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Imaging the brain with ultrasound full-waveform inversion

Lead Research Organisation: Imperial College London
Department Name: Earth Science and Engineering

Abstract

Rapid brain imaging is central to the diagnosis and treatment of acute neurological conditions - for example stroke or head trauma. Existing imaging methods require large, immobile, high-power instruments that are near-impossible to deploy outside specialized environments, leading to unnecessarily delayed diagnosis and treatment, and consequent increased disability and higher fatality rates. This project will create a device that can be simply and rapidly applied to any patient, any time, any place, exploiting advances that have already revolutionised imaging in geophysics. We will image the brain using ultrasound waves, transmitted across the head, applying advanced computer modelling to remove the distorting effects of the skull, thereby enabling high-resolution high-contrast imaging of the brain unachievable by conventional ultrasound.

The petroleum industry has spent large sums developing advanced geophysical algorithms to image oil and gas deposits in three dimensions. Foremost among these is "full-waveform inversion" (FWI), a computationally intensive technique in which accurate modelling of soundwave propagation through a three-dimensional object is used to recover the detailed internal properties of that object. This project will adapt and transfer that technology across disciplines so that it can be applied directly for medical imaging of the brain leading to cheaper, faster, more-accurate clinical diagnosis and treatment.

The main existing technologies used in three-dimensional medical imaging are magnetic resonance imaging (MRI), x-ray computed tomography (CT), and reflection ultrasound. MRI is high resolution and high accuracy but is time consuming, expensive and immobile, and it cannot be applied safely without a preliminary detailed investigation to ensure the absence of magnetic bodies within any new patient. X-ray CT is cheaper and faster, but it is typically lower resolution, with poor soft-tissue contrast, and it uses harmful ionising radiation. Conventional reflection ultrasound is cheap, fast, portable and universally safe, but it uses high-frequency ultrasound that has limited penetration, and that is especially attenuated and distorted by the bones of the skull. Consequently, existing ultrasound technology is unable to image the adult brain successfully within an intact human skull.

Ultrasound at frequencies below those normally used for imaging does however have the penetration required to travel right across the head. Full-waveform inversion is able to produce accurate high-resolution images using lower-frequency data than is possible using conventional techniques; FWI is also able to compensate accurately for all the distortions generated by the skull. Consequently, the combination of low-frequency transmitted ultrasound with full-waveform inversion is able to produce well-resolved accurate images of the entire human brain. The potential of this approach has already been demonstrated in computer simulations; this project now seeks to replicate that success in the laboratory.

Safe, fast, universally applicable, deployable continuously, and above all portable by paramedics, our device and our approach aim to revolutionise brain imaging, in health and disease. The technology has particular relevance to stroke - globally the second-commonest cause of premature death and a major, growing cause of adult disability - and to brain imaging in resource-limited and inaccessible environments.

Publications

10 25 50

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Cueto C (2021) Spatial Response Identification for Flexible and Accurate Ultrasound Transducer Calibration and its Application to Brain Imaging. in IEEE transactions on ultrasonics, ferroelectrics, and frequency control

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Cueto C (2022) Spatial Response Identification Enables Robust Experimental Ultrasound Computed Tomography. in IEEE transactions on ultrasonics, ferroelectrics, and frequency control

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Cueto C (2022) Stride: A flexible software platform for high-performance ultrasound computed tomography. in Computer methods and programs in biomedicine

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Yan J (2023) Fast 3D Super-Resolution Ultrasound With Adaptive Weight-Based Beamforming. in IEEE transactions on bio-medical engineering

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Graham M (2023) Latent Transformer Models for out-of-distribution detection in Medical Image Analysis

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Rehman M (2023) Federated learning for medical imaging radiology in The British Journal of Radiology

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Nelson APK (2024) The minimal computational substrate of fluid intelligence. in Cortex; a journal devoted to the study of the nervous system and behavior

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Jiang Z (2024) An Ultrasound Array of Emitter-Receiver Stacks for Microbubble-Based Therapy in IEEE Transactions on Biomedical Engineering

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Wang B (2024) Broad Elevation Projection Super-Resolution Ultrasound (BEP-SRUS) Imaging With a 1-D Unfocused Linear Array in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

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Tudosiu P (2024) Realistic morphology-preserving generative modelling of the brain in Nature Machine Intelligence

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Watkins H (2025) Neuradicon: Operational representation learning of neuroimaging reports. in Computer methods and programs in biomedicine

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Rondina J (2025) Artificial intelligence and stroke imaging. in Current opinion in neurology

 
Description Our high-level objective was to provide proof of principle for a new method of imaging the adult human brain within the skull - using ultrasound combined with an advanced computational approach originally developed to image within the Earth. In principle, this approach is fast, portable, low-cost, and of an equivalent resolution and quality to magnetic resonance imaging (MRI). Specifically, in this award, our aim was to acquire laboratory data using artificial models of the human head to test the feasibility of the concept and to aid the design of a 3D scanner suitable for application in the laboratory on a live volunteer. We were able to demonstrate that the method works on realistic models, and we have designed a prototype device for use on real people.
Exploitation Route Our technology has especial relevance for stroke and acute head trauma, and for monitoring of the brain within intensive-care and high-dependency unity units, in the operating theatre, in accident and emergency departments, within ambulances, and in remote, difficult or resource-constrained environments. Significant further research will be required to bring this technology into routine clinical practice. The technology needs to be proven on live volunteers. It needs to be miniaturised, made robust and tested against current clinical alternatives. Ultimately it needs to be commercialised and adopted into clinical practice across health services in the UK and worldwide.
Sectors Healthcare

 
Description Although the wider research programme is at an early stage, these encouraging results have stimulated discussions with early-stage commercial investors leading to an offer of £500k from our commercial partners to enable the university research team to purchase a new generation of ultrasound sensors.
First Year Of Impact 2022
Sector Healthcare
Impact Types Societal

Economic

 
Description A high-precision non-invasive multi-focal bidirectional electro-acoustic neural interface
Amount £4,192,945 (GBP)
Funding ID SCNI-PR01-P02 
Organisation Advanced Research and Innovation Agency (ARIA) 
Sector Public
Country United Kingdom
Start 01/2025 
End 12/2028
 
Description Imaging the brain with ultrasound full-waveform inversion
Amount £3,481,824 (GBP)
Funding ID EP/X033651/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 04/2023 
End 06/2027
 
Description Presentations at Workshop MUST2022 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Two presentations titled 'Using uncertainty to estimate imaging errors induced by variable density, attenuation, and position' and 'High-performance full-waveform inversion using Stride and Devito: a practical view' have been given at the workshop to a diverse audience covering academic, industry partners, clinicians, etc. This knowledge exchange activity engaged by project members led to increased interests in our project outcome and sparkled increased engagement requests from other academic institutions, industry sectors and potential funders.
Year(s) Of Engagement Activity 2022