Ontology highlight
ABSTRACT: Purpose
Accurate non-invasive prediction of histopathologic invasiveness and recurrence risk remains a clinical challenge in resectable non-small cell lung cancer (NSCLC). We developed and validated the Edge Proximity Score (EPS), a novel [18F]FDG PET/CT-based spatial imaging feature that quantifies the displacement of SUVmax relative to the tumor centroid and perimeter, to assess tumor aggressiveness and predict progression-free survival (PFS).Methods
This retrospective study included 244 NSCLC patients with preoperative [18F]FDG PET/CT. EPS was computed from normalized SUVmax-to-centroid and SUVmax-to-perimeter distances. A total of 115 PET radiomics features were extracted and standardized. Eight machine learning models (80:20 split) were trained to
SUBMITTER: Jiang Z
PROVIDER: S-EPMC12860873 | biostudies-literature | 2026 Feb
REPOSITORIES: biostudies-literature