Device implantation planning in a soft tissue environment: applied to transcatheter aortic valve implantation
20 February 2017
KULeuven, Kasteelpark, Thermotechnisch Instituut, Aula van de Tweede Hoofdwet, TI 01.03 - Arenberg 41 - 3001 Heverlee
Prof J. Bosmans & Prof J. Van der Sloten
PhD defence Bart Bosmans - Faculty of Medicine and Health Sciences & KULeuven
Recent developments in medical implant technology have seen a rise in devices designed for minimal invasive implantation in soft tissue. They allow to treat patients not considered for surgery, reduce pain and improve the recovery time. However, the range of manipulations that can be performed during a minimal invasive surgery is limited. In a transcatheter aortic valve implantation this can cause problems with the sealing around the new valve. Computer aided surgical planning can provide additional information about the 3-dimensional geometry of the anatomy, and the interaction between the implant and the native tissue prior to the surgery. Therefore, the aim of this thesis is to develop computer aided surgical planning tools to improve device implantation in soft tissue.
Four methods were developed to reach this aim. First, the aortic root of a population of transcatheter aortic valve implantation patients was characterised, based on the pre-interventional computed tomography images. Next, a method was developed to include the 3-dimensional anatomical shape of the aortic root in the evaluation of the optimal implant size. Subsequently, in order to incorporate the interaction between the calcified native valve and the implant, a method for the patient specific simulation of the implantation was developed.Finally, a framework for virtual testing of the fit of a device in the patient population was developed.
Patients suffering from moderate to severe aortic regurgitation post implantation, had a higher average calcification volume. However, whether an individual patient would develop severe aortic regurgitation could not be predicted based on the calcification volume.The implant size algorithm assigned the same size implant as was implanted to 96% of the patients with limited or no aortic regurgitation. When applied to the patients with moderate to severe aortic regurgitation, 54% of them were assigned a different size than was implanted. The patient-specific simulation method could accurately predict the shape of the post-operative result, and the regurgitation estimation shows promising results that should be further validated on a larger patient set.
In conclusion, this PhD thesis showed that computer aided surgical planning has the potential to improve the outcome for transcatheter aortic valve implantation patients by using the full potential of the available 3-dimensional anatomical shape information. This will allow to make a more informed decision on the optimal size and position of the implant. Further prospective research is required to assess whether the computer assisted planning will improve the outcome of those patients.
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