AI-Powered Analysis of Stent Healing

Each year, more than three million people worldwide are treated with stents to open blocked blood vessels caused by heart disease. However, monitoring the healing process after implantation remains a challenge. If the tissue growing over the stent develops irregularly - either becoming too thick or forming deposits - it can lead to complications, such as re-narrowing or occlusion of the blood vessel. Currently, analyzing these healing patterns in intravascular optical coherence tomography (OCT) images is time-consuming and impracticable for routine clinical practice.

A research team from Helmholtz Munich and the TUM University Hospital has now developed DeepNeo, an artificial intelligence (AI) algorithm that 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.

"With DeepNeo, we can achieve an automated, standardized, and highly accurate analysis of stent and vascular healing that was previously only possible through extensive manual effort," says Valentin Koch, first author of the study introducing the algorithm. "DeepNeo is as good as a doctor, but much faster."

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.

"DeepNeo demonstrates how machine learning can support clinicians in making quicker, more informed treatment decisions. The next step is now to effectively integrate AI algorithms like DeepNeo into clinical practice," explains Dr. Carsten Marr, Director at the Institute of AI for Health at Helmholtz Munich. His colleague Prof. Julia Schnabel, who leads the Institute of Machine Learning in Biomedical Imaging and is Professor of Computational Imaging and AI in Medicine at TUM, envisions DeepNeo as part of an AI-powered healthcare system that could offer unprecedented certainty for clinical decision-making.

The project has received a Helmholtz Innovation Grant, and a patent application has been filed. Ascenion, technology transfer partner in the life sciences, is supporting the DeepNeo team in identifying potential industry partners. "DeepNeo facilitates and standardizes OCT imaging assessment after stent implantation and thus improves clinical decision-making," say PD Dr. med. Philipp Nicol and Prof. Dr. med. Michael Joner, cardiologists at the TUM University Hospital, who led the project from the clinical side. "This has the potential to not only reduce healthcare costs but pave the way for more effective and personalized cardiovascular treatments."

Koch V, Holmberg O, Blum E, Sancar E, Aytekin A, Seguchi M, Xhepa E, Wiebe J, Cassese S, Kufner S, Kessler T, Sager H, Voll F, Rheude T, Lenz T, Kastrati A, Schunkert H, Schnabel JA, Joner M, Marr C, Nicol P.
Deep learning model DeepNeo predicts neointimal tissue characterization using optical coherence tomography.
Commun Med (Lond). 2025 Apr 17;5(1):124. doi: 10.1038/s43856-025-00835-5

Most Popular Now

AI Tool Helps Predict Relapse of Pediatr…

Artificial intelligence (AI) shows tremendous promise for analyzing vast medical imaging datasets and identifying patterns that may be missed by human observers. AI-assisted interpretation of brain scans may help improve...

Open Medical Works with Moray's Dig…

Open Medical is working with the Digital Health & Care Innovation Centre’s Rural Centre of Excellence on a referral management plan, as part of a research and development scheme to...

NHS, Councils, and Housing could Share N…

A new technology partnership formally announced, could help NHS, local government, and housing organisations collaborate to create an unprecedented understanding of the risks and needs of people in their care...

AI-Powered Analysis of Stent Healing

Each year, more than three million people worldwide are treated with stents to open blocked blood vessels caused by heart disease. However, monitoring the healing process after implantation remains a...

Generative AI on Track to Shape the Futu…

Using advanced artificial intelligence (AI), researchers have developed a novel method to make drug development faster and more efficient. In a new paper, Xia Ning, lead author of the study and...

AI could Help Improve Early Detection of…

A new study led by investigators at the UCLA Health Jonsson Comprehensive Cancer Center suggests that artificial intelligence (AI) could help detect interval breast cancers - those that develop between...

Reorganisation, Consolidation, and Cuts:…

NHS England has been downsized and abolished. Integrated care boards have been told to change function, consolidate, and deliver savings. Trusts are planning big cuts. The Highland Marketing advisory board...

AI-Human Task-Sharing could Cut Mammogra…

The most effective way to harness the power of artificial intelligence (AI) when screening for breast cancer may be through collaboration with human radiologists - not by wholesale replacing them...

Siemens Healthineers infection Control S…

Klinikum Region Hannover (KRH) has commissioned Siemens Healthineers to install infection control system (ICS) at the Klinikum Siloah hospital. The ICS aims to effectively tackle nosocomial infections and increase patient...

Philips Future Health Index 2025 Report …

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, today unveiled its 2025 Future Health Index U.S. report, "Building trust in healthcare AI," spotlighting the state of...

AI Tool Uses Face Photos to Estimate Bio…

Eyes may be the window to the soul, but a person's biological age could be reflected in their facial characteristics. Investigators from Mass General Brigham developed a deep learning algorithm...

Building Trust in Artificial Intelligenc…

A new review, published in the peer-reviewed journal AI in Precision Oncology, explores the multifaceted reasons behind the skepticism surrounding artificial intelligence (AI) technologies in healthcare and advocates for approaches...