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The effect of respiration-driven flow waveforms on hemodynamic metrics used in Fontan surgical planning
Elaine Tang1, Zhenglun Alan Wei2, Phillip M Trusty2
1School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
Objective:
Poor total cavopulmonary connection (TCPC) hemodynamics have been hypothesized to be associated with long-term complications in Fontan patients. Image-based Fontan surgical planning has shown great potential as a clinical tool because it can pre-operatively evaluate patient-specific hemodynamics. Current surgical planning paradigms commonly utilize cardiac-gated phase contrast magnetic resonance (MR) imaging to acquire vessel flows. These acquisitions are often taken under breath-held (BH) conditions and ignore the effect of respiration on blood flow waveforms. This study investigates the effect of respiration-driven flow waveforms on patient-specific hemodynamics using real-time MR acquisitions.
Methods:
Patient-specific TCPCs were reconstructed from cardiovascular MR images. Real-time phase contrast MR images were acquired under both free-breathing (FB) and breath-held conditions for 9 patients. Numerical simulations were employed to assess flow structures and hemodynamics used in Fontan surgical planning including hepatic flow distribution (HFD) and indexed power loss (iPL), which were then compared between FB and BH conditions.
Results:
Differences in TCPC flow structures between FB and BH conditions were observed throughout the respiratory cycle. However, the average differences (BH - FB values for each patient, which are then averaged) in iPL and HFD between these conditions were 0.002 ± 0.011 (p = 0.40) and 1 ± 3% (p = 0.28), respectively, indicating no significant difference in clinically important hemodynamic metrics.
Conclusions:
Respiration affects blood flow waveforms and flow structures, but might not significantly influence the values of iPL or HFD. Therefore, breath-held MR acquisition can be adequate for Fontan surgical planning when focusing on iPL and HFD.
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