Mixed Reality Technology and Three-Dimensional Printing in Teaching: Heart Anatomy as an Example

This study focuses on integrating mixed reality into anatomy education by developing high-fidelity 3D printed models and heart holograms, using the CarnaLife Holo application with Microsoft HoloLens in medical students'training sessions to improve their learning experience. Researchers worldwide are increasingly recognizing the potential of 3D printing and immersive technologies, including mixed reality in medical education and clinical practice. Their continuous advancement and wider adoption mark a pivotal shift in the future of medical innovation.

The objective of this study is to explore the expanding applications of mixed reality, not only in anatomy education, but also in routine clinical practice across medical disciplines, including orthopedics and musculoskeletal trauma surgery to enhance diagnostic precision and surgical planning. To begin, open 3D Slicer version 5.6.0, and navigate to the data module. Click add data and select the patient-specific CT images in DICOM format.

Assess the quality of the images by inspecting axial, sagittal, and coronal views in the slice viewer. Verify sufficient contrast to distinguish between the myocardium and the heart chambers. Now navigate to the segment editor module and click add to create a new segmentation.

Select threshold from the segmentation tools. Set the lower and upper threshold values to accurately isolate the myocardium and heart chambers. Adjust the range using the sliders or by entering values to ensure the correct anatomical structures are properly captured.

After applying threshold-based segmentation, inspect the segmented model in axial, sagittal, and coronal views to ensure that the myocardium and heart chambers are correctly captured. If any areas are missing, add missing regions using the paint tool in the segment editor module. Carefully add segmentation to regions that were not properly captured by thresholding.

Adjust the brush size as needed for better precision, especially in small or complex areas. Similarly, if unwanted tissues or artifacts are present in the segmentation, use the erase tool to remove them. For larger incorrect areas, use the scissors tool to cut them away efficiently.

Once all necessary corrections are made, review the segmentation to ensure that the myocardium is fully segmented with no missing or extra areas, and the heart chambers are correctly defined without unwanted connections. Click apply to finalize the segmentation. To export the STL files for both the myocardium and heart chambers separately, navigate to segmentations, followed by export to files, and then select STL format.

Next, to optimize the myocardium and heart chambers, open Meshmixer and navigate to file, followed by import. Load the STL files for both the myocardium and heart chambers. Ensure both models are correctly aligned and visible in the workspace.

Select each model and go to edit, followed by make solid. Adjust the solid accuracy slider to balance detail and mesh stability. Apply the operation and verify that the model remains intact.

Choose solid type accuracy to preserve anatomical details. Now use the select tool to highlight small unwanted artifacts and delete them using edit, followed by discard. If needed, reconstruct the disrupted areas by navigating to select, followed by modify, erase and fill, or by using brushes.

To optimize the model for 3D printing, select the area with surface irregularities. Click on deform and then smooth. Apply it iteratively.

Adjust the smooth strength slider depending on the severity of surface irregularities. Next, to merge the myocardium and heart chambers, navigate to edit, Boolean difference, and select both models. Ensure that the operation successfully joins the structures without creating internal holes or overlapping surfaces.

Once merging and refinement are complete, navigate to file, followed by export. Save the final unified model in STL format, ensuring it is ready for slicing and 3D printing. The mixed reality visualization provided an interactive and dynamic representation of CT data, allowing realtime manipulation of heart structures.

However, oversegmentation led to surface-rendering inaccuracies, distorting internal anatomical details. The volume rendering technique enabled visualization of different tissue densities, improving anatomical detail recognition. This approach allowed better differentiation of complex structures where segmentation alone was insufficient.