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 Predicts Risks for Outpatient Stem Cell Therapy in Myeloma
Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.

•EurekAlert
USC Unveils Joint Biomedical Engineering Department Bridging Medicine, Engineering, and Imaging
USC's medical and engineering schools launch a joint biomedical engineering department to accelerate interdisciplinary research and innovation, including imaging and AI.

•EurekAlert
AI-Enhanced CT Heart Fat Measurement Boosts Cardiovascular Risk Prediction
AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.