Quantitative image signature predicts survival in glioblastoma patients

Monday, December 1 | 10:40 a.m.-10:50 a.m. | SSC10-02 | Room N226
In this presentation, researchers from Stanford University will describe how a quantitative image signature on MRI can aid survival prediction in patients with glioblastoma multiforme.

Affecting young and old alike, glioblastoma multiforme is the most common primary malignant tumor of the brain and is highly lethal. While a few known factors can accurately predict survival, they rely on tumor molecular characteristics accessed via biopsy of brain tissue, said presenter Dr. Haruka Itakura.

"Being able to prognosticate survival by MR imaging -- a routinely used diagnostic tool -- would be ideal, but it has not been reported to date," he told AuntMinnie.com. "Our study addressed this need and identified a profile of signature prognostic imaging features, using a multivariate model that was developed on one patient cohort and validated on another."

The image signature, which predicted survival in distinct cohorts, could support a tool to inform clinical decision-making noninvasively in patients with glioblastoma multiforme, Itakura said.

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