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Ultrasound Ultrafast imaging for the neonatalbrain: the race for early quantitative biomarkers of brain lesions| title | Ultrasound Ultrafast imaging for the neonatalbrain: the race for early quantitative biomarkers of brain lesions |
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| start_date | 2023/03/06 |
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| schedule | 11h |
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| online | no |
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| visio | https://us02web.zoom.us/j/83888993899?pwd=ZFZ0STdQVmhESkI2bnVabWRWV0RpQT09 |
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| location_info | amphithéâtre & zoom |
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| summary | Assessing the severity of cerebral insults tothe brain of neonates can be particularly challenging as almost no behavioralinformation can be obtained on these very peculiar patients. The most severelesions are detected with structural imaging using MRI or BMode ultrasoundimaging and are generally associated with very poor outcome and irreversibleserious disabilities. The milder lesions, however, are much more subtle tocapture, if not undetectable, with these structural imaging modalities, and canproduce a very diverse clinical picture ranging from disabilities to normalneurodevelopment.
It is generally hypothesized that reversiblefunctional losses precede the observable irreversible structural insults, andthat very early detection of changes in the brain could help develop protectingstrategies effective before the lesions are too severe to be reversible. Thosechanges may span mechanical properties of the brain tissue, perfusion defectsor modulation of the brain activity. I will present imaging tools based onultrafast ultrasound imaging that we have developed and tested with the team ofPr Olivier Baud and Pr Valérie Biran at Hospital Robert Debré, in order todetect these early changes. This ultrafast ultrasound imaging enables to bevery sensitive to tissue elasticity, very slow blood flow and vascularresistivity, cerebral activity and much more, all relevant to perinatal pathologies.
First we have shown the feasibility ofelasticity imaging and cerebral vascular resistivity imaging in the brain ofpreterm and term neonates, and gathered quantitative data describing theevolution of those contrasts with post-natal age, both for extremely preterm(<28 weeks) and very preterm (28< age < 32 weeks) neonates, as well asfor term controls. We were also able to show that those two parameters could bepredictive of certain white matter brain lesions detected later with MRI.
Assessing the elasticity/integrity of the braintissue or the function of the cerebral vasculature is valuable, but earlycharacterization of the brain function might be even more sensitive andpredictive of future cerebral dysfunction: in particular, functional connectivityis envisioned to provide early markers of cognitive impairments. We leveragedthe huge sensitivity of ultrafast imaging to slow blood flow to image brainactivity indirectly, a technique called fUS imaging (functional ultrasoundimaging), the same way fMRI uses hemodynamic signal to derive brain activityimages. We used fUS imaging to evaluate resting-state functional connectivityin term and preterm neonates and were able to show interhemisphericconnectivity at an early stage in very preterm newborns. Furthermore, fUS highspatial resolution enabled to build fine-grain homotopic connectivity maps,based on correlations between mirror pixels, which revealed underlyingstructures, such as the white/grey matter boundary in the cortex. Finally,resting-state connectivity could be assessed dynamically showing a significantoccurrence decrease of thalamo-cortical networks for very preterm neonates(N=6) as compared to control term newborns (N=4), a subtle difference thatwould have stayed concealed with a more classical static connectivityanalysis. We feel that fUS is somehow unique in the landscape of neonatalbrain imaging as being relatively low cost, bedside, and having 250µm spatialresolution and <1s temporal resolution. We will pursue the development ofneonatal fUS with a larger study (called CONEXUS) in Hospital Robert Debré tostudy the emergence of functional networks in the early days of life and try toidentify abnormal neurodevelopmental trajectories. |
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| responsibles | Blancho |
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Workflow history| from state (1) | to state | comment | date |
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| submitted | published | | 2023/03/01 15:47 UTC |
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