Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery

The goal of this procedure is to demonstrate the steps of creating 3D-printed, fully colored, patient-specific anatomical models using data from different imaging modalities. By using the example of chondrosarcomas of the petrous apex, the whole process of image fusion and segmentation, generation of a virtual 3D model and fabrication of the 3D print are demonstrated. Moreover, volumetric coloring of 3D prints suitable for surgical simulation is described.

A variety of imaging modalities, such as computed tomography and magnetic resonance imaging, show different aspects of the surgical site, such as bone, soft tissue, tumor, and vessels. 3D printing technologies offer the unique possibility to combine these different aspects in a single, compact, and tangible object in real size dimensions that can be studied and used to simulate the surgical approach. Especially for surgical simulation, it is important to produce 3D prints not only colored on the surface for providing in-depth volumetric coloring to clearly visualize structures nested inside each other, such as a blood vessel crossing a tumor.

This video offers a step-by-step guide for the fabrication of a fully colored anatomical model based on the example of a chondrosarcoma of the petrous apex. The crucial steps in this procedure are fusion and segmentation of medical imaging data, followed by creation of a virtual 3D surface model. As a third step, the virtual model is prepared for multicolor 3D printing, including a modified workflow to allow volumetric coloring of specific parts.

Finally, printing and post-processing are described. It is important to use imaging data with high spatial resolution, for example, a slice thickness of one millimeter or less. CT was used for segmentation of bones.

Contrast-enhanced T1 MRI images were used for segmentation of tumor and neural structures and TOF images for vessels. Download the DICOM files on your computer, and open Amira Software. Import the files of the different imaging modalities, and select the folder of the imaging data.

Click on the CT images, and connect them with the Volume Rendering module. Choose Specular for a more realistic rendering, and adjust the color transfer slider to visualize bone only. Continue by importing the MRI sequences, and connect them to a Volume Rendering module as well.

As MRI and CT images are not overlapping, it is necessary to fuse the different imaging data. Therefore, right-click on the MRI dataset, and choose Compute, Affine Registration. Choose Reference, then direct the cursor to the CT.In the Registration module’s properties, leave all settings on default and click on Align Centers, followed by clicking Register.

The two different imaging datasets are now fused. Repeat this step for all further imaging datasets. Check the matching accuracy by hiding the volume renderings and adding an OrthoSlice module to the MR images.

Choose Colorwash. Then next click on Data, and connect this port with the CT by dragging the mouse onto it. Adjust the color slider to visualize the neural structures superimposed to the bony skull structures.

Check for any misalignments by toggling the weight factor slider and looking onto the border between skull and brain surface, as well as the ventricles. Repeat this procedure on different slices and in coronal and sagittal directions. Deactivate the OrthoSlice module’s visibility, and reactivate volume rendering of the CT.Go to the CT data, and look for the lowest value in this dataset, in this case, minus 2, 048.

Next, add a Volume Edit module, connect the Volren module with the output data, and set the Padding value to minus 2, 048. Click on Cut Inside, and mark the region to be removed in the 3D viewport. Note, it’s important to avoid overlapping with parts not intended to be removed.

In this example, parts of the mandible bone and the upper cervical vertebrae were removed. Next, the remaining bone will be segmented and converted into a surface mesh. Therefore, click on the Segmentation Editor, and choose the modified CT image sequence and add a new label set.

Now choose Threshold as segmentation option. Set the lower slider to a value around 250 in case of a CT.Ensure thin bone structures such as the temporal bone or the upper orbital region to be selected in the preview. Otherwise, adjust the lower threshold, but avoid selecting any soft tissue.

Next, click on Select. And finally, add the selection to the label set. Return to the Pool View.

A new label set has been created for the CT.Right-click and choose Compute, Surface Gen, check the Compactify option, and click Apply. Finally, add a Surface View module, and adjust the color of the generated mesh. Add other relevant structures by repeating the previous steps.

In case of the tumor, manual segmentation was used rather than the thresholding operation. Thus, the tumor, the optic nerve, and the intracranial vessels were segmented and added to the model. Finally, export the generated meshes by right-clicking on the mesh and clicking on Save.

Choose STL as file format. Open Netfabb, and import the meshes generated in the previous steps as new parts. Check Automatic Repair, and click Import.

Select the skull, and split its shells into parts. This separates any loose objects not connected to the skull bone. Select the skull bone, and toggle its visibility off.

Now select all other parts, and delete them. Repeat this step for all other objects. Note, in some regions, such as the tumor inside the petrous apex of the skull, the geometries of both objects intersect with each other.

To avoid printing errors, it is necessary to remove such intersections. Therefore, select the two intersecting objects, and click on Boolean Operations. Move the object to be subtracted from the other one to the red side of the list, and click on Apply.

Now the two objects are clearly separated, which should be checked by toggling their visibility. By repeating these steps, the tumor as well as the artery inside the tumor are clearly separated from each other. In case of the basilar artery, additional supports are needed to prevent the object from being a loose part after printing.

Add a new object, in this case, a cylinder, and adjust its dimensions and subdivisions as needed. Place the cylinder to completely intersect with the skull and the vessel geometry. Now perform the Boolean operation again to subtract the parts within the bone and the blood vessel.

Repeat this step to add more supports where needed. To allow volumetric coloring of certain parts, it is necessary to generate not only one surface shell but many subshells inside the object. Select the tumor, and generate a new shell from it.

Set a shell thickness of 3 millimeter in the Inner Offset Mode with an accuracy of 15 millimeter and apply. This generates an inner shell with a distance of 3 millimeter to the original surface. Select the outer shell, and generate a new shell from it.

Select the shell thickness of 25 millimeter in Hollow Mode with an accuracy of 15 millimeter. Also, select the Remove Original Part checkbox. This generates a space of 05 millimeter between the two adjacent shells.

By repeating these steps, multiple inner shells with constant thicknesses and invariant offsets are created. It is recommended to use a shell thickness of 35 to 25 millimeter, as well as an offset of 1 to 05 millimeter to achieve smooth volumetric coloring. Repeat these steps with all other objects, such as the blood vessels.

In the last step, the print color of every object has to be set. Therefore, select a part to be colored. Double-click on Texture and Color Mesh, and choose a color.

Click on the Paint on Shells icon, followed by clicking on the model displayed in the screen center. Finally, apply changes, and be sure to confirm the Remove Old Part dialog. Repeat these steps with all other objects and shells, respectively.

Finally, export all objects to be printed, including supports and inner shells, and export them as individual files. Be sure to choose the VRML format since the STL format is not able to transport the color information. Open the 3D system’s 3D printing software, and import the VRML files created in the previous step.

Choose millimeters as unit. Check Keep Position, and apply to all files. And set the material type to ZP151.

Now place the 3D model in the printing volume by adjusting its position and rotation. In case of the skull model, make sure the opening is facing upwards. Go to Setup, select ZP151 as a material type, and set the layer thickness to 1 millimeter.

Check Bleed Compensation, and confirm. Next, click on Build, and leave all settings as predefined. Finally, check the printer status, and click on Print.

After the print is finished, unpack the model by carefully removing loose powder with a vacuum cleaner. It is important not to directly contact the model with the suction tube to prevent thin structures from breaking apart. Remove the model, and clean it by carefully applying pressurized air, as well as cleaning it with a soft brush.

In this state, the model is still very fragile. To increase stability and color situation, put the model inside a plastic tub, and infiltrate it with a hardening solution. Surplus solution has to be removed with pressurized air to keep all surface details maintained.

Let the model cure for several hours until it is completely dry. Different multicolored 3D prints of patients with chondrosarcoma were created. The technique of multicolor 3D printing allows fusing different anatomical aspects such as bony and soft tissue structures, each derived from different imaging modalities, to be combined in one single object.

In a surgical simulation setup, the plaster material of the multicolor print showed bone-like properties and could be easily drilled and cut. This technique also offers the possibility to color an object’s internal structure, such as the internal carotid artery traveling through the tumor. By removing layers of tumor with the drill, the red artery is revealed during surgical simulation.

To prove the accuracy of the technique, 3D models were scanned in the computed tomograph. The models created for printing were superimposed to these scans. A deviation mapping was created, and accuracy was determined in 50 randomly chosen surface points.

A mean deviation of 21 microns demonstrates the high accordance of the 3D print compared to the original data. It was demonstrated how to combine different clinical imaging modalities into one single multicolored 3D print. Furthermore, modification of the standard 3D printing workflow was presented to allow production of volumetrically colored models.

Additionally, overlapping accuracy of the 3D prints compared to the original imaging data showed a high precision. In conclusion, these fully colored models allow surgical simulation of even complex and anatomical situations, such as skull-based tumors, which has been presented in a series of case studies.