Recipient organisationUniversity of SheffieldSource-published name: The University of Sheffield
Funding£2.0M
PeriodNov 2013 — Oct 2018
In plain English
AI plain-English summary
Lung disease kills one in five people in the UK, yet doctors still rely on blunt, whole-lung tests like spirometry that miss early signs of disease in specific regions of the lungs. This project aims to replace those crude tools with magnetic resonance imaging (MRI) techniques that can safely and repeatedly scan the lungs without ionising radiation. Current gold-standard imaging—CT and X-ray—delivers high radiation doses, making it unsuitable for monitoring children or tracking short-term treatment responses. The researchers will establish two MRI strands: one using standard (¹H) MRI to assess pulmonary hypertension and cystic fibrosis, and another integrating hyperpolarised gas MRI to produce sensitive biomarkers of inflammation and regional lung function. If successful, these methods could give clinicians a repeatable, non-invasive way to diagnose early disease, stratify patients, and evaluate whether a therapy is working—without exposing patients to radiation. The work builds on the Sheffield Pulmonary Vascular clinic, the UK’s largest referral centre for pulmonary hypertension, and draws on existing patient registries rather than costly new cohorts.
View original technical description
Within the UK, 1 in 7 people are estimated to have lung disease, which is the most commonly reported long-term illness in children and the third most commonly reported in adults. The British Thoracic Society (The Burden of Lung Disease, 2006) highlighted that lung disease kills one in five people in the UK (more than stroke and heart disease) and costs the NHS over £6 billion p.a. Lung cancer still remains the biggest cancer killer in the UK with deaths outstripping those from breast cancer. Death rates from respiratory disease are higher in the UK than both the European and EU average and South Yorkshire has higher rates than the national average due to socio-economic factors. An ageing population, poor smoking cessation rates, and environmental factors such as air pollution mean that the global burden of respiratory disease is set to increase: the European Lung Foundation estimates that, in 2020, 11·9 million of 68 million deaths worldwide will be caused by lung diseases. The routine clinical management and treatment assessment of lung and pulmonary-vascular diseases currently rely on very blunt instruments of global pulmonary physiology (spirometry, right heart catheterisation), which provide very limited insight in to mechanisms of early disease such as inflammation, and regional pulmonary function and are thus of limited use in disease stratification and treatment assessment. More sophisticated tests such multiple breath inert gas washout (MBW), do have functional sensitivity to gas exchange and ventilation heterogeneity. Nevertheless, these tests are still whole lung tests whilst lung diseases are anatomically regional. Functional imaging techniques with refined sensitivity to pulmonary physiology and inflammation are therefore desperately needed for more accurate diagnosis and to assess the patients’ response to therapies in order to determine whether an individual derives benefit. Treatment follow up requires repeatable, safe and sensitive imaging modalities capable of generating quantitative regional biomarkers that are future scale-able to broader clinical use and multicentre studies. Despite their different mechanisms and manifestations, this is a common need in all pulmonary diseases. Currently clinical pulmonary imaging in the NHS relies heavily on ionising radiation with X-ray, CT and nuclear scintigraphy the gold standards, with MRI currently only being used in only a few centres for pulmonary vascular imaging with a focus on the function of the right heart. Scintigraphy can provide some functional sensitivity with ventilation/perfusion (V/Q) scans, but the images are of poor spatial resolution and rely on the inhalation of radioactive tracers such as 99Tc whose availability is becoming limited. CT is the current gold standard for anatomical lung imaging and pulmonary vascular imaging but involves ionising radiation and in general provide anatomical rather than functional information. CT relies on particularly high doses of radiation, so is unsuitable as an imaging technique for repeated clinical follow up or assessment of short term changes in response to respiratory therapy evaluation, this is a particular concern in children. Hence, development of alternative non-ionising pulmonary imaging techniques with MRI for routine clinical use is an extremely timely concept that is aligned to an important healthcare need. Proposed research programme: The first translational strand of this project will be on establishing the role of 1H pulmonary MRI as a mainstream NHS imaging modality in diagnosis and treatment assessment. The clinical focus will be PH and CF, both orphan diseases, which are highly treatment intensive and demand regular and sensitive imaging. This will involve a major engagement with radiological and clinical practice in helping define how best to image the lungs in these patients groups. The second translational strand is the integration of our HP gas lung MRI and 1H pulmonary imaging tools in to a pulmonary imaging system to provide repeatable, safe and sensitive imaging biomarkers of inflammation and regional physiology for the evaluation of therapies in pulmonary diseases. This will consolidate on our standing and expertise in HP gas MRI and establish Sheffield as a national and international referral centre of excellence for image based understanding of lung disease mechanisms and assessment of new interventions. Both strands of the proposed research will in the first instance be built around existing registries of patients from local and national NHS hospital trusts and will not rely on the establishment of new patient cohorts, which would be expensive and difficult for me to coordinate as a non-clinician. 1 i). The role of 1H MRI in clinical management of pulmonary vascular disease Clinical collaborators: Dr D Kiely, Dr C Elliot, Dr R Condliffe, Dr A Swift, STH Trust. Dr N Screaton, Papworth The Sheffield Pulmonary Vascular clinic is the largest referral centre for PH in the UK (2010 NHS PH audit48) providing a quaternary referral service for nearly 25 % of the UK population for Pulmonary Hypertension (PH). As such PH imaging is of a high clinical, economic and strategic research importance to STH trust. Our pulmonary vascular MR imaging research is second to none in the UK. Key research question: Establish sensitivity of functional 1H pulmonary vascular MRI techniques for the non-invasive measurement of pulmonary artery pressure, change in regional pulmonary resistance and perfusion post therapy in CTEPH and PAH. Key to the clinical diagnosis of PH, are invasive catheter derived measures of pulmonary artery pressure, pulmonary vascular resistance and cardiac output. In prospective studies we have developed multi-parametric MR imaging based models for the noninvasive prediction of pulmonary artery pressure and regional hemodynamics11, 35 based on dynamic right heart imaging, flow imaging in the pulmonary artery and perfusion imaging. This is the largest study of patients with MRI and right heart catheterisation (within 48 hrs) ever performed worldwide. In this project we will establish if our image based metrics and models are robust as non-invasive markers for the clinical evaluation of response to personalised medical therapy in patients with idiopathic pulmonary arterial hypertension (PAH) and surgical therapy in chronic thrombo-embolic PH (CTEPH), follow-up studies are proposed at 4 months and 1 year. These MR indices will be evaluated for response to therapy in relation to catheter measurements and patient exercise tests. Based on the expected change in the MR measurements at follow-up49, a group of 20 patients has a statistical power of 91.5%, for the detection of change at follow-up at significance level of p
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know