Automated RANO 2.0-Aligned Response Assessment for Glioblastoma Clinical Trials: External Evaluation Against Expert Annotations

Background/objectives

Reliable and reproducible imaging-response assessment is essential for endpoint evaluation in glioblastoma clinical trials. The Response Assessment in Neuro-Oncology (RANO) criteria provide a rule-based framework for standardisation, but their implementation can still yield variable outputs between readers and across timepoints and trial sites. This partly reflects differences in lesion definition, measurement geometry, longitudinal tracking, and new-lesion adjudication. We externally evaluated an automated pipeline for auditable, RANO 2.0-aligned imaging-only response assessment using pre-existing segmentation masks.