Paper-based Sensor Allows Rapid Detection of Heart Attacks
Outcome/Accomplishment
When individuals experience acute myocardial infarction, also known as a heart attack, time is precious. Detection and diagnosis of a heart attack have typically required expensive laboratory equipment and quick access to advanced medical facilities. Now, researchers at the U.S. National Science Foundation (NSF)-funded Precise Advanced Technologies and Health Systems for Underserved Populations (NSF PATHS-UP) Engineering Research Center (ERC) have developed a paper-based test which measures cardiac troponin I (cTnI), one of the biomarkers of a heart attack, in just 15 minutes, making testing less expensive and more readily available. NSF PATHS-UP ERC is headquartered at Texas A&M University, with partners from the University of California at Los Angeles, Rice University, and Florida International University.
Impact/Benefits
In research recently published in the journal ACS Nano, the team demonstrated the use of a deep learning-enhanced, paper-based vertical flow assay capable of detecting cTnI with high sensitivity. These paper-based tests are both cost-effective and highly portable, costing only $4 per test and only $170 for the portable reader, which is designed using a Raspberry Pi computer and off-the-shelf components. The team anticipates that these sensing technologies will transition into commercial applications through licensing and/or spin-off efforts.
Explanation/Background
In experimental tests using small amounts of serum and whole blood, researchers have been able to benchmark the paper-based tests against current point-of-care devices and found that they not only meet the clinical requirements for testing but even surpass them in terms of sensitivity. Broadening access to this kind of diagnostic testing can improve health outcomes globally, reducing deaths due to cardiovascular diseases, which number 19 million fatalities worldwide each year. In particular, underserved populations that may not have access to medical facilities or testing in the limited window of cardiac event interventions would benefit from these highly sensitive rapid tests.
"The NSF PATHS-UP researchers have achieved a highly effective solution by leveraging a paper-based platform to minimize costs and incorporating machine learning to enhance diagnostic accuracy," said Dr. Lan Wang, Program Director for the NSF Division of Engineering Education and Centers. "Moreover, the NSF PATHS-UP Engineering Research Center trains diverse scientists and engineers to develop enabling technologies, like this one, aimed at improving health outcomes in communities with low access to medical care."
Location
College Station, Texaswebsite
Start Year
Biotechnology and Healthcare
Biotechnology and Healthcare
Lead Institution
Core Partners
Fact Sheet
Outcome/Accomplishment
When individuals experience acute myocardial infarction, also known as a heart attack, time is precious. Detection and diagnosis of a heart attack have typically required expensive laboratory equipment and quick access to advanced medical facilities. Now, researchers at the U.S. National Science Foundation (NSF)-funded Precise Advanced Technologies and Health Systems for Underserved Populations (NSF PATHS-UP) Engineering Research Center (ERC) have developed a paper-based test which measures cardiac troponin I (cTnI), one of the biomarkers of a heart attack, in just 15 minutes, making testing less expensive and more readily available. NSF PATHS-UP ERC is headquartered at Texas A&M University, with partners from the University of California at Los Angeles, Rice University, and Florida International University.
Location
College Station, Texaswebsite
Start Year
Biotechnology and Healthcare
Biotechnology and Healthcare
Lead Institution
Core Partners
Fact Sheet
Impact/benefits
In research recently published in the journal ACS Nano, the team demonstrated the use of a deep learning-enhanced, paper-based vertical flow assay capable of detecting cTnI with high sensitivity. These paper-based tests are both cost-effective and highly portable, costing only $4 per test and only $170 for the portable reader, which is designed using a Raspberry Pi computer and off-the-shelf components. The team anticipates that these sensing technologies will transition into commercial applications through licensing and/or spin-off efforts.
Explanation/Background
In experimental tests using small amounts of serum and whole blood, researchers have been able to benchmark the paper-based tests against current point-of-care devices and found that they not only meet the clinical requirements for testing but even surpass them in terms of sensitivity. Broadening access to this kind of diagnostic testing can improve health outcomes globally, reducing deaths due to cardiovascular diseases, which number 19 million fatalities worldwide each year. In particular, underserved populations that may not have access to medical facilities or testing in the limited window of cardiac event interventions would benefit from these highly sensitive rapid tests.
"The NSF PATHS-UP researchers have achieved a highly effective solution by leveraging a paper-based platform to minimize costs and incorporating machine learning to enhance diagnostic accuracy," said Dr. Lan Wang, Program Director for the NSF Division of Engineering Education and Centers. "Moreover, the NSF PATHS-UP Engineering Research Center trains diverse scientists and engineers to develop enabling technologies, like this one, aimed at improving health outcomes in communities with low access to medical care."