Brain connectivity of early-phase amyloid imaging in Alzheimer’s disease

Diplôme Master Brain connectivity of early-phase amyloid imaging in Alzheimer’s disease eng 2024 author Espinosa Ricardo David 874674 director Peretti Debora 975652 Département de radiologie et informatique médicale (RADIO) Introduction: Alzheimer’s disease (AD) is pathologically characterized by deposits of amyloid-b plaques and tau protein in the brain, as well as a characteristic neurodegeneration pattern in the cortex. Current research suggests that the brain can be regarded as a functional network of different regions forming a connectome and neurodegenerative processes, as AD, can affect it. The Default Mode Network (DMN) is particularly vulnerable to AD, and its alterations can lead to the cognitive deficits characteristic of this pathology. Positron emission tomography (PET) imaging using 18F-fluorodeoxyglucose (18F-FDG), or the first minutes after administration of radiotracers targeting amyloid pathology (early-phase) can reliably assess AD characteristic patterns of neurodegeneration. Florbetapir (FBP) and Flutemetamol (FMM) are radiotracers that target cerebral amyloid deposits. The ability of early-phase amyloid imaging to assess brain connectivity has not been explored yet. The aim of this study was to assess differences in connectivity measured with 18F-FDG and early-phase amyloid imaging. Methods: A cohort of 141 subjects from the Geneva Memory Clinic underwent 18F-FDG-PET and amyloid-PET within 12 months. Subjects were classified as Amyloid positive (A+) and Amyloid negative (A-) based on a centiloid scale threshold (12). Average uptake for Automated Anatomical Labelling atlas 3 brain regions were loaded into a graph theory software, a weighted connectivity matrix (Pearson correlation) was generated, and connectivity parameters were calculated for both 18F-FDG and early-phase images from FBP or FMM (eFBP and eFMM, respectively). Paired t-tests between networks generated by different images were performed after bootstrapping (1000 permutations). Results: The mean age (SD) for A+ was 72.15 (5.56) and for A- 70.8 (8.29), 53.2% of the subjects were women. Changes in connectivity patterns between A- and A+ subjects were observed in the same regions for 18F-FDG and early-phase. Early-phase connectivity matrices exhibit, in general, a lower hyperconnectivity pattern compared to 18F-FDG, both for the whole brain and within the DMN. Connectivity differences were mainly observed between eFMM and 18F-FDG in A- subjects, with similar results for DMN. Assessment of modularity and average degree showed significant differences between the A- and A+ groups in eFMM (p = 0.01 for both). For differences in connectivity between eFBP and 18F-FDG, A+ subjects more frequently showed significant differences, although DMN did not always reflect these same differences. Conclusion: Connectivity matrices derived early-phase amyloid images successfully allowed the detection of the AD changes observed in 18F-FDG PET, with less marked differences for eFMM in terms of connectivity parameters. The eFMM also showed an advantage in distinguishing connectivity profiles between the two groups of subjects, while revealing a similarity with the default mode network (DMN) for the whole brain. Dewey 616.8 Dewey 616.0757 Maîtrise universitaire en neurosciences 62 Département de radiologie et informatique médicale 227 61 Département des neurosciences cliniques 226 false 1222 Laboratoire de neuroimagerie et de traceurs moléculaires innovants 984 dad2029a-7de2-45c3-842e-88727b2d2a0a Master thesis Restricted Master_Thesis_Ricardo.pdf 28673642 application/pdf 0e87ab88079082e11ede504973a8b657cc7b0f7e4021b2c2667f8bea84c20b54 restrictedAccess Faculté de médecine / Section de médecine clinique / Département de radiologie et informatique médicale Faculté de médecine / Section de médecine clinique / Département des neurosciences cliniques

Title	Published in	Access level	OA Policy	Year	Views	Downloads

Brain connectivity of early-phase amyloid imaging in Alzheimer’s disease				2024	28	1

Archive ouverte UNIGE

Espinosa, Ricardo David

account_balance Affiliation entities

Research groups

Affiliation entities