FDG-PET-based brain network analysis: a brief review of metabolic connectivity
Abstract Background Over the past decades, the analysis metabolic connectivity patterns has received significant attention in exploring the underlying mechanism of human behaviors, and the neural underpinnings of brain neurological disorders. Brain network can be considered a powerful tool and play...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | EJNMMI Reports |
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| Online Access: | https://doi.org/10.1186/s41824-024-00232-6 |
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| author | Pham Minh Tuan Mouloud Adel Nguyen Linh Trung Tatiana Horowitz Ismail Burak Parlak Eric Guedj |
| author_facet | Pham Minh Tuan Mouloud Adel Nguyen Linh Trung Tatiana Horowitz Ismail Burak Parlak Eric Guedj |
| author_sort | Pham Minh Tuan |
| collection | DOAJ |
| description | Abstract Background Over the past decades, the analysis metabolic connectivity patterns has received significant attention in exploring the underlying mechanism of human behaviors, and the neural underpinnings of brain neurological disorders. Brain network can be considered a powerful tool and play an important role in the analysis and understanding of brain metabolic patterns. With the advantages and emergence of metabolic-based network analysis, this study aims to systematically review how brain properties, under various conditions, can be studied using Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) images and graph theory, as well as applications of this approach. Additionally, this study provides a brief summary of graph metrics and their uses in studying and diagnosing different types of brain disorders using FDG-PET images. Main body In this study, we used several databases in Web of Science including Web of Science Core Collection, MEDLINE to search for related studies from 1980 up to the present, focusing on FDG-PET images and graph theory. From 68 articles that matched our keywords, we selected 28 for a full review in order to find out the most recent findings and trends. Our results reveal that graph theory and its applications in analyzing metabolic connectivity patterns have attracted the attention of researchers since 2015. While most of the studies are focusing on group-level based analysis, there is a growing trend in individual-based network analysis. Although metabolic connectivity can be applied to both neurological and psychiatric disorders, the majority of studies concentrate on neurological disorders, particularly Alzheimer’s Disease and Parkinson’s Disease. Most of the findings focus on changes in brain network topology, including brain segregation and integration. Conclusion This review provides an insight into how graph theory can be used to study metabolic connectivity patterns under various conditions including neurological and psychiatric disorders. |
| format | Article |
| id | doaj-art-ddc6828d86be4731bba4399fbaee6b8f |
| institution | Kabale University |
| issn | 3005-074X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | EJNMMI Reports |
| spelling | doaj-art-ddc6828d86be4731bba4399fbaee6b8f2025-01-26T12:10:16ZengSpringerEJNMMI Reports3005-074X2025-01-019112810.1186/s41824-024-00232-6FDG-PET-based brain network analysis: a brief review of metabolic connectivityPham Minh Tuan0Mouloud Adel1Nguyen Linh Trung2Tatiana Horowitz3Ismail Burak Parlak4Eric Guedj5Fresnel Institute, Aix-Marseille UniversityFresnel Institute, Aix-Marseille UniversityVNU University of Engineering and Technology, Vietnam National UniversityFresnel Institute, Aix-Marseille UniversityDepartment of Computer Engineering, Galatasaray UniversityFresnel Institute, Aix-Marseille UniversityAbstract Background Over the past decades, the analysis metabolic connectivity patterns has received significant attention in exploring the underlying mechanism of human behaviors, and the neural underpinnings of brain neurological disorders. Brain network can be considered a powerful tool and play an important role in the analysis and understanding of brain metabolic patterns. With the advantages and emergence of metabolic-based network analysis, this study aims to systematically review how brain properties, under various conditions, can be studied using Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) images and graph theory, as well as applications of this approach. Additionally, this study provides a brief summary of graph metrics and their uses in studying and diagnosing different types of brain disorders using FDG-PET images. Main body In this study, we used several databases in Web of Science including Web of Science Core Collection, MEDLINE to search for related studies from 1980 up to the present, focusing on FDG-PET images and graph theory. From 68 articles that matched our keywords, we selected 28 for a full review in order to find out the most recent findings and trends. Our results reveal that graph theory and its applications in analyzing metabolic connectivity patterns have attracted the attention of researchers since 2015. While most of the studies are focusing on group-level based analysis, there is a growing trend in individual-based network analysis. Although metabolic connectivity can be applied to both neurological and psychiatric disorders, the majority of studies concentrate on neurological disorders, particularly Alzheimer’s Disease and Parkinson’s Disease. Most of the findings focus on changes in brain network topology, including brain segregation and integration. Conclusion This review provides an insight into how graph theory can be used to study metabolic connectivity patterns under various conditions including neurological and psychiatric disorders.https://doi.org/10.1186/s41824-024-00232-6Fluorodeoxyglucose positron emission tomographyMetabolic connectivityNetwork analysisGraph metricsAlzheimer’s diseaseParkinson’s disease |
| spellingShingle | Pham Minh Tuan Mouloud Adel Nguyen Linh Trung Tatiana Horowitz Ismail Burak Parlak Eric Guedj FDG-PET-based brain network analysis: a brief review of metabolic connectivity EJNMMI Reports Fluorodeoxyglucose positron emission tomography Metabolic connectivity Network analysis Graph metrics Alzheimer’s disease Parkinson’s disease |
| title | FDG-PET-based brain network analysis: a brief review of metabolic connectivity |
| title_full | FDG-PET-based brain network analysis: a brief review of metabolic connectivity |
| title_fullStr | FDG-PET-based brain network analysis: a brief review of metabolic connectivity |
| title_full_unstemmed | FDG-PET-based brain network analysis: a brief review of metabolic connectivity |
| title_short | FDG-PET-based brain network analysis: a brief review of metabolic connectivity |
| title_sort | fdg pet based brain network analysis a brief review of metabolic connectivity |
| topic | Fluorodeoxyglucose positron emission tomography Metabolic connectivity Network analysis Graph metrics Alzheimer’s disease Parkinson’s disease |
| url | https://doi.org/10.1186/s41824-024-00232-6 |
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