TY - JOUR
T1 - Structural gray matter alterations in glioblastoma and high-grade glioma - A potential biomarker of survival
AU - Lamichhane, Bidhan
AU - Luckett, Patrick H.
AU - Dierker, Donna
AU - Yun Park, Ki
AU - Burton, Harold
AU - Olufawo, Michael
AU - Trevino, Gabriel
AU - Lee, John
AU - Daniel, Andy G.S.
AU - Hacker, Carl D.
AU - Marcus, Daniel S.
AU - Shimony, Joshua S.
AU - Leuthardt, Eric C.
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Background: Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients. Methods: We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients' associated changes in CT as a potential biomarker of overall survival. Results: Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients' cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%. Conclusions: These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients.
AB - Background: Patients with glioblastoma (GBM) and high-grade glioma (HGG, World Health Organization [WHO] grade IV glioma) have a poor prognosis. Consequently, there is an unmet clinical need for accessible and noninvasively acquired predictive biomarkers of overall survival in patients. This study evaluated morphological changes in the brain separated from the tumor invasion site (ie, contralateral hemisphere). Specifically, we examined the prognostic value of widespread alterations of cortical thickness (CT) in GBM/HGG patients. Methods: We used FreeSurfer, applied with high-resolution T1-weighted MRI, to examine CT, evaluated prior to standard treatment with surgery and chemoradiation in patients (GBM/HGG, N = 162, mean age 61.3 years) and 127 healthy controls (HC; 61.9 years mean age). We then compared CT in patients to HC and studied patients' associated changes in CT as a potential biomarker of overall survival. Results: Compared to HC cases, patients had thinner gray matter in the contralesional hemisphere at the time of tumor diagnosis. patients had significant cortical thinning in parietal, temporal, and occipital lobes. Fourteen cortical parcels showed reduced CT, whereas in 5, it was thicker in patients' cases. Notably, CT in the contralesional hemisphere, various lobes, and parcels was predictive of overall survival. A machine learning classification algorithm showed that CT could differentiate short- and long-term survival patients with an accuracy of 83.3%. Conclusions: These findings identify previously unnoticed structural changes in the cortex located in the hemisphere contralateral to the primary tumor mass. Observed changes in CT may have prognostic value, which could influence care and treatment planning for individual patients.
KW - biomarker of GBM and HGG
KW - brain tumor
KW - cortical thickness
KW - glioblastoma and high-grade glioma
KW - overall survival
UR - http://www.scopus.com/inward/record.url?scp=85160919782&partnerID=8YFLogxK
U2 - 10.1093/noajnl/vdad034
DO - 10.1093/noajnl/vdad034
M3 - Article
C2 - 37152811
AN - SCOPUS:85160919782
SN - 2632-2498
VL - 5
JO - Neuro-Oncology Advances
JF - Neuro-Oncology Advances
IS - 1
M1 - vdad034
ER -