UCLA Researchers Develop AI-Powered Sensor for High-Sensitivity Cardiac Diagnostics
The Californer/10304607

LOS ANGELES - Californer -- A research team at UCLA has developed a deep learning-powered chemiluminescence vertical flow assay (CL-VFA) that brings clinical laboratory-grade cardiac troponin I (cTnI) testing to a portable, cost-effective point-of-care platform. Their work, recently published in the journal Small, demonstrates how the integration of chemiluminescence-based biosensing, high-sensitivity imaging through a portable reader, and AI-driven data analysis enables rapid, highly sensitive cTnI quantification for the detection of myocardial infarction (MI), also known as heart attack, in diverse clinical settings. This technology holds the potential to democratize access to fast and reliable cardiac diagnostics, particularly in resource-limited environments where advanced laboratory infrastructure is lacking.

This research was led by Dr. Aydogan Ozcan, Chancellor's Professor of Electrical & Computer Engineering and the associate director of the California NanoSystems Institute (CNSI) at UCLA, in collaboration with Professor Dino Di Carlo of the UCLA Bioengineering Department, Professor Omai Garner, the director of UCLA Clinical Microbiology Lab. The first authors of the paper are Dr. Gyeo-Re Han, a postdoctoral researcher, and Artem Goncharov, a graduate student at UCLA Electrical & Computer Engineering Department.

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This platform features a robust integration of deep learning-driven computational analysis and highly sensitive chemiluminescence biosensing. This innovation allows for the detection of cTnI at levels as low as 0.1-0.2 pg/mL and an extensive dynamic range from less than 1 pg/mL to 100 ng/mL. These specifications outperform existing point-of-care devices, effectively meeting the clinical standards for high-sensitivity troponin testing—an essential factor in early MI diagnosis and risk stratification. This point-of-care sensor requires only 50 µL of serum and features a streamlined workflow, potentially enabling medical staff to perform tests with simplicity. It provides cTnI results in just 25 min for rapid clinical decision-making.

The researchers rigorously validated their sensor platform using clinical serum samples. In a blinded validation study with patient samples, their sensor showed a strong correlation with an FDA-cleared laboratory analyzer, demonstrating its reliability, clinical accuracy, and potential for real-world diagnostic applications.

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Beyond its high performance, this sensor is also designed for affordability. Traditional benchtop chemiluminescence analyzers cost more than ~$10,000-20,000. In contrast, the UCLA reader system, which is built on a custom optical imager, costs ~$222, while each test is priced at ~$4. This cost-effectiveness of the sensor makes it an ideal solution for expanding access to cardiac diagnostics in primary care clinics, pharmacies, and mobile health units, particularly in resource-constrained settings.

This research was supported by the NSF-funded Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) Engineering Research Center (ERC).

Link to the Article: https://onlinelibrary.wiley.com/doi/10.1002/smll.202411585