Comparative evaluation of graph construction methods for individual brain metabolic network from FDG-PET images: an ADNI study in healthy subjects.
Purpose: Connectivity analyses of fluorodeoxyglucose positron emission tomography (FDG-PET) static images provide a valuable means of investigating brain network organization by capturing metabolic activity at rest. Graph theory is emergently applied to model these networks at individual level; howe...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 53; no. 2; pp. 1139 - 1155 |
|---|---|
| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jan2026
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191135959&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191135959 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Jan2026 vid: 53 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 191135959 187181679 10.1007/s00259-025-07462-1 191135959 ppf: 1139 ppct: 16 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Comparative evaluation of graph construction methods for individual brain metabolic network from FDG-PET images: an ADNI study in healthy subjects. aug: au: Tuan, Pham Minh Horowitz, Tatiana Adel, Mouloud Wojak, Julien Trung, Nguyen Linh Guedj, Eric affil: https://ror.org/03br1wy20 CNRS, Institut Fresnel, Aix-Marseille université, Marseille, France sug: ab: Purpose: Connectivity analyses of fluorodeoxyglucose positron emission tomography (FDG-PET) static images provide a valuable means of investigating brain network organization by capturing metabolic activity at rest. Graph theory is emergently applied to model these networks at individual level; however, the choice of graph construction method can significantly impact analytical outcomes. Methods: In this study, we systematically evaluate and compare methods for building individual graphs from FDG-PET images in healthy control subjects. Specifically, we assess five methods, categorized into mean-based graphs and probability density function (PDF)-based graphs, using two criteria: structural similarity between individual and group-level graphs, and their hub topology structure analysis. Results: Our findings indicate that the Effect Size-based (ES) method best preserves group-level graph structure, achieving 98.9% similarity for the averaged graph while also maintaining around 84% similarity for individual graphs. Among PDF-based approaches, the Wasserstein (WA) method, with its adaptability in PDF-based settings, provides the highest similarity across both averaged (82.5%) and individual (79.1%) graphs, with its adaptive in PDF-settings, making it the most effective for multi-scale network analysis. Meanwhile, Dynamic Time Warping (DTW) captures the highest individual variability, as reflected by its largest variation among individual graphs (11.5%). Conclusion: This analysis highlights the unique strengths and limitations of each method, emphasizing the critical importance of careful method selection tailored to specific research objectives. Additionally, our study suggests a framework for selecting the appropriate methods, with implications for further both research and clinical applications. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|