A biophysical simulation framework for magnetic resonance microstructure imaging
Lead Research Organisation:
University College London
Department Name: Computer Science
Abstract
This project develops a simulation system for the MR signal in biological tissue and its dependence on molecular dynamics as influenced by tissue microarchitecture and composition. The system is an essential tool in the development of next-generation non-invasive imaging techniques. Specifically, it underpins the development and translation of the emerging paradigm of microstructure imaging. The paradigm uses mathematical models, which relate the MR signal to underlying tissue properties, to estimate and map those properties by fitting the models voxel-by-voxel to combinations of appropriately sensitised image data. The approach provides much greater biological specificity than standard MRI, thus enhancing diagnosis and treatment planning.
The current generation of microstructure-imaging techniques is now starting to find widespread application in clinical studies. Prominent examples include NODDI for neuroimaging and VERDICT for cancer imaging, both developed by the investigators on this project. Those techniques are based entirely on diffusion MRI and their extension and refinement within that single contrast mechanism continues rapidly. However, a new generation of microstructure-imaging technique is just beginning to emerge that draws on multiple sources of MR contrast, for example combining diffusion MRI with relaxometry, susceptibility, etc. Such techniques offer great promise in the decades to come for the realisation of 'virtual histology' avoiding invasive procedures, such as biopsy, across a wide range of medical applications.
EPSRC grant EP/E064280/1, which finished in 2011, developed the current state-of-the-art simulation system within the Camino toolkit. That system underpinned the early development of the microstructure-imaging paradigm, which led to current techniques like NODDI and VERDICT. However, the current system is insufficient to evaluate even current microstructure imaging techniques, because it excludes key effects that influence the diffusion MR signal. Moreover, its implementation limits the simulation to molecular diffusion as the only source of MR contrast, which fundamentally prevents its extension for validation of next-generation techniques.
The new simulation system will use more sophisticated underlying models of tissue geometry and MR signal generation enabling it to support both modern diffusion-based microstructure-imaging applications and future multi-modal techniques. It provides a unique and invaluable validation tool allowing us to realise the full potential of quantitative non-invasive imaging in medicine and beyond. Within the project we demonstrate the new system by evaluating the performance of NODDI and VERDICT under a wide range of conditions. We also test two early examples of multi-modal microstructure imaging techniques paving the way for their robust development and eventual clinical translation.
The current generation of microstructure-imaging techniques is now starting to find widespread application in clinical studies. Prominent examples include NODDI for neuroimaging and VERDICT for cancer imaging, both developed by the investigators on this project. Those techniques are based entirely on diffusion MRI and their extension and refinement within that single contrast mechanism continues rapidly. However, a new generation of microstructure-imaging technique is just beginning to emerge that draws on multiple sources of MR contrast, for example combining diffusion MRI with relaxometry, susceptibility, etc. Such techniques offer great promise in the decades to come for the realisation of 'virtual histology' avoiding invasive procedures, such as biopsy, across a wide range of medical applications.
EPSRC grant EP/E064280/1, which finished in 2011, developed the current state-of-the-art simulation system within the Camino toolkit. That system underpinned the early development of the microstructure-imaging paradigm, which led to current techniques like NODDI and VERDICT. However, the current system is insufficient to evaluate even current microstructure imaging techniques, because it excludes key effects that influence the diffusion MR signal. Moreover, its implementation limits the simulation to molecular diffusion as the only source of MR contrast, which fundamentally prevents its extension for validation of next-generation techniques.
The new simulation system will use more sophisticated underlying models of tissue geometry and MR signal generation enabling it to support both modern diffusion-based microstructure-imaging applications and future multi-modal techniques. It provides a unique and invaluable validation tool allowing us to realise the full potential of quantitative non-invasive imaging in medicine and beyond. Within the project we demonstrate the new system by evaluating the performance of NODDI and VERDICT under a wide range of conditions. We also test two early examples of multi-modal microstructure imaging techniques paving the way for their robust development and eventual clinical translation.
Planned Impact
Impact of the project arises through facilitation of the development of accurate and well-validated microstructure-imaging techniques.
Microstructure imaging promises advances in understanding and management of some of the biggest challenges facing 21st century healthcare; most directly: neurological diseases and cancer. The UK dementia platform estimates annual socioeconomic costs of dementia in Britain at around £17B. A treatment prolonging independent life of the average dementia patient by just one year would save around £1B per year in care costs as well as boosting the UK economy through revenue from the treatment if realised through its pharmaceutical industry and thriving community of related SMEs. The potential of microstructure imaging is to detect and classify disease earlier, enabling appropriate and early intervention, and to stage disease more accurately supporting effective treatment development and deployment. Annual costs of cancer have similar scale. Microstructure imaging promises rapid, non-invasive, and specific early diagnosis, supporting precision medicine and treatment delivery with similar socio-economic impact.
Current microstructure-imaging techniques are rapidly becoming part of the mainstream battery of imaging techniques used routinely in clinical studies and exams. NODDI is a key component in large-scale data-collection initiatives, such as the 1946-cohort imaging project (~1000 subjects), and most current large-scale brain imaging projects, such as the UK Biobank (100,000 subjects) and the Human Connectome Project (1000s of subjects), use protocols designed to support the technique. The more recent VERDICT technique is already a key component of large-scale prostate-cancer imaging initiatives at UCLH, such as the PROMIS (1000s of subjects) and INNOVATE (100s of subjects) projects, and other institutions are preparing to follow suit.
Despite their success, intense debate continues in the technical imaging-science community about the mathematical models and acquisition protocols at the heart of the techniques. The debate arises from incomplete understanding of both the biophysical sources of MR contrast and the effects of simplifying modelling assumptions that are essential to make stable front-line techniques. The simulation tool we propose here advances our understanding in these key questions providing confidence in the conclusions drawn from large-scale studies and clinical trials, as well as highlighting areas of weakness in current techniques to ameliorate for future generations.
Microstructure imaging promises advances in understanding and management of some of the biggest challenges facing 21st century healthcare; most directly: neurological diseases and cancer. The UK dementia platform estimates annual socioeconomic costs of dementia in Britain at around £17B. A treatment prolonging independent life of the average dementia patient by just one year would save around £1B per year in care costs as well as boosting the UK economy through revenue from the treatment if realised through its pharmaceutical industry and thriving community of related SMEs. The potential of microstructure imaging is to detect and classify disease earlier, enabling appropriate and early intervention, and to stage disease more accurately supporting effective treatment development and deployment. Annual costs of cancer have similar scale. Microstructure imaging promises rapid, non-invasive, and specific early diagnosis, supporting precision medicine and treatment delivery with similar socio-economic impact.
Current microstructure-imaging techniques are rapidly becoming part of the mainstream battery of imaging techniques used routinely in clinical studies and exams. NODDI is a key component in large-scale data-collection initiatives, such as the 1946-cohort imaging project (~1000 subjects), and most current large-scale brain imaging projects, such as the UK Biobank (100,000 subjects) and the Human Connectome Project (1000s of subjects), use protocols designed to support the technique. The more recent VERDICT technique is already a key component of large-scale prostate-cancer imaging initiatives at UCLH, such as the PROMIS (1000s of subjects) and INNOVATE (100s of subjects) projects, and other institutions are preparing to follow suit.
Despite their success, intense debate continues in the technical imaging-science community about the mathematical models and acquisition protocols at the heart of the techniques. The debate arises from incomplete understanding of both the biophysical sources of MR contrast and the effects of simplifying modelling assumptions that are essential to make stable front-line techniques. The simulation tool we propose here advances our understanding in these key questions providing confidence in the conclusions drawn from large-scale studies and clinical trials, as well as highlighting areas of weakness in current techniques to ameliorate for future generations.
Publications
Ganepola T
(2018)
Using diffusion MRI to discriminate areas of cortical grey matter.
in NeuroImage
Ianus A
(2021)
Mapping complex cell morphology in the grey matter with double diffusion encoding MR: A simulation study.
in NeuroImage
Afzali M
(2021)
SPHERIOUSLY? The challenges of estimating sphere radius non-invasively in the human brain from diffusion MRI.
in NeuroImage
Palombo M
(2020)
SANDI: A compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI
in NeuroImage
Alfaro-Almagro F
(2018)
Image processing and Quality Control for the first 10,000 brain imaging datasets from UK Biobank.
in NeuroImage
Gyori N
(2021)
On the potential for mapping apparent neural soma density via a clinically viable diffusion MRI protocol
in NeuroImage
Palombo M
(2018)
Insights into brain microstructure from in vivo DW-MRS.
in NeuroImage
Alexander DC
(2017)
Image quality transfer and applications in diffusion MRI.
in NeuroImage
Description | The SANDI model: Palombo NIMG 2020. And neural soma imaging: Gyori NIMG 2021. Plus usage of machine learning for microstructure estimation from MRI: Gyori MRM 2021. |
Exploitation Route | The SANDI technique can be used in neuroscience and clinical neurology studies. Developers of future microstructure imaging techniques will use the advances here on parameter estimation and mapping. |
Sectors | Healthcare Pharmaceuticals and Medical Biotechnology |
Description | The system developed in this award has underpinned fundamental advances in microstructure imaging that has led to techniques, such as VERDICT (Panagiotaki Inv. Rad. 2015; Johnston Radiology 2019; Singh Radiology 2022), which is in clinical use for assessment of prostate cancer, and more recent developments of placental MRI techniques that reveal placenta malformation early in pregnancy (Slater MRM 2019; Cromb preprint - https://pubmed.ncbi.nlm.nih.gov/38343847/). It also provides essential validation for widely used neuroimaging techniques such as NODDI (Zhang NIMG 2012). |
First Year Of Impact | 2019 |
Sector | Healthcare |
Impact Types | Societal |
Description | A biophysical simulation framework for magnetic resonance microstructure imaging |
Amount | £665,423 (GBP) |
Funding ID | EP/N018702/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2016 |
End | 03/2019 |
Description | AI-powered brain microstructure imaging |
Amount | £1,076,148 (GBP) |
Funding ID | MR/T020296/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2020 |
End | 06/2021 |
Description | Anatomy driven brain connectivity mapping |
Amount | £775,427 (GBP) |
Funding ID | EP/L022680/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2014 |
End | 05/2017 |
Description | Assessing Placental Structure and Function by Unified Fluid Mechanical Modelling and in-vivo MRI |
Amount | £1,124,021 (GBP) |
Funding ID | EP/V034537/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2022 |
End | 07/2024 |
Description | Developing single cell resolution 3D models of immune surveillance in cancer |
Amount | £165,263 (GBP) |
Funding ID | NS/A000069/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 01/2018 |
End | 12/2020 |
Description | Direction measurements of microstructure from MRI |
Amount | £1,600,000 (GBP) |
Funding ID | EP/G007748/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2008 |
End | 09/2014 |
Description | EPSRC Centre for Doctoral Training in Intelligent, Integrated Imaging In Healthcare (i4health) |
Amount | £6,034,274 (GBP) |
Funding ID | EP/S021930/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 08/2019 |
End | 03/2028 |
Description | Enabling Clinical Decisions From Low-power MRI In Developing Nations Through Image Quality Transfer |
Amount | £1,035,545 (GBP) |
Funding ID | EP/R014019/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 02/2018 |
End | 01/2022 |
Description | JPND: Stratification of presymptomatic amyotrophic lateral sclerosis: the development of novel imaging biomarkers |
Amount | € 1,600,000 (EUR) |
Funding ID | MR/T046473/1 |
Organisation | JPND Research |
Sector | Academic/University |
Country | Global |
Start | 06/2020 |
End | 07/2023 |
Description | Medical image computing for next-generation healthcare technology |
Amount | £1,500,000 (GBP) |
Funding ID | EP/M020533/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2015 |
End | 05/2020 |
Description | National facility for in vivo MRI of human tissue microstructure |
Amount | £2,900,000 (GBP) |
Funding ID | EP/M00855X/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2014 |
End | 06/2019 |
Description | Next generation MRI brain imaging platform for dementia research: from microstructure to function |
Amount | £1,500,000 (GBP) |
Funding ID | MR/M009106/1 |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 07/2014 |
End | 07/2019 |
Description | Workshop on diffusion MRI meets diffusion MRS. Combining DW-MRI and DW-MRS: a multi-scale approach to microstructure imaging |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Title: Diffusion MRI meets diffusion MRS. Combining DW-MRI and DW-MRS: a multi-scale approach to microstructure imaging Organizers: Marco Palombo and Hui Zhang Topic: development of new methods for brain microstructure non-invasive imaging Aim: to create a stimulating forum where experts in diffusion-weighted MRI (DW-MRI) and spectroscopy (DW-MRS) techniques can discuss the best way to combine two techniques of complementary scale to improve the non-invasive brain tissue microstructure characterization. To scope out the key research challenges and opportunities associated with this multi-scale approach to microstructure imaging. Motivation: Up to now, diffusion-weighted magnetic resonance community has been working primarily on the development of either DW-MRI or DW-MRS techniques separately, without exploiting the complementarity between them to create a new unified technique which can perform much better than both on their own. We want to push the community to change its point of view, considering combining the two techniques of complementary scale to improve the non-invasive brain tissue microstructure characterization. Key invitees: Prof. F Barkhof (ION/UCH, UK); Dr. S Bisdas (ION/UCH, UK); Dr. S Punwani (ION/UCH, UK); Prof. S. Lehéricy (ICM, France); Dr. F Branzoli (ICM, France); Prof. I Ronen (LUMC, Netherlands); Dr. M Nilsson (Lund University, Sweden); Dr. J Valette (CEA/MIRCen, France). Attendees: over 50 students, researchers and professors from UCL; KCL; Cambridge University; Oxford University; Imperial College; Crick's Institute; NHS. Outcomes: 1) Review paper on the combination of DW-MRI and DW-MRS, in collaboration with Julien Valette (CEA Fontenay-aux-Roses in Paris, France), Itamar Ronen (LUMC in Leiden, the Netherlands) and Noam Shemesh (Champalimaud Centre for the Unknown in Lisbon, Portugal), published on NeuroImage 2017 (https://doi.org/10.1016/j.neuroimage.2017.11.028); 2) Collaboration with Francesca Branzoli and Stephane Lehericy (ICM in Paris, France): two abstracts submitted to ISMRM 2018; two papers in preparation; consolidation of long-term collaboration. 3) Collaboration with Noam Shemesh (Champalimaud Centre for the Unknown in Lisbon, Portugal): two abstracts submitted at the ISMRM 2018; two papers in preparation; establishment of new long-term collaboration. 4) Invited speaker at an equivalent workshop on combining DW-MRI and DW-MRS, 10-12 October 2018, in ICM in Paris, France, organized by Julien Valette, Itamar Ronen and Francesca Branzoli. The aim of the meeting will be to consolidate the collaborations established in the UCL's workshop and to discuss future projects. |
Year(s) Of Engagement Activity | 2017 |