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.

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
<ol>
	<li>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.
	<ol>
		<li>In the DICOM Browser window, select Import. Wait for the Import DICOM Files from directory popup window to appear.</li>
		<li>Navigate to the DICOM file stack and click the Import button.</li>
		<li>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.
		<ol>
			<li>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 &#181;m and 27 &#181;m slice thickness.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>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.
	<ol>
		<li>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&#39;s name matches the desired sequence selected in step 1.1.3.1.</li>
		<li>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.</li>
		<li>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.</li>
		<li>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&#39;s intensity values, and the up-down location refers to the opacity.</li>
		<li>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.</li>
	</ol>
	</li>
</ol>
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.
<ol>
	<li>Navigate to Modules and select the Segment Editor from the dropdown menu. Ensure the Segment Editor toolbars appear.
	<ol>
		<li>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.</li>
		<li>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.</li>
		<li>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.</li>
		<li>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.
		<ol>
			<li>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.</li>
			<li>Next, from the dropdown menu, select the newly created masked volume. Click the Eye Ball to activate the volume.</li>
			<li>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.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
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.
<ol>
	<li>Navigate to the Modules, select Slicerfab from the dropdown. Ensure the Print Parameters and Output Parameters menus are present.
	<ol>
		<li>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 &#181;m.</li>
		<li>Next, open the Output Parameters menu and modify the scale of the final model as needed.</li>
		<li>Finally, select a file location for the slices to be saved and click Generate. 
		&#8203;NOTE: This step can take several minutes to complete.</li>
	</ol>
	</li>
</ol>
4. Dithering
NOTE: Adobe Photoshop (see the Table of Materials) was used for the work completed in section 4.
<ol>
	<li>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.</li>
	<li>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.
	<ol>
		<li>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.</li>
		<li>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.
		<ol>
			<li>Repeat this process and ensure there are two squares devoted to 100% C, Y, and K.</li>
		</ol>
		</li>
		<li>In the Options menu, for Matte, select Custom from the dropdown menu. For Dither, select Diffusion, and for Amount, select 100%. Finally, click OK.</li>
		<li>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.</li>
	</ol>
	</li>
	<li>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.</li>
</ol>
5. Voxel printing
NOTE: Stratasys GrabCAD5 was used for the work completed in section 5.
<ol>
	<li>Open the print software, click Apps and Launch Voxel Print Utility from the dropdown menu.
	<ol>
		<li>In the Slice Files&#39; 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.</li>
		<li>Under Slice Range, ensure the First Slice and Number of Slices match the number of files in the created folder.</li>
		<li>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.</li>
		<li>Under Background Color, ensure the background matches the background color, set not to print. Once completed, click the Next button.</li>
	</ol>
	</li>
	<li>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.</li>
	<li>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.</li>
</ol>

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

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.

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...

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 &#181;m. 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.

<table><tbody><tr><td>3D Slicer Image Computing Platform</td><td>Slicer.org</td><td>Version 4.10.2&amp;ndash;4.11.2</td><td></td></tr><tr><td>GrabCAD</td><td>Stratasys</td><td>1.35</td><td></td></tr><tr><td>J750 Polyjet 3D Printer</td><td>Stratasys</td><td></td><td></td></tr><tr><td>Photoshop</td><td>Adobe</td><td>2021</td><td></td></tr></tbody></table>

voxel printing anatomy: design and fabrication of realistic, presurgical planning models through bitmap printing

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.

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 <stron...

Watch this Scientific Journal Video about Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing at JoVE.com

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

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.

Most applications of 3-dimensional (3D) printing for presurgical planning have been limited to bony structures and simple morphological descriptions of ...

voxel-printing-anatomy-design-fabrication-realistic-presurgical

Research

JoVE Journal

Bioengineering

2.7K Views.  University of Colorado-Anschutz. Bitmap printen maakt de directe fabricage van 3D-geprinte modellen voor medische beelden mogelijk. Met deze methode kan het zachte weefsel, dat geleidelijk variërende materiaaleigenschappen bevat, in hoge resolutie worden 3D-geprint. Het belangrijkste voordeel van deze techniek is het vermogen om het zachte weefsel te repliceren.Dit geeft chirurgen een beter ruimtelijk inzicht in variatie in het zachte weefsel bij complexe operaties. Wanneer u deze methode voor de eerste keer probeert...

Video: Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Multimodal 3D Printing of Phantoms to Simulate Biological Tissue

Biomedical optical imaging is playing an important role in diagnosis and treatment of various diseases. However, the accuracy and the reproducibility of an optical imaging device are greatly affected by the performance characteristics of its components, the test environment, and the operations. Therefore, it is necessary to calibrate these devices by traceable phantom standards. However, most of the currently available phantoms are homogeneous phantoms that cannot simulate multimodal and dynamic characteristics of biological tissue. Here, we show the fabrication of heterogeneous tissue-simulating phantoms using a production line integrating a spin coating module, a polyjet module, a fused deposition modeling (FDM) module, and an automatic control framework. The structural information and the optical parameters of a &#34;digital optical phantom&#34; are defined in a prototype file, imported to the production line, and fabricated layer-by-layer with sequential switch between different printing modalities. Technical capability of such a production line is exemplified by the automatic printing of skin-simulating phantoms that comprise the epidermis, dermis, subcutaneous tissue, and an embedded tumor.

Spin coating, polyjet printing, and fused deposition modeling are integrated to produce multilayered heterogeneous phantoms that simulate structural and functional properties of biological tissue.

Biomedical optical imaging is playing an important role in diagnosis and treatment of various diseases. However, the accuracy and the reproducibility of ...

Engineering

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving SSLE of Glass Crystals

A methodology is described herein for representing anatomical imaging data within crystals. We create scaled three-dimensional models of biomedical imaging data for use in Sub-Surface Laser Engraving (SSLE) of crystal glass. This tool offers a useful complement to computational display or three-dimensionally printed models used within clinical or educational settings.

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data ...

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

In this paper, we outline a method for surgical preparation that allows for the practical planning of a variety of neurosurgeries in NHPs solely using data extracted from magnetic resonance imaging (MRI). This protocol allows for the generation of 3D printed anatomically accurate physical models of the brain and skull, as well as an agarose gel model of the brain modeling some of the mechanical properties of the brain. These models can be extracted from MRI using brain extraction software for the model of the brain, and custom code for the model of the skull. The preparation protocol takes advantage of state-of-the-art 3D printing technology to make interfacing brains, skulls, and molds for gel brain models. The skull and brain models can be used to visualize brain tissue inside the skull with the addition of a craniotomy in the custom code, allowing for better preparation for surgeries directly involving the brain. The applications of these methods are designed for surgeries involved in neurological stimulation and recording as well as injection, but the versatility of the system allows for future expansion of the protocol, extraction techniques, and models to a wider scope of surgeries.

The method outlined below aims to provide a comprehensive protocol for the preparation of nonhuman primate (NHP) neurosurgery using a novel combination of three-dimensional (3D) printing methods and MRI data extraction.

In this paper, we outline a method for surgical preparation that allows for the practical planning of a variety of neurosurgeries in NHPs solely using ...

Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create anatomically accurate head phantoms with realistic brain imaging properties because standard fabrication methods are not optimized to replicate any patient-specific anatomical detail and 3D printing materials are not optimized for imaging properties. In order to test and validate a novel navigation system for use during brain tumor surgery, an anatomically accurate phantom with realistic imaging and mechanical properties was required. Therefore, a phantom was developed using real patient data as input and 3D printing of molds to fabricate a patient-specific head phantom comprising the skull, brain and tumor with both ultrasound and X-ray contrast. The phantom also had mechanical properties that allowed the phantom tissue to be manipulated in a similar manner to how human brain tissue is handled during surgery. The phantom was successfully tested during a surgical simulation in a virtual operating room.
The phantom fabrication method uses commercially available materials and is easy to reproduce. The 3D printing files can be readily shared, and the technique can be adapted to encompass many different types of tumor.

This protocol describes the fabrication of a patient specific skull, brain and tumor phantom. It uses 3D printing to create molds, and polyvinyl alcohol (PVA-c) is used as the tissue mimicking material.

Phantoms are essential tools for clinical training, surgical planning and the development of novel medical devices. However, it is challenging to create ...

3D Printing of Preclinical X-ray Computed Tomographic Data Sets

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing. Traditional, mold-injection methods to create models or parts have several limitations, the most important of which is a difficulty in making highly complex products in a timely, cost-effective manner.1 However, gradual improvements in three-dimensional printing technology have resulted in both high-end and economy instruments that are now available for the facile production of customized models.2 These printers have the ability to extrude high-resolution objects with enough detail to accurately represent in vivo images generated from a preclinical X-ray CT scanner. With proper data collection, surface rendering, and stereolithographic editing, it is now possible and inexpensive to rapidly produce detailed skeletal and soft tissue structures from X-ray CT data. Even in the early stages of development, the anatomical models produced by three-dimensional printing appeal to both educators and researchers who can utilize the technology to improve visualization proficiency. 3, 4 The real benefits of this method result from the tangible experience a researcher can have with data that cannot be adequately conveyed through a computer screen. The translation of pre-clinical 3D data to a physical object that is an exact copy of the test subject is a powerful tool for visualization and communication, especially for relating imaging research to students, or those in other fields. Here, we provide a detailed method for printing plastic models of bone and organ structures derived from X-ray CT scans utilizing an Albira X-ray CT system in conjunction with PMOD, ImageJ, Meshlab, Netfabb, and ReplicatorG software packages.

Using modern plastic extrusion and printing technologies, it is now possible to quickly and inexpensively produce physical models of X-ray CT data taken in a laboratory. The three -dimensional printing of tomographic data is a powerful visualization, research, and educational tool that may now be accessed by the preclinical imaging community.

Three-dimensional printing allows for the production of highly detailed objects through a process known as additive manufacturing.  Traditional, ...

Biology

Multicolor 3D Printing of Complex Intracranial Tumors in Neurosurgery

Three-dimensional (3D) printing technologies offer the possibility of visualizing patient-specific pathologies in a physical model of correct dimensions. The model can be used for planning and simulating critical steps of a surgical approach. Therefore, it is important that anatomical structures such as blood vessels inside a tumor can be printed to be colored not only on their surface, but throughout their whole volume. During simulation this allows for the removal of certain parts (e.g., with a high-speed drill) and revealing internally located structures of a different color. Thus, diagnostic information from various imaging modalities (e.g., CT, MRI) can be combined in a single compact and tangible object.
However, preparation and printing of such a fully colored anatomical model remains a difficult task. Therefore, a step-by-step guide is provided, demonstrating the fusion of different cross-sectional imaging data sets, segmentation of anatomical structures, and creation of a virtual model. In a second step the virtual model is printed with volumetrically colored anatomical structures using a plaster-based color 3D binder jetting technique. This method allows highly accurate reproduction of patient-specific anatomy as shown in a series of 3D-printed petrous apex chondrosarcomas. Furthermore, the models created can be cut and drilled, revealing internal structures that allow for simulation of surgical procedures.

The protocol describes the fabrication of fully colored three-dimensional prints of patient-specific, anatomical skull models to be used for surgical simulation. The crucial steps of combining different imaging modalities, image segmentation, three-dimensional model extraction, and production of the prints are explained.

Three-dimensional (3D) printing technologies offer the possibility of visualizing patient-specific pathologies in a physical model of correct dimensions. ...

Medicine

Combining Augmented Reality and 3D Printing to Display Patient Models on a Smartphone

Augmented reality (AR) has great potential in education, training, and surgical guidance in the medical field. Its combination with three-dimensional (3D) printing (3DP) opens new possibilities in clinical applications. Although these technologies have grown exponentially in recent years, their adoption by physicians is still limited, since they require extensive knowledge of engineering and software development. Therefore, the purpose of this protocol is to describe a step-by-step methodology enabling inexperienced users to create a smartphone app, which combines AR and 3DP for the visualization of anatomical 3D models of patients with a 3D-printed reference marker. The protocol describes how to create 3D virtual models of a patient&rsquo;s anatomy derived from 3D medical images. It then explains how to perform positioning of the 3D models with respect to marker references. Also provided are instructions for how to 3D print the required tools and models. Finally, steps to deploy the app are provided. The protocol is based on free and multi-platform software and can be applied to any medical imaging modality or patient. An alternative approach is described to provide automatic registration between a 3D-printed model created from a patient&rsquo;s anatomy and the projected holograms. As an example, a clinical case of a patient suffering from distal leg sarcoma is provided to illustrate the methodology. It is expected that this protocol will accelerate the adoption of AR and 3DP technologies by medical professionals.

Presented here is a method to design an augmented reality smartphone application for the visualization of anatomical three-dimensional models of patients using a 3D-printed reference marker.

Augmented reality (AR) has great potential in education, training, and surgical guidance in the medical field. Its combination with three-dimensional (3D) ...

Development and Evaluation of 3D-Printed Cardiovascular Phantoms for Interventional Planning and Training

Catheter-based interventions are standard treatment options for cardiovascular pathologies. Therefore, patient-specific models could help training physicians&#39; wire-skills as well as improving planning of interventional procedures. The aim of this study was to develop a manufacturing process of patient-specific 3D-printed models for cardiovascular interventions.
To create a 3D-printed elastic phantom, different 3D-printing materials were compared to porcine biological tissues (i.e., aortic tissue) in terms of mechanical characteristics. A fitting material was selected based on comparative tensile tests and specific material thicknesses were defined. Anonymized contrast-enhanced CT-datasets were collected retrospectively. Patient-specific volumetric models were extracted from these datasets and subsequently 3D-printed. A pulsatile flow loop was constructed to simulate the intraluminal blood flow during interventions. Models&#39; suitability for clinical imaging was assessed by x-ray imaging, CT, 4D-MRI and (Doppler) ultrasonography. Contrast medium was used to enhance visibility in x-ray-based imaging. Different catheterization techniques were applied to evaluate the 3D-printed phantoms in physicians&#39; training as well as for pre-interventional therapy planning.
Printed models showed a high printing resolution (~30 &#181;m) and mechanical properties of the chosen material were comparable to physiological biomechanics. Physical and digital models showed high anatomical accuracy when compared to the underlying radiological dataset. Printed models were suitable for ultrasonic imaging as well as standard x-rays. Doppler ultrasonography and 4D-MRI displayed flow patterns and landmark characteristics (i.e., turbulence, wall shear stress) matching native data. In a catheter-based laboratory setting, patient-specific phantoms were easy to catheterize. Therapy planning and training of interventional procedures on challenging anatomies (e.g., congenital heart disease (CHD)) was possible.
Flexible patient-specific cardiovascular phantoms were 3D-printed, and the application of common clinical imaging techniques was possible. This new process is ideal as a training tool for catheter-based (electrophysiological) interventions and can be used in patient-specific therapy planning.

Here we present development of a mock circulation setup for multimodal therapy evaluation, pre-interventional planning, and physician-training on cardiovascular anatomies. With the application of patient-specific tomographic scans, this setup is ideal for therapeutic approaches, training, and education in individualized medicine.

Catheter-based interventions are standard treatment options for cardiovascular pathologies. Therefore, patient-specific models could help training ...

Digital Hybrid Model Preparation for Virtual Planning of Reconstructive Dentoalveolar Surgical Procedures

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial registration, and free-form surface modeling. Firstly cone-beam computed tomography datasets were reconstructed with a semi-automatic segmentation method. Alveolar bone and teeth are separated into different segments, allowing 3D morphology, and localization of periodontal intrabony defects to be assessed. The severity, extent, and morphology of acute and chronic alveolar ridge defects are validated concerning adjacent teeth. On virtual complex tissue models, positions of dental implants can be planned in 3D. Utilizing spatial registration of IOS and CBCT data and subsequent free-form surface modeling, realistic 3D hybrid models can be acquired, visualizing alveolar bone, teeth, and soft tissues. With the superimposition of IOS and CBCT soft tissue, thickness above the edentulous ridge can be assessed about the underlying bone dimensions; therefore, flap design and surgical flap management can be determined, and occasional complications may be avoided.

A workflow for creating three-dimensional (3D) virtual hybrid models has been designed based on cone-beam computed tomography dataset and intraoral optical scans utilizing radiographic image segmentation methods and free-form surface modeling. Digital models are used for the virtual planning of reconstructive dentoalveolar surgical procedures.

Virtual, hybrid three-dimensional (3D) model acquisition is presented in this article, utilizing the sequence of radiographic image segmentation, spatial ...

A Personalized 3D-Printed Model for Preoperative Evaluation in Thyroid Surgery

The anatomic structure of the surgical area of thyroid cancer is complex. It is very important to comprehensively and carefully evaluate the tumor location and its relation with the capsule, trachea, esophagus, nerves, and blood vessels before operation. This paper introduces an innovative 3D-printed model establishment method based on computerized tomography (CT) DICOM images. We established a personalized 3D-printed model of the cervical thyroid surgery field for each patient who needed thyroid surgery to help clinicians evaluate the key points and difficulties of the surgery and select the operation methods of key parts as a basis. The results showed that this model is conducive to preoperative discussion and the formulation of operation strategies. In particular, as a result of the clear display of the recurrent laryngeal nerve and parathyroid gland locations in the thyroid operation field, injury to them can be avoided during surgery, the difficulty of thyroid surgery reduced, and the incidence of postoperative hypoparathyroidism and complications related to recurrent laryngeal nerve injury reduced too. Moreover, this 3D-printed model is intuitive and aids communication for the signing of informed consent by patients before surgery.

Here, a new method of establishing a personalized 3D-printed model for preoperative evaluation of thyroid surgery is proposed. It is conducive to preoperative discussion, reducing the difficulty of thyroid surgery.

Voxel Printing Anatomy: Design and Fabrication of Realistic, Presurgical Planning Models through Bitmap Printing

Samenvatting

Meer video's verkennen