Transcranial super-localization imaging of the adult brain in the Best Of EMIM Talks 2020

Transcranial super-localization imaging of the adult brain in the Best Of EMIM Talks 2020

Charlie Demené, researcher in our lab Physics for Medicine Paris and associate professor at ESPCI Paris-PSL, has received an award at the European Molecular Imaging Meeting which was held virtually in August 24-28, 2020: his presentation has been selected in the Best Of EMIM Talks 2020 in the session Imaging Technologies. The presented work, entitled “Transcranial Ultrasound Localization Microscopy reveals sub-resolution blood dynamics in aneurysms and arterial malformations in the adult human brain”, marks a leap in neuroimaging with the first demonstration of Ultrasound Localization Microscopy (ULM) in clinics.

Imaging the brain vasculature is essential to diagnose and monitor neurovascular pathologies. Currently, clinicians rely on CT (computed tomography) and MRA (magnetic resonance angiography). These techniques are extremely costly, and fail to capture small features and the dynamics of vascular flows.

Ultrasound Localization Microscopy (ULM) enables to image the brain vasculature at high sensitivity and down to the micron scale by combining ultrafast ultrasound with the injection of clinically-approved and non-ionizing contrast agents. This technique adresses the challenge of transcranial imaging – the skull is an obstacle to conventional ultrasound imaging of the brain, and provides an unpredecented spatiotemporal resolution. We validated the concept of ULM in rodents in 2015. Here, Charlie Demené and his team transpose it for the very first time to human adult patients, demonstrating the tremendous phenomenal capacities of ULM for cerebrovascular diagnosis.

For instance, a 100-micron size aneurysm was detected on ULM images. Besides, within this aneurysm, the blood flow directions and speeds, unaccessible with CT and MRA, were fully characterized. With ULM, all these highly-resolved and quantitative data are acquired within tens of seconds at the patient’s bedside. This remarkable achievement could transform the diagnosis and management of patients in neurology departments. 

This first translation of ULM to clinical settings required several technical developments, including new acquisition sequences, and algorithms for correcting motions and skull-induced aberrations. Next, Charlie Demené will aim at developing fast processing methods to display vascular features in real-time during the examination.