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In This Article

  • Summary
  • Abstract
  • Introduction
  • Protocol
  • Results
  • Discussion
  • Disclosures
  • Acknowledgements
  • Materials
  • References
  • Reprints and Permissions

Summary

This method demonstrates a voxel-based 3D printing workflow, which prints directly from medical images with exact spatial fidelity and spatial/contrast resolution. This enables the precise, graduated control of material distributions through morphologically complex, graduated materials correlated to radiodensity without loss or alteration of data.

Abstract

Most applications of 3-dimensional (3D) printing for presurgical planning have been limited to bony structures and simple morphological descriptions of complex organs due to the fundamental limitations in accuracy, quality, and efficiency of the current modeling paradigm. This has largely ignored the soft tissue critical to most surgical specialties where the interior of an object matters and anatomical boundaries transition gradually. Therefore, the needs of the biomedical industry to replicate human tissue, which displays multiple scales of organization and varying material distributions, necessitate new forms of representation.

Presented here is a novel technique to create 3D models directly from medical images, which are superior in spatial and contrast resolution to current 3D modeling methods and contain previously unachievable spatial fidelity and soft tissue differentiation. Also presented are empirical measurements of novel, additively manufactured composites that span the gamut of material stiffnesses seen in soft biological tissues from MRI and CT. These unique volumetric design and printing methods allow for deterministic and continuous adjustment of material stiffness and color. This capability enables an entirely new application of additive manufacturing to presurgical planning: mechanical realism. As a natural complement to existing models that provide appearance matching, these new models also allow medical professionals to "feel" the spatially varying material properties of a tissue simulant-a critical addition to a field in which tactile sensation plays a key role.

Introduction

Currently, surgeons study numerous discrete 2-dimensional (2D) imaging modalities displaying distinct data to plan for operations on 3D patients. Furthermore, viewing this data on a 2D screen is not fully capable of communicating the full extent of the collected data. As the number of imaging modalities grows, the ability to synthesize more data from distinct modalities, which exhibit multiple scales of organization, necessitates new forms of digital and physical representation to condense and curate information for more effective and efficient surgical planning.

3D-printed, patient-specific models have emerged as a new diagnostic tool for surgical planning that has been shown to reduce operating time and surgical complications1. However, the process is time-consuming due to the standard stereolithography (STL) method of 3D printing, which shows a visible loss of data and renders printed objects as solid, homogeneous, and isotropic materials. As a result, 3D printing for surgical planning has been limited to bony structures and simple morphological descriptions of complex organs2. This limitation is a result of an outdated manufacturing paradigm guided by the products and needs of the industrial revolution, where manufactured objects are fully described by their exterior boundaries3. However, the needs of the biomedical industry to replicate human tissue, which displays multiple scales of organization and varying material distributions, necessitate new forms of representation that represent the variations across the entire volume, which change point by point.

To address this issue, a 3D visualization and modeling technique (Figure 1) was developed and coupled with a novel, additive manufacturing process that enables greater control over the mixing and deposition of resins in ultrahigh resolution. This method, called bitmap printing, replicates human anatomy by 3D printing directly from medical images at a level of spatial fidelity and spatial/contrast resolution of advanced imaging technology approaching 15 µm. This enables the precise and graduated control required to replicate variations in morphologically complex soft tissue with no loss or alteration of data from diagnostic source images.

Protocol

NOTE: 3D Slicer Medical Image Computing Software4 (see the Table of Materials) was used for the work completed in sections 1 through 3.

1. Data input

  1. Open the medical image computing software, click the File button and DICOM from the dropdown menu, and wait for the DICOM Browser window to open.
    1. In the DICOM Browser window, select Import. Wait for the Import DICOM Files from directory popup window to appear.
    2. Navigate to the DICOM file stack and click the Import button.
    3. Ensure that the selected stack of DICOM files are loaded into the DICOM Browser. Ensure that the data has been correctly populated and matches the desired study in the following categories: Patient, Study, Series, and Instance.
      1. Click the Advanced check box to activate additional metadata. Select the desired Series Number and click the Examine button. Ensure the desired sequence is not displaying warnings. Click the check box next to the desired DICOM Data file | Load.
        NOTE: Select the highest resolution images with the thinnest slice acquisition as this method is capable of printing at 15 µm and 27 µm slice thickness.
  2. For volume rendering, once the sequence is loaded into the medical image computing software, navigate to Modules and select Volume Rendering Module from the dropdown menu.
    1. In the Volume Rendering module, select the name of the sequence from the Volume dropdown menu to activate the image stack and translate the data into a voxelized volume. Ensure that the active module's name matches the desired sequence selected in step 1.1.3.1.
    2. Click the Eye Ball icon next to the Volume dropdown to visualize the selected volume in 3D. Ensure that the 3D display window is open and a grayscale 3D representation is visible.
    3. Next, click the arrow next to Advanced to open the Advanced Tools. Select the Volume Property tab to open a set of controls for modifying the color channel of the voxel model.
    4. Navigate to the Scalar Opacity Mapping menu. Left-click in the field to create points where intensity values will be defined by opacity. Place points along this scale to visualize the anatomy of interest.
      NOTE: The right-left location of the point is correlated to the range of the image's intensity values, and the up-down location refers to the opacity.
    5. Navigate to the Scalar Color Mapping menu. Left-click in the field to create points and specify colors correlated to intensity values. Double-click in the field to open a Select Color window to modify color information.

2. Manipulations

NOTE: A masking step is required if the anatomy is sufficiently complex, to the point where surrounding tissues and extraneous data are present after modifications to the Volume Properties.

  1. Navigate to Modules and select the Segment Editor from the dropdown menu. Ensure the Segment Editor toolbars appear.
    1. Navigate to the Segmentation dropdown and select Create New Segmentation as. Type a custom name for the segmentation from the Rename Segmentation popup window and click OK.
    2. Navigate to the Master Volume dropdown and select the active volume, which will have the same name as the Volume Rendering. Next, click the Add button directly below the dropdown. Ensure the segment container is created in the field below.
    3. Navigate to the effects tool panel below and select the Scissors tool. Navigate to the Scissors menu and select Fill Inside, Free-form, and Unlimited. Next, hover over the 3D Window, right-click and hold while drawing around the area to be erased. Ensure a colored swath appears, showing what has been covered. Repeat this process until all areas to be deleted are covered.
      NOTE: There are Extensions, such as Segment Editor Extra Effects, that can be downloaded into the medical image computing software, containing tools for creating this segmentation.
    4. Next, select the Mask Volume tool from the Effects menu. Check Select Inside to delete all image data covered by the segment. Next, modify the Fill Value to be -1000, which is equal to air, or void, in the Hounsfield unit scale. Finally, hit apply and click the Eye Ball next to the Output Volume to show the new masked volume.
      1. Navigate to Modules and select Volume Rendering from the dropdown menu. Click the Eye Ball next to the active volume to turn off the visualization.
      2. Next, from the dropdown menu, select the newly created masked volume. Click the Eye Ball to activate the volume.
      3. Finally, navigate to the Inputs menu and open the Properties dropdown menu. Select the Volume Property created in step 1.2.5. Ensure the volume in the 3D View is masked and color-encoded.

3. Slicing

NOTE: This process bypasses the traditional 3D printing method by sending the slice files directly to the 3D printing instead of an STL mesh file. In the following steps, slices will be created from the volume rendering. The Bitmap Generator module is a custom-built extension. This can be downloaded from Extensions Manager.

  1. Navigate to the Modules, select Slicerfab from the dropdown. Ensure the Print Parameters and Output Parameters menus are present.
    1. Under the Printer Parameters dropdown, ensure the X resolution is set to 600 DPI and the Y resolution is set to 300 DPI. Ensure the Layer thickness is set to 27 µm.
    2. Next, open the Output Parameters menu and modify the scale of the final model as needed.
    3. Finally, select a file location for the slices to be saved and click Generate.
      ​NOTE: This step can take several minutes to complete.

4. Dithering

NOTE: Adobe Photoshop (see the Table of Materials) was used for the work completed in section 4.

  1. Open the image editing software and click File and select Open from the dropdown menu. Navigate to the first image of the PNG file stack created in the previous step and click the Open button.
  2. Navigate to Window and select Actions from the dropdown menu. In the Actions menu, click New Action, enter a custom name, and select OK. Ensure the action is being recorded by checking that the Record button is active and red.
    1. Once the image has loaded, navigate to Image | Mode | Indexed Color. In the Index window, select from the dropdown menu Local Perceptual and specify the number of colors to be 8.
    2. In the Forced menu, select Custom. Click the first two squares, wait for the Custom Color window to pop up, and select a custom color pallet. Select 100% Magenta and ensure C, Y, and K are set to 0.
      1. Repeat this process and ensure there are two squares devoted to 100% C, Y, and K.
    3. In the Options menu, for Matte, select Custom from the dropdown menu. For Dither, select Diffusion, and for Amount, select 100%. Finally, click OK.
    4. Navigate to the Action menu and click the square button to stop recording. Close the active window and click No in the save changes popup window.
  3. Navigate to File | Automate | Batch. In the Batch popup window, navigate to the Action dropdown and select the action created in the previous step. Next, under the Source menu, click the Choose button and navigate to the folder of images exported in step 3.1.3. Under the Destination menu, click the Choose button, select a destination folder location for the new files, and click OK.

5. Voxel printing

NOTE: Stratasys GrabCAD5 was used for the work completed in section 5.

  1. Open the print software, click Apps and Launch Voxel Print Utility from the dropdown menu.
    1. In the Slice Files' Prefix text box, enter the prefix of the PNG file stack. Next, click the Select button and navigate to the folder where the PNG files stack is located, and click OK.
    2. Under Slice Range, ensure the First Slice and Number of Slices match the number of files in the created folder.
    3. Under Slicing Parameters, ensure the Sliced thickness (mm) matches the settings specified in step 3.1.1.1 and Slice width (pixels) and Slice height (pixels) match the PNG files width and height.
    4. Under Background Color, ensure the background matches the background color, set not to print. Once completed, click the Next button.
  2. On the Tools page under Material Mapping, select the material from the dropdown menu to be mapped to the associated color, derived from the PNG files. Repeat this process for each color in the menu. Then, click Finish | OK on the popup window Info Gcvf creation succeeded.
  3. On the host computer print software, click File | Import File from the dropdown menu. Navigate to the Gcvf file and click Load. On the main screen, select Print.

Results

A positive result, as shown in Figure 2 and Figure 3, will be a direct translation of the volume rendering as defined in steps 1.2.5 or 2.1.1.4. The final model should visually match the volume rendering in size, shape, and color. Along this process, there are numerous steps where an error can occur, which will affect one or more of the properties listed above.

Issues related to the uniform scaling, as shown in

Discussion

The current representational framework that the majority, if not all, of digital modeling tools employ today results in the STL file format8. Nevertheless, the specific nature of this paradigm has proven inadequate when trying to express the granular or hierarchical structure of more complex, natural materials. With the arrival of recent additive manufacturing techniques such as multimaterial 3D printing, highly tuned and highly optimized objects can be produced, which display gradual material tra...

Disclosures

N.J. is an author on a patent application filed by the University of Colorado Regents that describes methods like those described in this work (application no. US16/375,132; publication no. US20200316868A1; filed 04 April 2019; published 08 October 2020). All other authors declare that they have no competing interests.

Acknowledgements

We thank AB Nexus and the State of Colorado for their generous support of our scientific research into voxel printing for presurgical planning. We thank L. Browne, N. Stence, and S. Sheridan for providing data sets used in this study. This study was funded by the AB Nexus Grant and the State of Colorado Advanced Industries Grant.

Materials

NameCompanyCatalog NumberComments
3D Slicer Image Computing PlatformSlicer.orgVersion 4.10.2–4.11.2
GrabCADStratasys1.35
J750 Polyjet 3D PrinterStratasys
PhotoshopAdobe2021

References

  1. Ali, A., et al. Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: adult cardiac conditions. 3D Printing in Medicine. 6 (1), 24 (2020).
  2. Ballard, D. H., et al. Radiological Society of North America (RSNA) 3D Printing Special Interest Group (SIG) clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: abdominal, hepatobiliary, and gastrointestinal conditions. 3D Printing in Medicine. 6 (1), 13 (2020).
  3. Corney, J. The next and last industrial revolution. Assembly Automation. 25 (4), (2005).
  4. Fedorov, A., et al. 3D Slicer as an image computing platform for the quantitative imaging network. Magnetic Resonance Imaging. 30 (9), 1323-1341 (2012).
  5. Guide to Voxel Printing. GrabCAD Available from: https://help.grabcad.com/article/230-guide-to-voxel-printing?locale=en (2021)
  6. Bader, C., et al. Making data matter: Voxel printing for the digital fabrication of data across scales and domains. Science Advances. 4 (5), (2018).
  7. Zhang, F., Li, C., Wang, Z., Zhang, J., Wang, Y. Multimaterial 3D printing for arbitrary distribution with nanoscale resolution. Nanomaterials. 9 (8), 1108 (2019).
  8. Robson, R. The STL Algorithms. Using the STL. , 47-54 (1998).
  9. Waran, V., Narayanan, V., Karuppiah, R., Owen, S. L. F., Aziz, T. Utility of multimaterial 3D printers in creating models with pathological entities to enhance the training experience of neurosurgeons. Journal of Neurosurgery. 120 (2), 489-492 (2014).
  10. Cumbler, E., et al. Contingency planning for healthcare worker masks in case of medical supply chain failure: Lessons learned in novel mask manufacturing from COVID-19 pandemic. American Journal of Infection Control. 49 (10), 1215-1220 (2021).

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Voxel PrintingBitmap Printing3D Printed ModelsMedical ImagesSoft Tissue ReplicationPresurgical PlanningRadiologist CollaborationDICOM FilesMedical Image Computing SoftwareVolume RenderingVoxelized VolumeGrayscale 3D RepresentationOpacity MappingColor Mapping

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