METLiT provides non-invasive magnetic resonance spectroscopy (MRS) services enhanced by deep learning to quantify a broader range of metabolites in living tissues. This technology enables medical professionals to obtain real-time biochemical information for accurate diagnosis and treatment monitoring, reducing the need for invasive biopsy procedures.
Funding
Funding not disclosed
Founders
Product
Problem
Conventional magnetic resonance spectroscopy (MRS) struggles to quantify a broad range of metabolites in living tissues due to limitations in data processing and analysis. This restricts the amount of biochemical information obtainable, hindering accurate diagnosis and treatment monitoring. Invasive biopsy procedures are often required to compensate for these limitations.
Solution
METLiT offers non-invasive MRS services enhanced by deep learning to quantify a wider array of metabolites from standard MRS data. Their AI-powered solution extracts more comprehensive biochemical information from existing MRS scans, providing a real-time snapshot of cellular activity. This enables medical professionals to gain deeper insights for diagnosis, treatment monitoring, and research, potentially reducing the reliance on invasive biopsies. The technology integrates with most MRI scanners, adding a short amount of time to the overall scan.
Target Audience
The primary audience includes medical professionals, such as radiologists, oncologists, and neurologists, who utilize MRI for diagnosis and treatment monitoring, as well as researchers in related fields.
Features
- AI-driven analysis of MRS data to quantify a broader range of metabolites.
- Non-invasive assessment of biochemical concentrations in living tissues.
- Compatibility with most existing MRI scanners, requiring only a short additional scan time.
- Provides real-time metabolic information for diagnosis and treatment monitoring.
- Enables the discovery of localized molecular biomarkers for various pathological processes.