NeoPred, a dual-phase CT AI tool, accurately predicts major pathological response in NSCLC patients preoperatively.
Key Details
- 1NeoPred combines pre-treatment and pre-surgery CT scans with clinical data to predict major pathological response (MPR) in NSCLC undergoing neoadjuvant chemo-immunotherapy.
- 2Study included 509 patients across four oncology centers (459 retrospective, 50 prospective, 59 external validation).
- 3NeoPred reached AUCs of 0.772 (imaging only) and 0.787 (imaging plus clinical data) on external validation, outperforming thoracic surgeons (AUC 0.760 vs 0.720) in prospective testing.
- 4AI support improved surgeons' AUC to 0.829 and diagnostic accuracy to 82%.
- 5NeoPred identified 'pseudo-stable' responders missed by standard RECIST criteria, with AUCs of 0.742 (external) and 0.833 (prospective).
Why It Matters
Accurately predicting response before surgery could enable earlier, evidence-based clinical decisions for NSCLC, reducing overtreatment and personalizing care. This work demonstrates the expanding role and performance advantage of AI-assisted imaging over traditional assessment in complex oncologic management.
Source
EurekAlert
Related News
•EurekAlert
AI Method Automates X-ray Absorption Spectroscopy for Material Analysis
Researchers have developed an AI-based approach to automate and enhance the analysis of X-ray absorption spectroscopy (XAS) data for materials science.
•EurekAlert
BraDiPho: New 3D AI Atlas Integrates Brain Dissections with MRI
Researchers have developed BraDiPho, a tool that merges ex-vivo photogrammetric brain dissection data with in-vivo MRI tractography using AI.
•EurekAlert
AI Maps Genetic Factors Shaping the Corpus Callosum via MRI Scans
USC researchers used AI to analyze MRI scans and uncover the genetic architecture of the brain's corpus callosum.