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ODIASP

Maturation

Optimization of the DIAgnosis of SarcoPenia

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Linksium Contact Chloé Poyet +33 (0)6 46 57 42 17 chloe.poyet@linksium.fr

Benefits

Automated screening for undernutrition
Time saving
Better patient care

Key words

Undernutrition
Artificial intelligence
Medical imaging
Scanner

Intellectual Property

1 software

Laboratory

TIMC

Institutions

CNRS
GRENOBLE INP-UGA
UGA

Linksium Continuum

Maturation

Context

Undernutrition, particularly in hospitals, has a major medico-economic impact, leading to an increased risk of complications and death. Identifying patients suffering from malnutrition is therefore crucial in order to provide them with nutritional care and improving their prognosis.

Technology

Thanks to the integration of AI algorithms, the ODIASP software can automatically and rapidly detect a reduction in muscle mass, a criterion of undernutrition, from scans taken as part of routine care. The software has been rigorously validated on a database of over 600 patients.

Advantages

Thanks to artificial intelligence algorithms, the software can automatically calculate the muscular surface index (MSI) from a patient scan, making it possible to detect undernutrition in hospitalised patients and adapt nutritional care accordingly. The time saved in screening is invaluable, enabling early intervention with affected patients.

State of progress

The software has been developed and validated on a database of over 600 patients. Developments are underway to CE mark the ODIASP software so that it becomes a standard tool for identifying undernutrition opportunistically on all scanners.

Applications

The software is designed for medical use with patients who have a scanner as part of their routine care.