Using OCT to predict post-transplant renal function

Peter M. Andrews; Yu Chen; Jeremiah Wierwille; Daniel Joh; Peter Alexandrov; Derek Rogalsky; Patrick Moody; Allen Chen; Matthew Cooper; Jennifer E. Verbesey; Wei Gong; Hsing-Wen Wang

doi:10.1117/12.2005962

8 March 2013 Using OCT to predict post-transplant renal function

Peter M. Andrews, Yu Chen, Jeremiah Wierwille, Daniel Joh, Peter Alexandrov, Derek Rogalsky, Patrick Moody, Allen Chen, Matthew Cooper, Jennifer E. Verbesey, Wei Gong, Hsing-Wen Wang

Author Affiliations +

Proceedings Volume 8565, Photonic Therapeutics and Diagnostics IX; 856511 (2013) https://doi.org/10.1117/12.2005962
Event: SPIE BiOS, 2013, San Francisco, California, United States

Abstract

The treatment of choice for patients with end-stage renal disease is kidney transplantation. However, acute tubular necrosis (ATN) induced by an ischemic insult (e.g., from prolonged ex vivo storage times, or non-heart beating cadavers) is a major factor limiting the availability of donor kidneys. In addition, ischemic induced ATN is a significant risk factor for eventual graft survival and can be difficult to discern from rejection. Currently, there are no rapid and reliable tests to determine ATN suffered by donor kidneys and whether or not donor kidneys might exhibit delayed graft function. OCT (optical coherence tomography) is a rapidly emerging imaging modality that can function as a type of “optical biopsy”, providing cross-sectional images of tissue morphology in situ and in real-time. In a series of recent clinical trials, we evaluated the ability of OCT to image those features of the renal microstructure that are predictive of ATN. Specifically, we found that OCT could effectively image through the intact human renal capsule and determine the extent of acute tubular necrosis. We also found that Doppler based OCT (i.e., DOCT) revealed renal blood flow dynamics that is also reported to be a determiner of post-transplant renal function. This kind of information will allow transplant surgeons to make the most efficient use of available donor kidneys, eliminate the possible use of bad donor kidneys, provide a measure of expected post-transplant renal function, and allow better distinction between post-transplant immunological rejection and ischemic-induced acute renal failure.

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Peter M. Andrews, Yu Chen, Jeremiah Wierwille, Daniel Joh, Peter Alexandrov, Derek Rogalsky, Patrick Moody, Allen Chen, Matthew Cooper, Jennifer E. Verbesey, Wei Gong, and Hsing-Wen Wang "Using OCT to predict post-transplant renal function", Proc. SPIE 8565, Photonic Therapeutics and Diagnostics IX, 856511 (8 March 2013); https://doi.org/10.1117/12.2005962

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