Abstract
Optimizing treatment planning is essential for advances in patient care and outcomes. Precisely tailored therapy for each patient remains a yearned-for goal. Cardiovascular modelling has the potential to simulate and predict the functional response before the actual intervention is performed. The objective of this study was to proof the validity of model-based prediction of haemodynamic outcome after aortic valve replacement. In a prospective study design virtual (model-based) treatment of the valve and the surrounding vasculature were performed alongside the actual surgical procedure (control group). The resulting predictions of anatomic and haemodynamic outcome based on information from magnetic resonance imaging before the procedure were compared to post-operative imaging assessment of the surgical control group in ten patients. Predicted vs. post-operative peak velocities across the valve were comparable (2.97 ± 1.12 vs. 2.68 ± 0.67 m/s; p = 0.362). In wall shear stress (17.3 ± 12.3 Pa vs. 16.7 ± 16.84 Pa; p = 0.803) and secondary flow degree (0.44 ± 0.32 vs. 0.49 ± 0.23; p = 0.277) significant linear correlations (p < 0.001) were found between predicted and post-operative outcomes. Between groups blood flow patterns showed good agreement (helicity p = 0.852, vorticity p = 0.185, eccentricity p = 0.333). Model-based therapy planning is able to accurately predict post-operative haemodynamics after aortic valve replacement. These validated virtual treatment procedures open up promising opportunities for individually targeted interventions.
Highlights
Optimizing treatment planning is essential for advances in patient care and outcomes
The valid prediction of haemodynamics after aortic valve and vascular surgery opens up several opportunities for individualized pre-treatment planning, decision making and optimisation in patients with Aortic valve disease (AVD)
A fully operational virtual valve treatment procedure with all its challenges described was shown to be applicable in a first disease-specific study cohort of AVD patients
Summary
Optimizing treatment planning is essential for advances in patient care and outcomes. The resulting predictions of anatomic and haemodynamic outcome based on information from magnetic resonance imaging before the procedure were compared to post-operative imaging assessment of the surgical control group in ten patients. Model-based therapy planning is able to accurately predict post-operative haemodynamics after aortic valve replacement. These validated virtual treatment procedures open up promising opportunities for individually targeted interventions. The ability to model, and to predict the functional response before the actual surgical procedure is performed holds great promise for improvements in heart valve surgery and has remained a yearned-for goal. Clinical guidelines provide the current standards for medical decision making such as indications for surgical valve interventions They highlight the need for reliable treatment procedures and heart valve types that re-establish physiologic haemodynamics. Imaging-based CFD was shown to provide valid functional information in a variety of cardiovascular diseases, offering additional guidance in the process of pre-treatment planning
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