A new AI approach enables OCT to automatically detect lipid-rich plaques in coronary arteries, showing strong agreement with histopathology results.
Key Details
- 1Researchers developed an AI method for detecting fatty deposits in coronary arteries using OCT images.
- 2This method combines spectral data from OCT with deep learning to identify lipid-rich plaques.
- 3The AI approach works with existing clinical OCT systems and does not require extra hardware.
- 4Validation against histopathology in a rabbit model showed strong classification performance.
- 5The technique requires only frame-level annotations, reducing expert labeling time and subjectivity.
- 6Plans are underway for further validation in human coronary artery data and workflow integration.
Why It Matters
Automated lipid plaque detection in OCT can help clinicians better assess cardiac risk without increasing workflow burden, offering more objective and robust support for interventional cardiology. This is a significant advance in imaging AI for cardiovascular applications.
Source
EurekAlert
Related News
•EurekAlert
UVA's $4M NIH Grant Backs AI to Optimize Cardiac MRI Therapies
UVA secures $4 million NIH funding to develop GenStrain, an AI model using MRI data to personalize cardiac pacing therapies.
•EurekAlert
Machine Learning Models Predict Cancer Risk with Routine Health Data
Researchers developed machine learning models using routinely collected health data to predict individual risk for 20 common cancers, outperforming traditional methods for several cancer types.
•EurekAlert
Duke Receives $25M to Lead National Trustworthy AI Hub for Dementia and Aging
Duke University has launched a $25 million national center to make AI for aging and dementia clinically robust and trustworthy.