AI Overview: New Tools to Help with Regional Patient Data and Reduce Image Noise
This week, we announced new vendors across a range of artificial intelligence applications: improving county-level population health management and a spinoff from New York University Langone Health focused on harnessing physics to improve artificial intelligence imaging technology.
In addition, the new, unique imaging software, with regulatory clearance from the U.S. Food and Drug Administration, may give clinicians access to a powerful noise reduction algorithm that improved the quality of MRI scans in a recent neurology study by developer Microstructure Imaging.
FDA Clears RMT for Clinical Practice
Microstructure Imaging, a Brooklyn, New York-based vendor specializing in the development of MRI software, announced Wednesday that it has received FDA 501 clearance for its breakthrough signal-to-noise diffusion and functional MRI software.
While MRI machines are often noisy for patients, the noise the images produce is a bigger concern for their overall care. MRI uses a strong magnetic field and radio waves to create detailed images of organs and tissues, but the clarity of the image is subject to an SNR ratio, which is a calculation that indicates the difference between the area of interest and the background at each pixel.
While more medical understanding can be gained from images with higher signal-to-noise ratios, MICSI says it has added an algorithm based on random matrix theory that provides “a multiplicative boost in signal-to-noise ratio.”
The software, called MICSI-RMT, is the first to bring RMT denoising into clinical practice, the company said, making it particularly suitable for neuroimaging applications, such as stroke treatment, where accurate imaging improves medical decision-making.
The software can improve the quality of MRI images without external training data or powerful GPUs, unlike traditional AI-enhanced imaging, the company said in a rack.
This means the AI-enhanced denoising approach does not hallucinate, the company said. website.
MICSI-RMT also incorporates modules that support weighted linear least squares and Bayesian fitting techniques to facilitate quantitative analysis of diffusion-weighted imaging. Additionally, the company noted that DICOM data routing allows for secure integration into medical workflows.
In the company’s blinded rater study, neuroradiologists reviewed MRI images processed with MICSI-RMT and standard-of-care tools and said they preferred RMT imaging for its clarity and reduced artifacts. They also said DTI images processed with MICSI-RMT had sharper visualization of small structures in the brain’s white matter and better contrast with adjacent tissue types. They also reported more anatomically appropriate activation maps with functional MRI images produced with RMT technology.
Researchers found that RMT technology improved diffusion MRI by 4.35x and fMRI by 1.9x, and provided more accurate parametric mapping. There was also a notable improvement – 56.3% – in dMRI improvement with the precision of ADC maps.
County improves patient analyses
Innovaccer Inc., a company focused on AI platforms in healthcare, announced Wednesday that San Mateo County Health will use its population health management platform to improve patient care and manage data from approximately 165,000 lives and 500,000 past lives in the region.
By collecting data from multiple SMCH systems and integrating it into electronic health records, healthcare providers can search for patients across multiple EHR systems, view longitudinal patient records, and send data back to their main EHRs, the company said.
“This collaboration is a great example of teams successfully working together to seamlessly integrate data and improve care delivery, while bringing back the joy of care,” said Abhinav Shashank, co-founder and CEO of Innovaccer, in a statement.
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Andrea Fox is Editor-in-Chief of Healthcare IT News.
Email address: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.