Dynamical graph networks may aid in phenotyping prognostically different brain tumor types

Meyer‐Baese, Anke; Juetten, Kerstin; Meyer-Baese, Uwe; Stadlbauer, Andreas; Kinfe, Thomas M.; Na, Chuh‐Hyoun

doi:10.1117/12.2645973

Cited by 1 publication

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References 5 publications

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“…On the other hand, failures of nodes on brain networks can become more frequent and severe and are associated with dysfunction and neurobiological disorder such as dementia or gliomas. 1,2 The controllability of a network decreases due to these failures, which leads to an increase in the number of drivers needed to control the network.…”

Section: Introductionmentioning

confidence: 99%

Controllability and robustness of functional and structural connectomic networks in dementia

Meyer-Baese,

Mueller,

Moon

et al. 2024

Medical Imaging 2024: Clinical and Biomedical Imaging

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Brain connectivity is usually analyzed based on graph theory and pinning control theory. Previous studies suggested that the topological properties of structural and functional networks for brain networks may be altered in association with neurodegnerative diseases. To better understand and characterize these alterations, we introduce a new approach -robustness of network controllability to evaluate network robustness, and identify the critical nodes, whose removals maximally destroys the network's functionality. These alterations are due to external or internal changes in the network. Understanding and describing these interactions at the level of large-scale brain circuitry may be a significant step towards unraveling dementia disease evolution. In this study, we analyze structural and functional brain networks for healthy controls, MCI and AD patients such that we reveal the connection between network robustness and architecture and the differences between patients' groups. We determine the critical and driver nodes of these networks as the key components for robustness of network controllability.Our results suggest that healthy controls for both functional and structural connectivity have more critical nodes than AD and MCI networks, and that these critical nodes appear clustered in almost all networks. Our findings provide useful information for determining disease evolution in dementia under the aspects of controllability and robustness.

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Section: Introductionmentioning

confidence: 99%