A research team has developed DeepNeo, an AI-powered algorithm that automates the process of analyzing coronary stents after implantation. The tool matches medical expert accuracy while significantly reducing assessment time. With strong validation in both human and animal models, Deep-Neo has the potential to standardize monitoring after stent implantation and thus improve cardiovascular treatment outcomes.
The AI algorithm can automatically assess stent healing in OCT images. DeepNeo differentiates between different healing patterns with an accuracy comparable to clinical experts — but in a fraction of the time. The AI tool also provides precise measurements, e.g., regarding tissue thickness and stent coverage, offering valuable insights for patient management.
To train DeepNeo, researchers used 1,148 OCT images from 92 patient scans, manually annotated to classify different types of tissue growth. They then tested the AI algorithm in an animal model, where it correctly identified unhealthy tissue in 87 percent of cases when compared to detailed laboratory analysis, the current gold standard. When analyzing human scans, DeepNeo also demonstrated high precision, closely matching expert assessments. (Image credit: Helmholtz Munich)
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