Indirect functional connectivity does not predict overall survival in glioblastoma

• Published in: Neurobiology of disease Vol. 196; p. 106521
• Main Authors: Pini, Lorenzo, Lombardi, Giuseppe, Sansone, Giulio, Gaiola, Matteo, Padovan, Marta, Volpin, Francesco, Denaro, Luca, Corbetta, Maurizio, Salvalaggio, Alessandro
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15.06.2024; Elsevier
• Subjects: Adult; Aged; Brain - diagnostic imaging; Brain - physiopathology; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - mortality; Brain Neoplasms - physiopathology; Connectome - methods; Disconnections; Female; Functional imaging; Glioblastoma; Glioblastoma - diagnostic imaging; Glioblastoma - mortality; Glioblastoma - physiopathology; Humans; Magnetic Resonance Imaging - methods; Male; Middle Aged; Nerve Net - diagnostic imaging; Nerve Net - physiopathology; Retrospective Studies; Survival prediction; Disconnections; Survival prediction; Glioblastoma; Functional imaging

Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous...