The dynamic functional connectivity fingerprint of high-grade gliomas

被引:1
作者
Moretto, Manuela [1 ,2 ]
Silvestri, Erica [1 ,2 ]
Facchini, Silvia [1 ,3 ]
Anglani, Mariagiulia [4 ]
Cecchin, Diego [1 ,5 ]
Corbetta, Maurizio [1 ,3 ,6 ]
Bertoldo, Alessandra [1 ,2 ]
机构
[1] Univ Padua, Padova Neurosci Ctr, Padua, Italy
[2] Univ Padua, Dept Informat Engn, Via G Gradenigo 6-B, I-35131 Padua, Italy
[3] Univ Padua, Dept Neurosci, I-35121 Padua, Italy
[4] Univ Padua, Neuroradiol Unit, I-35121 Padua, Italy
[5] Univ Padua, Nucl Med Unit, I-35121 Padua, Italy
[6] Venetian Inst Mol Med, I-35131 Padua, Italy
关键词
RESTING-STATE FMRI; DEFAULT-MODE NETWORK; BRAIN-TUMORS; SURVIVAL; GLIOBLASTOMA; RESECTION; DIAGNOSIS; ATTENTION;
D O I
10.1038/s41598-023-37478-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.
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页数:13
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