M. K. Harris1, J. DiRito1,3, A. Feizi4, N. Boutagy2,5, A. Feher2,5, P. Yoo1, D. Haakinson1, D. Mulligan1, A. J. Sinusas2,5, G. Tietjen1 1Yale University School Of Medicine,Department Of Surgery,New Haven, CT, USA 2Yale University School Of Medicine,Department Of Internal Medicine, Section Of Cardiovascular Medicine,New Haven, CT, USA 3University of Cambridge,Department Of Surgery,Cambridge, CAMBRIDGESHIRE, United Kingdom 4Yale University School Of Medicine,New Haven, CT, USA 5Yale University School Of Medicine,Yale Translational Research Imaging Center,New Haven, CT, USA
Introduction:
Despite a high transplant waiting list mortality, many marginal organs are discarded based on incomplete and subjective data. Organ viability assessment relies on risk stratification of donor data and limited organ evaluation by visualization and frozen biopsy. Dynamic computed tomography (CT) is used in vivo to assess microvascular tissue perfusion and ischemia, factors related to damage sustained by transplanted organs. Dynamic CT has potential to provide objective, quantifiable data to improve marginal organ utilization. We adapted in vivo dynamic CT methods to an ex vivo setting to measure individual organ perfusion variability.
Methods:
CT was performed at the Yale Translational Research Imaging Center on a GE Medical Systems clinical CT scanner. 10 kidneys and 5 livers were obtained from a local pig slaughterhouse. Organs were dissected, flushed with cold Custodial HTK preservation solution, and stored on ice until imaging. DICOM images were reconstructed in Horos and analyzed using custom MATLAB code to measure rates of contrast enhancement and clearance throughout the organs over time.
Results:
Marginal organs are known to sustain microvascular changes. We expect that these microvascular obstructions impair flushing and promote tissue injury. We adapted dynamic CT for use with ex vivo organs by performing sequential scans during contrast administration with iohexol and during subsequent continuous flush. Using custom MATLAB code, we measured enhancement of two regions of cortex equidistant from the right and left sides of each organ and measured peak enhancement, rates of enhancement, and rates of clearance.
Figure 1A includes representative images of two kidneys. Region of interest (ROI) 1 and ROI 2 are measured in the cortex on the left and right sides of each organ and demonstrate varied contrast kinetics within organs. Kidney 3L had a slower rate of contrast accumulation, lower total enhancement, and faster rate of decay in the tissue (Figure 1B and 1C). These preliminary data may suggest that less microvasculature was engaged and that contrast primarily remained in the larger vessels.
Conclusion:
Dynamic CT of ex vivo organs can be used to directly quantify perfusion deficits and microvascular changes. Its use could be extended to assess marginal organs to more accurately identify viable organs and improve utilization. This technique also creates opportunities to potentiate other tools for assessing viability and to evaluate the effects of emerging techniques in ex vivo organ preservation, recovery, and treatment.
