OCEAN: One-stop-shop microstructure-sensitive perfusion/diffusion MRI: Application to vascular cognitive impairment

Lead Research Organisation: University of Leeds
Department Name: Sch of Computing

Abstract

The term "dementia" is used to describe a syndrome that results, initially, in cognitive function impairment and in many cases, a descending staircase of psychological dysfunction, leading eventually to death.
It is a major socio-economic challenge with care costs approaching 1% of global GDP. Several conditions that lead to serious loss of cognitive ability are grouped under this syndrome, including Alzheimer's disease (AD), Vascular Dementia (VaD), Frontotemporal Dementia, etc. A high publicity announcement was made in 2012, by the Prime Minister, emphasising the high priority that should be given to dementia-related research and that funding will more than double in the immediate future, to partially remedy the fact that the overwhelming impact of the syndrome has been over-looked (Guardian, 26/3/12). On Dec 2013, the G8 Summit hosted in London brought together G8 ministers, researchers, pharmaceutical companies, and charities to develop co-ordinated global action on dementia.

Dementia has marked adverse effects on the quality of life of tens of millions of people (both patients and carers) and exerts tremendous pressure on healthcare systems, especially when clear trends towards an ageing population, changing environmental influences and contemporary lifestyle choices are considered. Ca. 35M people suffer from dementia worldwide, a figure to quadruple by 2050. Europe and North America share a disproportionally high burden: the effects of ageing are particularly stark for these regions, exacerbating the healthcare provision implications.

The Clinical Relevance: Vascular Cognitive Impairment (VCI). VCI defines alterations in cognition attributable to cerebrovascular causes, ranging from subtle or fixed deficits to full-blown dementia. VCI is a wide and accepted term referring to the "syndrome with evidence of clinical stroke or subclinical vascular brain injury and cognitive impairment affecting at least one cognitive domain", with resulting VaD being its most severe form. VaD is responsible for at least 20% of dementias, second only to AD, with a prevalence doubling every 5. 3 years. Several trials examined cholinesterase inhibitors for the treatment of vascular dementia, but the benefits are very modest, except in the individuals with a combination of AD and VaD. Vascular changes result in white matter (WM) damage (leukoaraiosis), which profoundly affect the fidelity of the information transfer underlying brain function and cognitive health8.

Cerebral Magnetic Resonance Imaging (MRI) of Diffusion and Perfusion. MRI is a medical imaging technique affording non-invasive investigation of anatomy and tissue function, which is particularly suited to studying cognitive disorders due to its sensitivity and reliability. Our main interest is to characterise vascular and non-vascular tissues using quantitative diffusion and perfusion MR. Our overall aim is to characterise and quantify early differential alterations in brain blood transport and subsequent microstructural tissue damage using one-stop-shop perfusion/diffusion MR GSI incorporating novel MR signal models and optimal MR sequence design based on new human brain histomorphometric data in health and disease.

Planned Impact

Dementia already is one of society's biggest medical challenges. No cures are so far available. Yet, research is intense and strong candidate therapies are on the horizon. Given the variety of causes and aetiologies of dementia, reliable identification of the underlying pathologies is a requisite for therapy effectiveness. Differential diagnosis is therefore key. Effectiveness, also, is greatly modulated by the level of disease progression in individuals. Even where outright cure is unrealistic, evidence already suggests that lifestyle changes and other treatments can delay the progression of symptoms, provided these are identified sufficiently early. This is of enormous significance to sufferers and their families. Societal economic implications aside, the quality of life benefits for sufferers from prolonged independence, and the emotional and financial alleviation for families and carers are substantial. Early diagnosis is therefore key. It is in the provision of differential and early diagnosis that the technologies developed within OCEAN can have a serious impact.

Knowledge management and exchange with other key EU-, RCUK- and NIHR-funded initiatives. To maximise synergies with other relevant initiatives and ensure knowledge cross-fertilisation, we set up a Scientific Advisory Board (SAB) experienced in relevant engineering and physical sciences and with a track record of clinical translation of research results. This cadre of academics includes world class scientists in the areas of MR diffusion imaging, medical image computing, and computational modelling.

Industrial engagement and commercial take-up. Several companies are committed to OCEAN thus incorporating a technological and exploitation dimension from the outset of the project. Companies were selected to cover all key areas and technologies in OCEAN where exploitable outcomes or collaborations are anticipated; previous or ongoing research collaborations were also accounted. Statements of support are appended.
Microscopy data will be made available to community. OCEAN is committed to making the multimodal image database of light and electron microscopy and 7T MRI brain tissue data available online by the end of the project. We shall also make available the quantitative statistics of microstructural composition and properties. Access to this unique resource will be made online via a project portal built and
managed jointly by SITraN and CISTIB-INSIGNEO.

MR GSI Image Analysis & Visualisation Tool. Once validation of the modelling methodologies has taken place, these tools will be made available to the wider clinical and research community. We plan to prototype an MR GSI Image Analysis & Visualisation Tool based on GIMIAS (www.gimias.org), an open-source platform developed at CISTIB.

From proof of principle and feasibility to demonstration of clinical impact. Once we have established the feasibility of MR GSI and evaluated it in simulation, phantom studies and short series of volunteers, we will seek follow-up funding streams to conduct a clinical proof-of-concept in a large cohort. This will be designed to assess the effectiveness of MR GSI for early detection of VCI-related disorders and, importantly, the differentiation of pathological mechanisms that is essential for therapy formulation.

Engaging patient and public in research through the Dementia Public and Patient Involvement (PPI) group. We have partnered with the Alzheimer's Society, which will contribute two volunteers in our Scientific and Clinical Advisory Boards, respectively. Funds have been set apart according to the INVOLVE guidance to facilitate the participation of these volunteers.

Publications

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Lassila T (2018) Screening for Cognitive Impairment by Model-Assisted Cerebral Blood Flow Estimation. in IEEE transactions on bio-medical engineering

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Luo X (2022) Guest Editorial Special Section on Surgical Vision, Navigation, and Robotics in IEEE Transactions on Medical Robotics and Bionics

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Fathi Kazerooni A (2020) Diffusion MRI for Assessment of Bone Quality; A Review of Findings in Healthy Aging and Osteoporosis. in Journal of magnetic resonance imaging : JMRI

 
Description Deep subcortical lesions (DSCL) of the brain, are present in ~60% of the ageing population, and are linked to cognitive decline and depression. DSCL are associated with demyelination, blood brain barrier (BBB) dysfunction, and microgliosis.
Computational models of biophysical tissue properties have been widely used in diffusion MRI (dMRI) research to elucidate the link between microstructural properties and MR signal formation. For brain tissue, the research community has developed the so-called Standard Model (SM) that has been widely used. Biophysical tissue models have the potential to detect specific alterations of the brain tissue. However, in clinically applicable acquisition protocols, the inverse problem that recovers the SM parameters from a set of MR diffusion measurements using pairs of short pulsed field gradients was shown to be ill-posed.

The OCEAN project has tackled this problem with two complementary strategies: Inclusion of more specific prior information of the tissue and exploitation of more complex dMRI acquisition protocols.

We acquired immunohistochemistry histological data of axons, astrocytes, myelin, and capillaries in deep subcortical white matter from a population of 90 subjects, stratified into three groups of 30 subjects each, in relation to the presence of age-associated deep subcortical lesions. This database has been made publicly available [Data in brief 23 (2019): 103762]. We developed adapted analysis methods to characterize the distribution of sizes and volumetric densities of axons, astrocytes, and myelin [NeuroImage 179 (2018): 275-287], and capillaries [NeuroImage: Clinical 23 (2019): 101839]. We also assess statistically significant differences found between the three groups.
In agreement with previous literature, our results indicate that white matter lesions are related with a decrease in the myelinated axons fraction and an increase in astrocytic fraction, while no statistically significant changes occur in axonal mean fraction. In addition, we investigated the correlation of microglial markers, ramification and size of cells, and lesion [PloS one 14.1 (2019) e0210888].

To incorporate prior information on the distribution along the population of the SM parameters (tissue properties), we developed a Bayesian framework softening the parameter estimation ill-posedness [Magnetic resonance in medicine 82.4 (2019): 1553-1565]. The population-based prior produced substantially more accurate and robust parameter estimates for clinically feasible protocols, without introducing any evident bias.

Following the second strategy, we extended the SM to dMRI acquisition with double diffusion-encoding and more general multidimensional-diffusion encoding. We analytically demonstrate that double diffusion-encoding provides invariant information non-accessible from convencional (single diffusion encoding) sequences, which solves the previously reported degeneracies making the model parameter estimation injective (well-posed). In silico experiments show that DDE reduces the bias and mean square error of the estimation along the whole feasible region of 5D model parameter space [Magnetic resonance in medicine 82.1 (2019): 395-410].

Motivated by these positive results, we have also investigated the determination of optimal acquisition protocols for the SM from the full tensorial space of multidimensional diffusion encoding [In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 617-625. Springer, Cham, 2019]. Our results suggest that the optimal dMRI acquisition is a combination of only single and double diffusion encoding.

Brain blood microcirculation is an important factor in early diagnosis of lesion. An emerging topic in diffusion magnetic resonance is imaging blood microcirculation alongside water diffusion using the intravoxel incoherent motion (IVIM) model. The MRI signal incorporating simultaneously diffusion and perfusion is determined by the generalised Bloch-Torrey Equation. We developed a finite element solver for this equation [Computational Diffusion MRI. Springer, Cham, 2016. 3-14] allowing us to simulate different scenarios. We investigated the combination of IVIM and diffusion tensor imaging (IVIM-DTI), proposing a robust approach for simultaneous diffusion and pseudo-diffusion tensor imaging [Magnetic resonance in medicine 79.4 (2018): 2367-2378]. Our Bayesian method incorporating a Gaussian prior was less sensitive to noise and delivered more accurate
estimates of IVIM-DTI parameters compared to previous methods.
Exploitation Route The histological databases that we have created have been made publicly available online [Data in brief 23 (2019): 103762].
The expertise obtained by Santiago Coelho during his fruitful PhD associated to the OCEAN project, has been transferred to NYU Langone Health (USA) where he has recently started his first postdoc.
Finally, the expertise, data and methods developed during the project were instrumental for the design of the BQ Minded project, funded by European Union's Horizon 2020
research and innovation programme under the Marie Sklodowska-Curie grant agreement No 764513. The transference of the methodologies from neurology to cardiology is currently supporting two other PhD students.
Sectors Digital/Communication/Information Technologies (including Software),Healthcare

URL http://www.ocean-mri.org/
 
Description The project has led to a collaboration with a company in the Sheffield area that develops advanced data sharing middlewares. We created a joint video explaining, in lay terms, the impact of this technology and our group's research in this context. The video is available: https://www.youtube.com/watch?v=VG8lSGWIbY0&list=PLup8cbzcK-NOf4ZTeYNJhPq_dmvl42_ot The work has also led to the training of a PhD student, Santiago Coelho https://ethos.bl.uk/OrderDetails.do?did=2&uin=uk.bl.ethos.798018 who visited the group of Dimitry Novikov https://med.nyu.edu/faculty/dmitry-novikov in NYU Langone Health. Santiago is now doing a postdoctoral stay in that group. The project inspired the BQ-MINDED Marie Curie Training Network (https://cordis.europa.eu/project/id/764513) activities led by Leeds (we moved from Sheffield to Leeds in 2018) that led to the PhD funding for Mojtaba Lashgari and Shokoufeh Golshani. This project extended work in OCEAN on brain MR diffusion to cardiac MR diffusion. This work is under review and will reported in the next round.
First Year Of Impact 2015
Sector Healthcare
Impact Types Societal,Economic

 
Description MICCAI Code of Conduct
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
Impact Prof AF Frangi, as General Chair of MICCAI 2018 in Granada, Spain, for the first time developed and implemented a Code of Conduct that required to be agreed by any attendee to the meeting. Unfortunately, we had a serious case as part of the meeting in 2018, which was handled and led to a public annoucement http://www.miccai.org/news/2019/09/26/public-statement-from-the-miccai-board-violation-of-the-code-of-conduct-at-miccai-2018. We believe that members of MedIAN have contributed to deal with a better equality and diversity in our main conference. As a professional scientific society, the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) is committed to providing an atmosphere that encourages the free expression and exchange of ideas. Consistent with this commitment, it was the purpose of this Code of Conduct to detail how MICCAI envisions that participants in MICCAI activities enjoy a safe, welcoming, and inclusive environment, free from threatening conduct, harassment, bullying, and intimidation. We believe the UK community has contributed to make this possible in a very instrumental way.
URL http://www.miccai.org/about-miccai/code-of-conduct/
 
Description Breakthroughs in Quantitative Magnetic resonance ImagiNg for improved DEtection of brain Diseases
Amount € 3,861,067 (EUR)
Funding ID 764513 
Organisation European Commission H2020 
Sector Public
Country Belgium
Start 01/2018 
End 12/2021
 
Description CardioX: integrated and quantitative cardiac imaging reports for Precision Cardiology within LTHT
Amount £79,830 (GBP)
Funding ID POC 000041 
Organisation Grow MedTech 
Sector Academic/University
Country United Kingdom
Start 10/2019 
End 09/2020
 
Description Educational Stipend for Students
Amount $450 (USD)
Organisation International Society for Magnetic Resonance in Medicine (ISMRM) 
Sector Charity/Non Profit
Country United States
Start 04/2017 
End 04/2017
 
Description Healthcare Impact Partnership
Amount £932,050 (GBP)
Funding ID EP/P023509/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 10/2017 
End 09/2020
 
Description INSILEX: Precision Computational Medicine for \textit{in silico} Trials of Medical Devices
Amount £2,760,000 (GBP)
Funding ID CiET1819/19 
Organisation Royal Academy of Engineering 
Sector Charity/Non Profit
Country United Kingdom
Start 05/2018 
End 04/2029
 
Description Learned Society Fund 16/17 - Funding for conference/workshop attendance
Amount £500 (GBP)
Organisation University of Sheffield 
Department Learned Societies Fund (University of Sheffield)
Sector Charity/Non Profit
Country United Kingdom
Start 04/2017 
End 04/2017
 
Description OCEAN: One-stop-shop microstructure-sensitive perfusion/diffusion MRI: Application to vascular cognitive impairment
Amount £58,452 (GBP)
Funding ID EP/M006328/2 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 11/2018 
End 06/2019
 
Description Royal Society International Exchange
Amount £12,000 (GBP)
Organisation The Royal Society 
Sector Charity/Non Profit
Country United Kingdom
Start 03/2015 
End 02/2016