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The National Institutes of Biomedical Imaging and Bioengineering (NIBIB), part of NIH, lead the multi-institutional collaboration.
“This program is particularly exciting because it will give us new ways to rapidly turn scientific findings into practical imaging tools that benefit COVID-19 patients,” Bruce J. Tromberg, PhD, NIBIB Director, said in the announcement.
“It unites leaders in medical imaging and artificial intelligence from academia, professional societies, industry, and government to take on this important challenge.”
Medical images show the severity of infected lungs and hearts, which can help to predict responses to treatment and improve patient outcomes.
But a major challenge s, NIH noted, is that providers and researchers must rapidly and accurately identify these features and evaluate the information along with other clinical symptoms and tests, especially when time is of the essence with COVID-19 care
“This effort will gather a large repository of COVID-19 chest images,” explained Guoying Liu, PhD, NIBIB scientific program lead on this effort. “Allowing researchers to evaluate both lung and cardiac tissue data, ask critical research questions, and develop predictive COVID-19 imaging signatures that can be delivered to healthcare providers.”
The MIDRC will facilitate rapid and flexible collection and analysis of imaging and associated clinical data, NIH said. Participating organizations will provide expertise within medical imaging, imaging data quality, security, access, and sustainability.
“This major initiative responds to the international imaging community’s expressed unmet need for a secure technological network to enable the development and ethical application of artificial intelligence to make the best medical decisions for COVID-19 patients,” said Krishna Kandarpa, MD, PhD, director of research sciences and strategic directions at NIBIB.
“Eventually, the approaches developed could benefit other conditions as well.”
Back in June, NIH rolled out a COVID-19 analytics platform that will provide a centralized, secure enclave to analyze medical record data from COVID-19 patients so that experts can understand the disease and develop effective treatments.
The study is part of an effort called the National COVID Cohort Collaborative (N3C), which aims to transform clinical information needed to identify health risk factors that indicate better or worse outcomes of COVID-19.
The initiative will combine information into a standard format and make it available for researchers and providers to find potentially effective COVID-19 treatments.
Additionally, the platform will help researchers and healthcare providers answer clinically important questions about which patients may need dialysis because of kidney failure or individuals who may need to be on a ventilator because of lung failure.
Currently, there are 35 collaborating sites across the US. N3C will translate the different ways that contributing hospitals and organizations store patient data into one common format, which NIH called an ‘apples to apples’ analysis.
“NCATS initially supported the development of this innovative collaborative technology platform to speed the process of understanding the course of diseases, and identifying interventions to effectively treat them,” Christopher P. Austin, MD, NCATS Director, said in the announcement.
“This platform was deployed to stand up this important COVID-19 effort in a matter of weeks, and we anticipate that it will serve as the foundation for addressing future public health emergencies.”