Opportunity Overview
1) Brief description of the context of the research including potential impact
Inflammation, one of the body's defense mechanisms against infection and injury, can be wrongfully directed at the body's own tissues as a result of abnormal activity of the immune system, resulting in immune-mediated inflammatory diseases (IMIDs). IMIDs afflict millions of individuals, leading to loss in productivity and increased costs to health services.
Treatments for IMIDs are now available, however these carry a high risk of serious side-effects. To decide who should receive these treatments and when they should be given (i.e. where the benefits of treatment outweigh the risks), we need to establish if inflammation is present and to monitor its activity over time. As many IMIDs affect deep tissues, clinical assessment alone is often limited, making imaging essential.
Among available imaging techniques, magnetic resonance imaging (MRI) has several advantages, including its ability to image deep tissues and to generate contrast between inflamed and non-inflamed tissue. However, conventional MRI's image contrast can only be explained as the aggregated effect of multiple tissue properties. The disentanglement of tissue properties can be achieved by quantitative MRI (qMRI), although current qMRI algorithms are prone to error, require high computation time and may not be optimised for imaging spatially heterogenous processes.
To address these limitations, we propose the development of a pipeline that incorporates novel tools for the detection of inflammation, its characterisation and its monitoring during the course of treatment. These components will enable accurate diagnosis and monitoring of inflammation, enabling doctors to customize treatment for individual patients, while also allowing for objective evaluation of newly proposed therapies in clinical trials.
2) Aims and Objectives
The aim of the project is to build a pipeline to accurately characterise inflammation, and...
Inflammation, one of the body's defense mechanisms against infection and injury, can be wrongfully directed at the body's own tissues as a result of abnormal activity of the immune system, resulting in immune-mediated inflammatory diseases (IMIDs). IMIDs afflict millions of individuals, leading to loss in productivity and increased costs to health services.
Treatments for IMIDs are now available, however these carry a high risk of serious side-effects. To decide who should receive these treatments and when they should be given (i.e. where the benefits of treatment outweigh the risks), we need to establish if inflammation is present and to monitor its activity over time. As many IMIDs affect deep tissues, clinical assessment alone is often limited, making imaging essential.
Among available imaging techniques, magnetic resonance imaging (MRI) has several advantages, including its ability to image deep tissues and to generate contrast between inflamed and non-inflamed tissue. However, conventional MRI's image contrast can only be explained as the aggregated effect of multiple tissue properties. The disentanglement of tissue properties can be achieved by quantitative MRI (qMRI), although current qMRI algorithms are prone to error, require high computation time and may not be optimised for imaging spatially heterogenous processes.
To address these limitations, we propose the development of a pipeline that incorporates novel tools for the detection of inflammation, its characterisation and its monitoring during the course of treatment. These components will enable accurate diagnosis and monitoring of inflammation, enabling doctors to customize treatment for individual patients, while also allowing for objective evaluation of newly proposed therapies in clinical trials.
2) Aims and Objectives
The aim of the project is to build a pipeline to accurately characterise inflammation, and...
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Start FreeSolicitation Details
| Issuing agency | EPSRC |
|---|---|
| Country | United Kingdom |
| Category | Research Development |
| Published | September 30, 2023 |
| Procurement stage | Active solicitation |
| Closed | Closing date not published |
| Status | Closed — no longer accepting responses |
| Official source | View original notice |
| Last verified | October 10, 2026 |
Source: UK Research and Innovation (UKRI) — Open Government Licence v3.0.
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