Vpliv kakovosti in števila slik FDG-PET možganov na obliko značilnega presnovnega vzorca pri Alzheimerjevi bolezni

Tomanič, Tadej (author), Simončič, Urban (mentor), Trošt, Maja (comentor)

Demenca je sindrom, pri katerem pride do motenj višjih živčnih funkcij, ki so tako hude, da vplivajo na bolnikove vsakodnevne dejavnosti. Pogosto je posledica Alzheimerjeve bolezni (ang. $\textit{Alzheimer's disease}$, AD), ki je najbolj razširjena nevrodegenerativna bolezen možganov. Zaradi podobnih kliničnih znakov predstavljajo nevrodegenerativne bolezni možganov precejšen diagnostični izziv, zato se pojavlja vedno večja potreba po objektivnem biološkem označevalcu, s pomočjo katerega bi lahko prisotnost bolezni potrdili že v začetnih fazah razvoja. Za čim uspešnejšo in natančnejšo postavitev diagnoze se med drugim poslužujemo funkcijskega slikanja možganov s pozitronsko emisijsko tomografijo (ang. $\textit{positron emission tomography}$, PET). Pri slikanju preiskovancu intravenozno apliciramo radiofarmak fluorodeoksiglukozo (ang. $\textit{fluorodeoxyglucose}$, FDG), kemijski analog deoksiglukoze, ki se porazdeli po celem telesu, vključno z možgani. Gostota FDG v možganih je višja v področjih z višjo presnovno aktivnostjo in nižja v področjih z nižjo presnovno aktivnostjo. S kvalitativno analizo slik FDG-PET možganov lahko odkrijemo spremembe v presnovni aktivnosti možganov, ki so posledica Alzheimerjeve bolezni, še preden je vidna atrofija možganov na strukturnih slikah. Z uporabo skalirnega podprofilnega modela, ki temelji na analizi glavnih komponent (ang. $\textit{Scaled Subprofile Model/Principal Component Analysis}$, SSM/PCA), lahko na podlagi slik FDG-PET možganov bolnikov in zdravih kontrolnih preiskovancev identificiramo značilen presnovni možganski vzorec Alzheimerjeve bolezni (ang. $\textit{Alzheimer's disease-related pattern}$, ADRP). Na obliko in klinično uporabnost ADRP vplivajo številni parametri. V tem magistrskem delu raziskujemo učinek tehnične kakovosti in števila slik FDG-PET možganov, ki jih uporabimo pri identifikaciji, na obliko, diagnostično moč in klinično uporabnost ADRP. Pri tem na kratko predstavimo značilnosti Alzheimerjeve bolezni in osnove slikanja s PET ter opišemo celoten postopek izbora in predpriprave slik FDG-PET ter identifikacije in validacije ADRP. V nadaljevanju identificiramo in z različnimi kvalitativnimi ter kvantitativnimi metodami preverimo tri različne ADRP, nakar na osnovi validacije preverimo hipoteze, ki smo si jih zastavili pred pričetkom dela.

• Language: Slovenian
• Keywords: Alzheimerjeva bolezen (AD), FDG-PET, SSM/PCA, ADRP, ADNI
• Work type: Master's thesis/paper
• Typology: 2.09 - Master's Thesis
• Organization: FMF - Faculty of Mathematics and Physics
• Year: 2020
• PID: 20.500.12556/RUL-119598
• COBISS.SI-ID: 49744387
• Publication date in RUL: 10.09.2020

Secondary language

• Language: English
• Title: Effect of quality and number of FDG-PET brain images on the shape of Alzheimer's disease-related metabolic brain pattern

Abstract

Dementia is a syndrome that causes severe disorders of higher brain functions and thus greatly affects patient’s everyday activity. It is often caused by Alzheimer’s disease (AD), a common neurodegenerative brain disease. Due to similar clinical signs the diagnosis of neurodegenerative brain diseases is often challenging. Therefore an objective biomarker is needed to confirm the presence of the disease in its early stages. To improve the diagnosis of neurodegenerative brain diseases positron emission tomography (PET), a functional brain imaging technique, is widely used. Prior to scanning radioactive tracer fluorodeoxyglucose (FDG), a glucose analogue, is intravenously applied to the subject. FDG is then distributed within subject’s body and brain, so that the tracer density is high in the brain areas with high metabolic activity and low in the areas of low metabolic activity. Qualitative analysis of FDG-PET brain images can be used to discover changes in brain metabolic activity caused by AD before they are visible on structural brain images. What is more, by utilising Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) it is possible to derive a characteristic brain metabolic pattern of Alzheimer’s disease (ADRP) from the FDG-PET brain images of AD patients and healthy control participants (CN). There are several parameters affecting the shape and the clinical applicability of ADRP. This thesis explores the effect of both technical quality and number of FDG-PET brain images used in the pattern derivation process on the shape, diagnostic capability and clinical applicability of ADRP. Therefore an overview of AD and PET is presented, followed by a description of image selection and pre-processing. Moreover, the procedures of pattern derivation and validation are described. Then three different ADRPs are derived and validated by employing various qualitative and quantitative statistical methods. Finally, three hypotheses defined early in this thesis are tested by analysing results obtained during pattern validation.

• Keywords: Alzheimer's disease (AD), FDG-PET, SSM/PCA, ADRP, ADNI