| EPSRC Reference: |
EP/P018912/2 |
| Title: |
Predicting cardiovascular biomechanical stiffening due to the interplay of tissue layers with focus on calcific aortic valve disease |
| Principal Investigator: |
Aggarwal, Dr A |
| Other Investigators: |
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| Project Partners: |
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| Department: |
College of Science and Engineering |
| Organisation: |
University of Glasgow |
| Scheme: |
First Grant - Revised 2009 |
| Starts: |
01 January 2019 |
Ends: |
31 October 2019 |
Value (£): |
29,408
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| EPSRC Research Topic Classifications: |
| Biomaterials |
Med.Instrument.Device& Equip. |
| Tissue Engineering |
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Summary on Grant Application Form |
The primary function of the cardiovascular system is to supply blood to all parts of our body and stiffness of the tissue structures transporting the blood play a critical role in the optimal functioning of the system. The heart valves are a perfect example, which open and close over three billion times in a human life span. In spite of being robust, in our ageing society many valve-related diseases are becoming a major health problem; the stiffening of the valves leads to unwanted resistance to blood flow making it harder for the heart to pump blood at the same rate, which sometimes leads to heart failure and death. Calcific aortic valve disease (CAVD) is one such disease that progresses through accumulation of calcium within the valve tissue and affects 5% of population older than 75 years. 4 million people in the 75-84 age group are projected by 2018 and the population beyond the age of 85 is set to double by 2028. Thus, with our aging demographics, valvular diseases have been compared to an epidemic.
In this study, we propose to develop a computational tool that will help identify patients at a higher risk of CAVD at an early stage of development. Based upon clinical images of a patient's heart valves and experimental results already collected by our collaborators, we will formulate a pipeline that uses the valve's movement as an input and predicts the speed and severity of its calcification. This will allow close follow-up of high-risk patients and timely intervention before the complications arise. Usually, the patients at an advanced stage of disease are recommended for valve replacement surgery; however, the patients who are seen unfit for surgery have a survival rate of merely 32% after 5 years from the disease onset. The tool developed in this project will tremendously help improve the survival rate of those patients. Furthermore, the new insight obtained from this work will help us improve the design of medical devices such as artificial heart valves and blood pumps, since currently used devices have limited durability because of valve calcification or related issues.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.gla.ac.uk |