Heart attacks are a leading cause of death worldwide. Early diagnosis is crucial for saving lives. However, standard lab tests can be time-consuming and expensive.
To address this, University of California, Los Angeles researchers have developed a low-cost paper-based sensor to detect a biomarker for heart attacks.
The developers say that it’s designed to provide rapid results in just 15 minutes.
“We are excited to introduce this low-cost, portable solution that bridges the gap between central laboratory diagnostics and point-of-care testing,” said Aydogan Ozcan, the senior author of the study.
“Our paper-based platform, powered by deep learning, offers an effective alternative to the bulky, expensive instruments currently used in hospitals. It holds the promise of bringing advanced cardiac diagnostics to underserved populations globally,” Ozcan added.
Powered by deep learning algorithms
The researchers have designed a paper-based vertical flow assay (VFA). It detects cardiac troponin I (cTnI), a protein released into the bloodstream when heart muscle is damaged.
This innovative platform is the combination of two powerful technologies: deep learning algorithms and advanced nanoparticle amplification chemistry. In this platform, the algorithms are used to analyze images captured by the VFA system and enhance the detection of cTnI.
Interestingly, the sensor holds the potential to achieve a “detection limit as low as 0.2 picograms per milliliter (pg/mL).”
The researchers state that this platform’s exceptional sensitivity far exceeds that of existing point-of-care devices. The tool meets “clinical requirements” to detect very small amounts of troponin protein in the bloodstream. This accurate detection may pave the way for early diagnosis of acute myocardial infarction (AMI), or heart attack.
Low-cost
The hs-VFA system works in two steps. In the immunoassay phase, the test identifies the cTnI protein in the blood sample. For this, it uses tiny gold particles attached to other molecules to bind to the cTnI protein.
In the second, the signal amplification phase, the gold particles trigger a chemical reaction that creates a color change. A special portable device then takes pictures of this color change.
Deep learning algorithms are used to analyze these pictures and make the test even more sensitive and accurate.
The team found that hs-VFA test results were very similar to the results of traditional lab tests. This showcased the hs-VFA test reliability.
Also, the system can detect various levels of cTnI, from very low to very high (0.2 pg/mL to 100 nanograms per milliliter (ng/mL).
In terms of cost, the paper-based assay is priced below $4 per test, while the portable reader costs roughly $170 per unit. This affordability may prove valuable for resource-constrained environments.
“Our goal was to design a system that could be used not only in hospitals but also in clinics, pharmacies, and even in ambulances,” said Gyeo-Re Han, the first author of the study and a postdoctoral researcher at UCLA.
“The ability to rapidly detect and quantify troponin levels in diverse settings could enable faster, more effective treatment of heart attack patients, particularly during the critical prehospital phase of care,” Han added in the press release.
The findings were published in the journal ACS Nano.
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