Accuracy of 3D-Printed Models of Aortic Valves – a Comparative Analysis Between Planimetric and Photogrammetric Measurements
Published Online: Sep 21, 2023
Page range: 16 - 22
Received: Apr 15, 2023
Accepted: May 27, 2023
DOI: https://doi.org/10.2478/jim-2023-0004
Keywords
© 2023 Daniel Cernica et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
Background
3D printing has changed the paradigm of personalized medicine. Similarly to fingerprints, there are no two identical hearts; consequently, in cardiology, diagnosis and treatment, either medical, interventional or surgical, must be individualized according to the specific problem of a particular patient.
The aim
of this proof-of-concept study was to analyze two measurement methods, the planimetric and the photogrammetric method, in the process of creating a 3D-printed model from cardiac computed tomography angiography images and to evaluate the accuracy of an aortic valve anatomical model.
Material and methods
Cardiac computed tomography images, obtained from 20 patients with severe aortic stenosis, underwent stereolithographic reconstruction using 3D Slicer to create digital 3D models of the aortic valves. Serial measurements of six key elements of the aortic valvular apparatus were measured on the 3D model and compared to the measurements taken on the 2D computed tomography images.
Results
The differences between the two measurement methods were sub-millimetric in case of the left ventricular outflow tract and the sinotubular junction, and 1.386 mm for the left sinus of Valsalva (p = 0.0412), 0.3476 mm for the right sinus of Valsalva (p = 0.1874), and 0.6905 mm for the non-coronary Valsalva sinuses (p = 0.1353). Sinus heights were also similar, with a difference of 0.0119 mm (p = 0.6521).
Conclusion
In this study, the results of digital photogrammetry were superimposable to those of computed tomography scan measurements. The accuracy of each 3D-printed model depends on geometric complexity, the level of training of the personnel, and on the resources of each 3D printing laboratory.