Chronic liver disease and cirrhosis causes about 30,000 deaths annually in the US, 4,000 of which are directly due to lack of a donor liver available for transplant. These numbers could be reduced dramatically should the donor organ pool be expanded by rendering marginal cases, such as Donors obtained after Cardiac Death (DCD), transplantable. It is estimated that about 6,000 cadaveric livers/yr are only marginally damaged by ischemia post-cardiac death and could be resuscitated for transplantation. There is evidence from our lab and others that machine perfusion is a very promising approach for recovering cadaveric organs that would be otherwise rejected from the donor pool. However, clinical realization of such a machine perfusion device requires sophisticated algorithms that ensure tight control of the system, maximize the viability of the organ and accurately assess if the liver is ready for transplantation at the end of perfusion. There is a significant gap of algorithms designed for such an organ viability maximization task, which prevents clinical translation of these technologies and vertical advancement of the field. Our long-term goal is to develop novel engineering strategies to enable efficient transplantation of marginal donor organs and reduce deaths due to organ shortage. The objective of the proposed study is to develop a dynamic, online method to assess liver viability during perfusion and employ it to optimize liver metabolism to enhance recovery from ischemia. The central hypothesis to be tested here is that the liver viability during perfusion is correlated to liver metabolic function during machine perfusion. The work described here is expected to generate a dynamic, on-line liver viability score which can be used to assess the condition of the donor organs prior to transplantation surgery, ultimately reducing the guesswork involved in transplantation of marginal donor organs. The results of this work will also have a positive impact on engineering science by establishing the basis for integration of process design &control of these complex, dynamic organ preservation systems. The work is also expected to lead to improvements in healthcare by accelerating development of sophisticated organ preservation modalities and reducing deaths due to liver failure.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Research Project (R01)
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Modeling and Analysis of Biological Systems Study Section (MABS)
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Serrano, Jose
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Massachusetts General Hospital
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