A Total Artificial Heart (TAH) replaces the human heart both functionally and anatomically. Since the device is implanted permanently into a patient, the accurate fit of this device is an important challenge. Every patient’s anatomy is unique, yet because of the technical complexity and cost of such devices only a limited number of designs are economically feasible. This challenges device engineers to find a way to optimize their designs to treat the maximum number of patients. For virtual fitting of the Aachen TAH ReinHeart design A.J. Fritschi and his colleagues sought out the Mimics Innovation Suite software to create anatomical models from real patient data.

(Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, Helmholtz Institute, RWTH-Aachen University, 
Aachen, Germany; Department for the Surgical Therapy of End-Stage Heart Failure and Mechanical Circulatory Support, Heart and Vascular Centre Duisburg, Duisburg, Germany)

Mimics Innovation Award Winner



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Design Optimization for an Optimal Fit

From a clinical point of view, it is important that the TAH fits each patient’s anatomy in an optimal way, though the size options are limited. Consequently, device engineers must ensure that their design is compatible for the maximum number of individual patient anatomies. Therefore, a detailed analysis of a large number of patients was required to optimize the design of the Aachen TAH ReinHeart.

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Efficiently Analyzing Large Volumes of Medical Datasets

The major challenge in this type of study is handling the large volume of medical imaging data. All patient data must be processed in precisely the same way to ensure comparability of the findings and thus the credibility of the study. These requirements demand a highly accurate workflow and a significant time investment due to the large number of patients.

Fritschi et al. selected medical images from 27 patients as the input for their design validation. They segmented these datasets to create detailed virtual models in the Mimics Innovation Suite.

With the help of this software, all 3D models were aligned using a common coordinate system to derive meaningful measurements from the virtual analysis (Figure 1). The team performed a virtual fitting of the current artificial heart design to each of the individual patients’ 3D models (Figure 2). This virtual fitting is an accurate and cost-effective way to determine the precise device fit and reveal areas for improvement. Subsequently, Fritschi et al. experimentally verified their virtual fitting process through cadaver studies.

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Virtual Fitting for Justified Implant Design Adjustments

The virtual fitting process started with the creation of an accurate model of each patient’s heart from CT images using the Mimics Innovation Suite. Fritschi et al. ensured the reproducibility of the model creation by using tools that can be applied globally to the images, such as thresholding, region growing and morphological operations (Figure 3). The authors were interested in determining the spatial constraints of the pericardial cavity and the valve position and orientation. They used Mimics to measure oblique parameters according to anatomical landmarks (Figure 1). All measurements made were comparable between patients.

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In the next step, Fritschi et al. virtually implanted the artificial heart. Figure 4 shows an overlay of the CAD model of the artificial heart on a patient’s heart. The alignment could also be verified using the original image data (Figure 2), which allowed the authors to iteratively improve the device design. Finally, the researchers verified their virtual fitting process through cadaver studies and a 3D capturing system acquired the position of the implanted artificial heart (Figure 5). This information was transferred to the Mimics Innovation Suite where a further design analysis was performed.

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Fritschi et al. concluded that virtual fitting is an effective tool for device design and an economical solution for including a larger number of patients in the study. The authors caution, however, that conventional cadaver studies will still play an important role, as many key elements of surgery such as haptic feedback are not yet available in virtual studies.

Fritschi et al.: Image based evaluation of mediastinal constraints for the development of a pulsatile total artificial heart. BioMedical Engineering OnLine 2013 12:81. http://www.biomedical-engineering-online.com/content/12/1/81

Go to www.materialise.com/medical/mimics-innovation-awards for more information about the Mimics Innovation Awards and our previous winners.

The Standard in ‘Engineering on AnatomyTM

The Mimics Innovation Suite turns 3D image data into high-quality digital models. Starting from medical image data such as CT, MRI or 3D Ultrasound images, the Mimics Innovation Suite offers the most advanced image segmentation, the broadest anatomical measurement options, powerful CAD tools for Engineering on Anatomy and 3D Printing, and accurate model preparation for FEA and CFD. Fritschi et al. used the Mimics Innovation Suite to:

  • Create accurate 3D heart models of 27 invididual CT scanse
  • Investigate the anatomical design requirements to attain an optimal fit
  • Perform a validation study

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