Focusing on two important diseases
- Aortic valve disease:
- 50,000 aortic valve replacements are reported per year in the EU
- Longevity of valve substitutes is limited
- Dilation of ascending aorta
- Aortic coarctation:
- CoA is one of the most frequent congenital heart diseases
- Often requiring repeated interventions
Motivation for CARDIOPROOF‘s trials
- Existing evidence-based algorithms (guidelines) are vulnerable to individual variability
- Patient pathways for diagnosis, treatment and follow-up remain significantly inconsistent at all levels (physician, hospital, national, European, International).
- Former VPH efforts have already generated high quality modelling tools
- computational fluid dynamics (CFD)
- lumped heart models
that are ideally suited to support physicians in decision making.
Treatments of the aortic valve disease (AVD) and of the aortic coarctation (CoA) represent a real clinical challenge. Currently, more than 50,000 aortic valve replacements are reported per year in the EU, while CoA is known to be one of the most frequent congenital heart diseases. In both AVD and CoA, the timing and type of treatment (surgery, catheter/based intervention or medication/follow-up) are crucial to prevent potentially life threatening sequelae (e.g. heart failure) and, on the other hand, to avoid too early procedures which might in turn increase the risk for re-operation during the life time of a given patient.
AVD’s are usually treated, in a simplified view, by medication and surgery (or catheter based intervention i.e. TAVI, which is applied in high-risk patients with contraindications to surgery, and is not part of the CARDIOPROOF trial). Surgery can be performed by aortoplasty or valve replacement (mechanical, biological valve substitute). Biological valves have limited longevity and do not grow, although tissue engineered valves with “growth potential” are currently being tested in preclinical (FP7 Life Valve) or first clinical trials (FP7 ESPOIR). Mechanical prostheses have better longevity but require life-long anticoagulation and are not suited for smaller children. The reconstruction of aortic valve leaflets is another option in some patients. However, surgery is often not successful because repair is difficult due to the intricate structure and complex properties of the valve apparatus. Furthermore, repairs are normally performed during open heart surgery when the heart is emptied of blood and the valves are motionless. This makes it difficult for the surgeon to know how a given surgical modification will translate into the valve function after the heart has been closed and the blood flow restored. CARDIOPROOF will thus try to apply methods that can help guide decision making concerning different types of valve surgery (aortoplasty, biological/mechanical valve) by using virtual models of different valve prostheses.
The second area to be examined by CARDIOPROOF is the aortic arch coarctation. Patients with CoA are typically operated at young age, and re-coarcation occurs frequently. State-of-the-art treatment options for patients with primary or secondary CoA require medication and/or stenting of the aorta in order to reduce aortic pressure and left ventricular overload, but not all patients experience a significant improvement in haemodynamics after stenting and thus the treatment choice for this disease still varies widely between centres. In past and current research, models were tested first in small clinical studies aiming to predict the immediate haemodynamic effect of stent placement in re-CoA. This is due to the fact that current imaging and other routinely used diagnostic methods (such as blood pressure measurement and haemodynamic measurements through invasive catheterisation) cannot accurately predict the haemodynamic state after the procedure. Furthermore as many of the patients at risk are growing children and clinicians need sufficient information on how gradients will develop over time taking into account the growth induced increase of cardiac outputs. The successful introduction of model-based patient specific decision-making should ensure that every patient gets the optimum treatment for his/her disease.