An AI tool analyzing CCTA images can predict future cardiovascular events and death in patients with suspected stable coronary artery disease.
Key Details
- 1The FISH&CHIPS study involved 7,836 patients who underwent AI-derived FFR-CT analysis from an initial 90,553 receiving CCTA.
- 2Lower FFR-CT values correlated with significantly increased rates of MI, cardiovascular death, and all-cause mortality independent of traditional risk factors.
- 3Patients with severely reduced FFR-CT had a four-fold risk of heart attack and triple risk of death versus those with normal values.
- 4The FFR-CT AI analysis (by HeartFlow) provided additive prognostic value over classical cardiovascular risk scores.
- 5This is the first large-scale evidence of FFR-CT's independent prognostic power in stable CAD.
- 6Study funded by UK MRC; HeartFlow provided analysis but did not fund or direct the study.
Why It Matters
This research demonstrates real-world prognostic utility for AI-based imaging tools in cardiovascular risk prediction, supporting expanded adoption of AI-enhanced CT in personalized patient management and reducing unnecessary procedures.
Source
EurekAlert
Related News
•EurekAlert
NIH-Backed AI Model Predicts Cancer Survival Using Single-Cell Data
Researchers have developed scSurvival, a machine learning tool that uses single-cell tumor data to accurately predict cancer patient survival and identify high-risk cell populations.
•EurekAlert
Deep Learning Pathomics Platform Improves Immunotherapy Prediction in Lung Cancer
A deep learning pathomics platform accurately predicts immunotherapy response in metastatic NSCLC using routine pathology slides.
•EurekAlert
AI Pathology Model Outperforms PD-L1 in Predicting NSCLC Immunotherapy Response
MD Anderson's Path-IO machine learning platform accurately predicts immunotherapy responses in metastatic non-small cell lung cancer, surpassing current biomarker standards.