Standard predictors of outcome after cardiac arrest (CA) have substantial limitations in terms of reliability and generalizability. By providing brain structural connectivity maps, or connectomes, advanced MRI techniques, operating through high-strength magnetic field (HF; 1.5 to 3-T), have precisely revealed structural brain damages induced by CA, and have demonstrated the high sensitivity and specificity of these indicators for predicting neurological outcome after CA. However, HF MRI requires patient’s transport to dedicated hospital imaging suites, hindering the implementation of these promising neuroimaging techniques in the setting of critical illness. Interestingly, a recent report demonstrates the capability of a proof-of-concept (POC) very low-field (VLF; 0.064-T) portable MRI to obtain neuroimaging at the bedside in critically ill patients. Nevertheless, the spatial resolution of VLF-MRI seems low and there is no available evidence about the use of VLF-MRI to extract highly needed new predictors of neurological recovery based on brain structural connectomes. Based on previous studies from our group, we hypothesize that VLF MRI brain data carries potentially game-changing information that can be used to significantly improve neuroprognostication in this clinically challenging setting. The current proposal is a POC study which aims to compare for the first time, HF, VLF and enhanced VLF (recon-VLF) structural connectomes from anoxo-ischemic coma patients and healthy subjects across the time. To obtain recon-VLF data, we will use an ensemble of ground-breaking methods to increase the native spatial resolution of VLF-MRI data. A numerical solution will be developed to provide robust indicators of CA brain impact across the time at patient’s bedside, allow data sharing (FAIR data) and pave the way for future large scale neuroprognostication clinical studies that will combine standard predictors and VLF / recon-VLF MRI brain data.

The GEONAV IoT project aims at the development and delivery of precise ubiquitous positioning and navigation applications and services. The core activity of the project is to develop and industrialize the 2nd evolution phase of the GEONAV IoT solution, following NAVISP Element 2 outcomes (TRL7). GEONAV IoT is market driven with clear commercialization ambition. It aims to: - Use Galileo features that improve performances: Dual Frequency for an improved real-time positioning and TTFF; - Improve fusion with other positioning techniques thanks to innovative network fusion techniques with 5G; - Optimise power consumption thanks to TTFF improvements and GEONAV IoT algorithms; - Expand the range of market application with demonstration on 3 use cases: Elite sports (Rugby), Asset tracking and monitoring; Autonomous Drones based delivery system; - Set-up a European Industrialisation chain. The GEONAV IoT consortium is made of industrials and SMEs mastering the full industrial value chain. Our aim is to demonstrate the European production capacity of innovative EGNSS application based devices and services and accelerate their market take up. The project duration is 18 months, our ambition is to improve TRL up to 8-9. The addressable LBS and Drones markets are huge and Elite Sport will help for promotion on GEOANV IoT. Market take up per use cases is part of GEONAV IoT business plan. Expected revenues are promising: eg, in 2024 24m€ and 50 new jobs created. Ambition is to bring European industry as leader in LBS and drones Markets.