MRIMath, an artificial intelligence (AI)-driven company supported by the National Cancer Institute, has earned the US Food & Drug Administration (FDA) 510(k) clearance for its cyber device, MRIMath i2Contour and AI solution.
MRIMath i2Contour and its AI are designed to improve both the efficiency and precision of glioblastoma (GBM) management.
According to Alabama-based MRIMath, the offering helps to eliminate bottlenecks in contouring and speed up patient care by potentially saving physicians up to an hour per imaging study.
The MRIMath i2Contour device features advanced AI-powered tools designed to streamline processes, minimise inter-user variability, and enhance precision.
By enabling quicker and more accurate reviews, the technology is said to have the potential to improve patient outcomes and lower healthcare costs.
It empowers physicians to provide optimal treatments across different locations, leading to a better overall patient experience.
The MRIMath i2Contour device boasts several key features. It enhances time-saving efficiency by reducing GBM labelling and volume measurement times by up to an hour, addressing critical bottlenecks.
As a secure cyber device, it complies with US FDA security measures, ensuring safe medical data management.
The device also supports collaborative team spaces, optimising workflow both within and across institutions, whether rural or urban, thereby improving access to healthcare and multidisciplinary coordination.
Its accurate AI labelling offers precise identification of GBM in MRI FLAIR and T1 contrast sequences, aiding clinical decision-making.
Additionally, the device features smart manual contouring to reduce inter-user variability and simplify review and approval processes.
Furthermore, it includes tools for precise volume measurement and plotting, essential for monitoring and treatment planning over time. The device also comes with a DICOM viewer.
University of Alabama neurology department professor Burt Nabors said: “MRIMath cyber device and GBM AI provide needed and advanced tools for the rapid, longitudinal computation of segmented imaging changes occurring in the central nervous system as a result of glioblastoma, the treatment of glioblastoma, or infiltration into the normal brain.
“This advance in technology will help improve the outcomes for patients with glioblastoma.”
MRIMath AI models achieved high labelling accuracy, with 95% for T1c and 92% for FLAIR, matching radiologists’ scores in FDA testing.
The Smart manual contouring platform showed less than 5% variability between radiologists for T1c and under 10% for FLAIR sequences.
