Track 1: Computational reconstruction of glioblastoma surgical margins identifies molecular drivers of residual tumor recurrence

Glioblastoma recurrence after maximal safe resection remains a major challenge in neurosurgical oncology, with residual infiltrative tumor cells frequently persisting beyond radiographically visible margins. Current surgical approaches rely primarily on anatomical visualization and histopathological evaluation, limiting the ability to predict which residual regions harbor aggressive tumor populations. This study developed a computational framework integrating surgical pathology, transcriptomic profiles, and invasion-associated molecular signatures to identify biological determinants of postoperative recurrence risk.

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