2021
DOI: 10.3389/fneur.2021.642241
|View full text |Cite
|
Sign up to set email alerts
|

Machine Learning Analytics of Resting-State Functional Connectivity Predicts Survival Outcomes of Glioblastoma Multiforme Patients

Abstract: Glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy. Due to its poor prognosis with currently available treatments, there is a pressing need for easily accessible, non-invasive techniques to help inform pre-treatment planning, patient counseling, and improve outcomes. In this study we determined the feasibility of resting-state functional connectivity (rsFC) to classify GBM patients into short-term and long-term survival groups with respect to reported median survival (14.6 months).… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
9
0

Year Published

2022
2022
2023
2023

Publication Types

Select...
7
1
1

Relationship

1
8

Authors

Journals

citations
Cited by 15 publications
(9 citation statements)
references
References 60 publications
0
9
0
Order By: Relevance
“…No prior studies have evaluated T1w MRI -based connectome models of glioma survival. Our T1w MRI connectome model was superior to previously reported fMRI and DTI based connectome models in predicting glioma survival, which have demonstrated AUCs or accuracies of 0.75–0.81 11 , 12 , 46 . T1w MRI has distinct advantages compared to DTI in terms of reliability in constructing brain networks and standardizing pulse sequences across scanner types 47 , 48 .…”
Section: Discussionmentioning
confidence: 56%
“…No prior studies have evaluated T1w MRI -based connectome models of glioma survival. Our T1w MRI connectome model was superior to previously reported fMRI and DTI based connectome models in predicting glioma survival, which have demonstrated AUCs or accuracies of 0.75–0.81 11 , 12 , 46 . T1w MRI has distinct advantages compared to DTI in terms of reliability in constructing brain networks and standardizing pulse sequences across scanner types 47 , 48 .…”
Section: Discussionmentioning
confidence: 56%
“…Recent studies have also shown that intratumoural functional connectivity is prognostic of better survival and cognitive outcomes after surgery (21,38). The relationship between intratumoural functional connectivity and relevant clinical variables (e.g., overall survival, eloquence of tissue, and cognitive outcome) suggests that rs-fMRI could be a useful, noninvasive biomarker to help guide clinical decision making (21,38,39). Future research should help delineate the biological significance of intratumoural functional connectivity to inform the interpretability of BOLD signal in neoplastic tissue.…”
Section: Discussionmentioning
confidence: 99%
“…Indeed, some studies have found that measures of functional connectivity are predictive of clinical outcomes for glioma patients, independent of other known prognostic factors. 8 , 9 , 197 A related MEG study found that elevated oscillatory activity within diffuse gliomas was associated with poorer progression free survival outcomes, even after adjusting for potential confounding variables. 10 The molecular basis for these prognostic imaging markers is currently incompletely understood.…”
Section: Recent Research At the Intersection Of Brain Mapping And Gli...mentioning
confidence: 99%