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Kidney Week

Abstract: TH-PO749

Understanding the Effects of Haemodialysis on Blood Flow: An Imaging-Mathematical Modeling Study

Session Information

  • Bioengineering
    October 25, 2018 | Location: Exhibit Hall, San Diego Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Bioengineering

  • 300 Bioengineering

Authors

  • Kharche, Sanjay R., Lawson Health Research Institute, London ON, Ontario, Canada
  • Marants, Raanan, University of Western Ontario, London, Ontario, Canada
  • Qirjazi, Elena, Lawson Health Research Institute, London ON, Ontario, Canada
  • Kassay, Andrea D., Lawson Health Research Institute, London ON, Ontario, Canada
  • Joseph, Jermiah, Lawson Health Research Institute, London ON, Ontario, Canada
  • McDougall, Kierra D., Lawson Health Research Institute, London ON, Ontario, Canada
  • Lee, Ting, University of Western Ontario, London, Ontario, Canada
  • McIntyre, Christopher W., Lawson Health Research Institute, London ON, Ontario, Canada
Background

Haemodialysis (HD) is a circulatory stress to organs. The clinical assessment of blood flow (BF) during HD is challenging. We are developing in silico tools to permit patient specific prediction of HD effects on BF, to accelerate translation. This study aimed to test the feasibility of creating imaging informed, patient specific simulations of multi-organ perfusion under the stress of HD.

Methods

We reconstructed 3D liver and kidney BF using CT images from a previous study, under both standard and cooled dialysate (DC). Ten patient data sets were analysed. Volumes of each organ were calculated. A binned histogram of blood flow distribution was computed for each case. Patient specific mathematical models of blood flow (Kharche et al. Front. Physiol. 2018) based on observed organ shape and BF distributions, known blood vessel morphometry, autoregulation mechanisms, and mathematically optimized spatial BF distribution were successfully generated for further study. Novel texture analysis based on fractal dimension was implemented to quantify BF heterogeneity in the images as well as models.

Results

One 3D reconstructed aorta-liver-kidney composite is shown in Figure 1,A. Histograms of BF (Figure 1, B) show that DC altered BF. In all cases, portal hepatic BF increased markedly due to DC. The volumes of organs were also affected by both dialysis and DC.

Conclusion

The development of patient specific in silico models of the multi-organ blood flow consequences of HD appears to be feasible and warrants further study to accurately predict individual treatment responses and optimize treatment parameters.

Figure 1. A. Reconstructed BF maps of aorta, liver, and kidneys. B. Histogram of BF in right kidney before (red) and after (green) cooling.

Funding

  • Private Foundation Support