Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
Αναπαύσεως 5 Άγιος Νικόλαος
Κρήτη 72100
00302841026182
00306932607174
alsfakia@gmail.com

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Δευτέρα 4 Ιανουαρίου 2021

Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma

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Purpose:

Heterogeneity in glioblastomas is associated with poorer outcomes, and physiologic heterogeneity can be quantified with noninvasive imaging. We developed spatial habitats based on multiparametric physiologic MRI and evaluated associations between temporal changes in these habitats and progression-free survival (PFS) after concurrent chemoradiotherapy (CCRT) in patients with glioblastoma.

Experimental Design:

Ninety-seven patients with isocitrate dehydrogenase (IDH)-wildtype glioblastoma were enrolled and two serial MRI examinations after CCRT were analyzed. Cerebral blood volumes and apparent diffusion coefficients were grouped using k-means clustering into three spatial habitats. Associations between temporal changes in spatial habitats and PFS were investigated using Cox proportional hazard modeling. The performance of significant predictors for PFS and overall survival (OS) was measured using a discrete increase of habitat (habitat risk score) in a temporal validation set from a prospective registry (n = 53, ClinicalTrials.gov NCT02619890). The site of progression was matched with the spatiotemporal habitats.

Results:

Three spatial habitats of hypervascular cellular, hypovascular cellular, and nonviable tissue were identified. A short-term increase in the hypervascular cellular habitat (HR, 40.0; P = 0.001) and hypovascular cellular habitat was significantly associated with shorter PFS (HR, 3.78; P < 0.001) after CCRT. Combined with clinical predictors, the habitat risk score showed a C-index of 0.79 for PFS and 0.74 for OS and stratified patients with short, intermediate, and long PFS (P = 0.016). An increase in the hypovascular cellular habitat predicted tumor progression sites.

Conclusions:

Hypovascular cellular habitats derived from multiparametric physiologic MRIs may be useful predictors of clinical outcomes in patients with posttreatment glioblastoma.

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