool allows a very flexible data evaluation of small animal PET data in vivo including statistical data evaluation. Using the radiotracers [\(^{18}\)F]FDG and [\(^{68}\)Ga]Ga-Fucoidan, it was shown that the semi-automatic MRI-template based data analysis of the NU_DPA tool is potentially suitable for both metabolic radiotracers as well as target-selective radiotracers. KW - data analysis KW - Matlab KW - MRI KW - PET KW - positron emission tomography KW - preclinical imaging Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-240289 SN - 1662-5196 VL - 15 ER - TY - THES A1 - Schadt, Fabian T1 - Entwicklung und erste Validierung eines innovativen Analysen-Tools für präklinische Bewertungen von PET-Radiopharmazeutika zur \(in\) \(vivo\) Untersuchungen neurologischer Erkrankungen T1 - Development and initial validation of an innovative analytical tool for preclinical evaluations of PET radiopharmaceuticals for \(in\) \(vivo\) investigations of neurological disease N2 - Die präklinische Forschung stellt den ersten wichtigen Meilenstein in der Klärung und Untersuchung klinisch-relevanter Erkrankungen dar. Darüber hinaus unterstützt die präklinische Forschung erheblich die Entwicklung von Therapien. Die Kleintier-Positronenemissionstomographie (µ-PET) spielt dabei eine wichtige Rolle, da sie in der Lage ist, funktionelle, physiologische und biochemische Prozesse in vivo darzustellen und zu quantifizieren. Trotz diverser etablierter PET-Datenauswertungs-Programme bleibt die Analyse von in vivo akquirierten Bilddaten aufgrund der Vielzahl an medizinischen Fragestellungen, der Komplexität der Krankheitsbilder, sowie der Etablierung neuer Radiotracer weiterhin eine große Herausforderung in der Medizin. Ziel dieser Doktorarbeit ist es daher, ein geeignetes, brauchbares Auswertungstool für eine einfache und effiziente Analyse von akquirierten µ-PET-Daten zu entwickeln und zu etablieren, welches das Spektrum bereits vorhandener Programme erweitert. Das entwickelte nuklearmedizinische Datenverarbeitungs-Analyseprogramm (engl. nuclear medicine data processing analysis tool, NU_DPA) wurde in Matlab implementiert und anhand dreier präklinischer Versuchs- bzw. Testreihen erprobt und etabliert. Bei den Datenreihen handelt es sich um µ-PET-Datensätze verschiedener Schlaganfall-Rattenhirnmodelle unter Verwendung folgender Radiotracer. Zum einen die im Gehirn homogen akkumulierende 2-[18F]Fluor-2-desoxy-glukose ([18F]FDG) zum anderen das spezifisch an P-Selektin anreichernde [68Ga]Fucoidan. Das NU_DPA umfasst die automatische Selektion des Zielvolumens (volume-of-interest, VOI) aus dem vollständigen PET-Bild und die anschließende Ausrichtung des VOI mit Hilfe eines PET-Templates (gemittelter PET-Datensatz). Dieses PET Template wird aus den eigenen akquirierten PET-Daten erstellt. Durch das Einbinden eines geeigneten anatomischen MRT-Atlas‘ (anpassbar) können die ausgerichteten PET-Daten einzelnen, Atlas-spezifischen Teilregionen zugeordnet werden. Eine solche Subklassifikation des VOI erlaubt eine genauere Betrachtung und Auswertung der Radiotracer-Akkumulation. Des Weiteren bietet NU_DPA die Möglichkeit einer semiquantitativen Auswertung der PET-Bilddaten anhand von drei unterschiedlichen Parametern, der normalisierten Aktivität, dem Standardized Uptake Value und der Uptake Ratio. Durch die Matlab-integrierten Statistik-Algorithmen ist zusätzlich eine Möglichkeit der statistischen Auswertung der zuvor berechneten Parameter gegeben. Das NU_DPA-Programm stellt somit ein semi-automatisiertes Datenauswertungs-Programm dar, das sowohl die Registrierung als auch die semiquantitative Auswertung von PET-Bilddaten innerhalb einer Versuchsreihe ermöglicht und bereits erfolgreich für die Radiotracer [18F]FDG und [68Ga]Fucoidan in Tiermodellen getestet wurde. Nach derzeitigem Kenntnisstand ist kein Datenauswertungs-Programm bekannt, das PET-Bilddaten unter Verwendung des hinzugefügten Atlas‘ semi-automatisiert analysieren kann und potenziell für homogene und Target-spezifisch akkumulierende Radiotracer geeignet ist. N2 - Preclinical research represents the first important milestone in the clarification and investigation of clinically relevant diseases. In addition, preclinical research significantly supports the development of therapies. Small animal positron emission tomography (µ-PET) plays an important role in this context, as it is able to image and quantify functional, physiological and biochemical processes in vivo. Despite various established µ-PET data analysis programs, the analysis of in vivo acquired image data remains a major challenge in medicine due to the multitude of medical questions, the complexity of disease patterns, and the establishment of new radiotracers. Therefore, the aim of this PhD thesis is to develop and establish a suitable, usable evaluation tool for a simple and efficient analysis of acquired µ-PET data, which extends the spectrum of already existing programs. The developed nuclear medicine data processing analysis tool (NU_DPA) was implemented in Matlab and tested and established on the basis of three preclinical experimental or test series. The data series are µ-PET datasets of different stroke rat brain models using the following radiotracers: 2-[18F]fluoro-2-deoxy-glucose ([18F]FDG), which accumulates homogeneously in the brain and [68Ga]fucoidan, which specifically accumulates at p-selectin. The NU_DPA involves automatic segmentation of a volume-of-interest (VOI) from the full PET image and the subsequent alignment of the VOI using a PET template (averaged PET dataset). This PET template is created from the own acquired PET data. By embedding a suitable anatomical MR atlas (customizable), the aligned PET data can be assigned to individual atlas-specific sub-regions. Such a sub-classification of the VOI allows a more detailed analysis and evaluation of the radiotracer accumulation. Furthermore, NU_DPA offers the possibility of a semi-quantitative evaluation of the PET image data based on three different parameters, the normalized activity, the standardized uptake value and the uptake ratio. The Matlab-integrated statistical algorithms provide an additional option for statistical evaluation of the previously calculated semi-quantitative parameters. The NU_DPA program thus represents a semi-automatic data evaluation program that enables both the registration and the semi-quantitative evaluation of PET image data within a series of experiments and it has already been successfully tested for the radiotracers [18F]FDG and [68Ga]fucoidan in animal models. To the best of our current knowledge, there is no known data analysis program that can semi-automatically analyze PET image data using the added atlas and is potentially suitable for homogeneous and target-specific accumulating radiotracers. KW - PET KW - Präklinische Bildgebung Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-247499 ER - TY - JOUR A1 - Schadt, Fabian A1 - Israel, Ina A1 - Beez, Alexandra A1 - Alushi, Kastriot A1 - Weiland, Judith A1 - Ernestus, Ralf-Ingo A1 - Westermaier, Thomas A1 - Samnick, Samuel A1 - Lilla, Nadine T1 - Analysis of cerebral glucose metabolism following experimental subarachnoid hemorrhage over 7 days JF - Scientific Reports N2 - Little is known about changes in brain metabolism following SAH, possibly leading towards secondary brain damage. Despite sustained progress in the last decade, analysis of in vivo acquired data still remains challenging. The present interdisciplinary study uses a semi-automated data analysis tool analyzing imaging data independently from the administrated radiotracer. The uptake of 2-[18F]Fluoro-2-deoxy-glucose ([\(^{18}\)F]FDG) was evaluated in different brain regions in 14 male Sprague–Dawley rats, randomized into two groups: (1) SAH induced by the endovascular filament model and (2) sham operated controls. Serial [\(^{18}\)F]FDG-PET measurements were carried out. Quantitative image analysis was performed by uptake ratio using a self-developed MRI-template based data analysis tool. SAH animals showed significantly higher [\(^{18}\)F]FDG accumulation in gray matter, neocortex and olfactory system as compared to animals of the sham group, while white matter and basal forebrain region showed significant reduced tracer accumulation in SAH animals. All significant metabolic changes were visualized from 3 h, over 24 h (day 1), day 4 and day 7 following SAH/sham operation. This [\(^{18}\)F]FDG-PET study provides important insights into glucose metabolism alterations following SAH—for the first time in different brain regions and up to day 7 during course of disease. KW - SAH KW - metabolism KW - brain Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300725 VL - 13 IS - 1 ER -