This work was supported by a Vanderbilt Clinical Oncology Research Career Development Program (K12 NCI 2K12CA090625-22A1), the NIH/National Institute for Deafness and Communication Disorders (R25 DC020728), Vanderbilt-Ingram Cancer Center Support Grant (P30CA068485) and Swim Across America.

This protocol was performed at Vanderbilt University Medical Center under IRB#221597. Patients provided written consent for ex vivo 3D scanning and digital mapping of their surgical specimen prior to surgery and the addition of their scan to a 3D specimen model biorepository. Inclusion criteria were patients 18 and older with a suspected or biopsy-proven head and neck neoplasm undergoing surgical resection. 3D specimen maps were created based on surgeon and pathologist preference and staff availability.
This protocol follows the guidelines of the human research ethics committees of the Institutional Review Board (IRB#221597) at Vanderbilt University Medical Center. All subjects provided written informed consent prior to participation. All patient data have been de-identified.
1. Setting up the 3D scanner
<ol>
	<li>Identify a 3 x 2 ft flat workstation available for scanner setup. Ensure the workstation is a dark environment where the scanner is enclosed or that the lights in the room are turned off. Alternatively, perform 3D scanning within a mobile cart setup as seen in Figure 1.</li>
	<li>Set up the three-legged camera tripod on the flat workstation. Carefully place the 3D scanning camera into the tripod. Angle the camera down toward the workstation at a 60&#176; angle.</li>
	<li>Connect the two-part power cord to an external power source and the back of the camera.</li>
	<li>Place the scanner turntable 1 foot in front of the 3D camera and tripod setup. Connect the turntable to the camera using the micro-USB cable.</li>
	<li>Connect the camera to the laptop computer using the camera to USB cable. See Figure 2 for the labeled setup. 
	NOTE: If the laptop computer does not have a USB port, an external USB adapter may be required. An external mouse is recommended.</li>
	<li>Turn off the lights in the workstation to calibrate the scanner to current lighting conditions.</li>
	<li>Press and hold the power button on the back of the camera until a blue light appears.</li>
	<li>Open the 3D capture software on the computer desktop. Center the turntable in the cross projected by the camera. 
	&#8203;NOTE: Ensure the camera is powered on and the lights are off prior to opening the software.</li>
</ol>
2. Specimen handling
<ol>
	<li>Obtain the resected oncologic specimen from the surgical team.</li>
	<li>Rinse the specimen to remove any blood or excess clots from resection. Gently pat dry. 
	NOTE: This step is very important to obtain a high-quality scan. The 3D scanner has difficulty picking up data when a specimen is very shiny or has residual blood on the surface.</li>
	<li>Place the specimen on a flat, clean surface.</li>
	<li>Using a smartphone camera or digital camera, obtain high-quality 2D images of the specimen. Obtain one photograph of the anterior surface of the specimen. Flip the specimen over exactly 180&#176; and obtain a second photograph of the posterior surface of the specimen.</li>
</ol>
3. 3D scanning following en bloc resection of solid tumor
<ol>
	<li>Place a thin sheet of plastic on the 3D scanner turntable to protect the target points from human tissue. Place the specimen onto the plastic sheet with the anterior surface facing up.</li>
	<li>Click on the 3D scanner software application on the desktop of the laptop.</li>
	<li>Click on the 3D scanner icon on the right side of the screen. Click on the New Work button.</li>
	<li>Create a new folder, using a naming convention that is easy to understand. 
	NOTE: Naming convention recommendation: YYYY-MM-DD_SPECIMENTYPE</li>
	<li>Click on Texture Scan. Leave the open global markers file section blank.</li>
	<li>Adjust all fixed settings in the menu on the left side of the screen (Figure 3). Select HDR OFF. select the ON option for With Turntable. Set align mode = Turntable Coded Targets, turntable steps = 8, turntable speed = 10, and turntable turns = One Turn.</li>
	<li>Adjust the brightness by sliding the brightness slider bar to the right to maximize the exposure (redness) on the dark surfaces of the specimen as demonstrated in Figure 3. 
	NOTE: Attempt to maximize the exposure (redness) on the dark-colored parts of the specimen (muscle, soft tissue) without overexposing (too red) the light-colored parts of the specimen (bone, teeth).</li>
	<li>Click on the triangle play button on the right-hand toolbar labeled Start Scan or press the spacebar to start the first round of scanning. Wait for the platform to complete all eight rotations (~4 min). Do not touch the scanner or turntable during this step.</li>
	<li>Once complete, rotate the scan to see if there are any scan data captured outside the green dots displayed on the screen or any obvious artifact. Once satisfied, click on the checkmark on the right side of the edit screen to proceed to the next half of the scan.
	<ol>
		<li>If any artifact is discovered, press Shift and use the cursor to drag a circle around the artifact outside the intended scan. Look for a red circle that appears around the unwanted artifact. Click on the Delete data button on the right-hand toolbar designated by a garbage can icon.</li>
	</ol>
	</li>
	<li>Using gloves, flip over the specimen to expose the opposite surface. Adjust the brightness as necessary, and keep all other settings the same. Repeat steps 3.8-3.9.</li>
</ol>
4. Alignment and meshing
<ol>
	<li>The program will attempt to automatically align the specimen. If the alignment is accurate (rare), proceed to step 4.4. If the alignment is poor (see note), continue to step 4.2. 
	NOTE: Accurate alignment is characterized by a fully formed specimen without any gapping or overlap on the sides. The yellow portions represent the inside of the scan and optimal alignment shows the least amount of yellow as possible.</li>
	<li>For manual alignment, press the align button indicated by a puzzle piece on the right-hand toolbar.</li>
	<li>Perform three-point cross-registration to geometrically align the two 3D scans.
	<ol>
		<li>Click and drag one set of scan data (Group 1 and Group 2) into each of the alignment frames. Place Group 1 in the Fixed box and Group 2 in the Floated box.</li>
		<li>Use the right-click function to rotate and position the two halves so that one side shows the outside of the specimen (3D scanned surface) and the other half shows the inside of the specimen (yellow). Orient the two halves such that the silhouettes create the same shape if superimposed. Use the middle scroll button on the mouse to zoom in and out on the specimen.</li>
		<li>Identify three clear landmarks on each set of scan data to pick as alignment points that are present on both sets of data. 
		NOTE: Choose three points that are roughly equidistant from each other on the edges of the specimen. Use the unique topography of the scans to choose these points.</li>
		<li>Press shift and left-click to select the first of three corresponding alignment points on each group of data as described above. Following selection by clicking the two corresponding points, look for a red dot that appears in the chosen corresponding positions. Repeat this process 2x and look for green dots to appear for the second set of chosen alignment points and orange dots for the third set.</li>
		<li>Look for the alignment result to appear in the larger pane below the two halves. If the scan is aligned well (see NOTE in section 4.1 for optimal alignment recommendations), proceed to step 4.4. To repeat the alignment process, proceed to step 4.3.6.</li>
		<li>To re-select the alignment points, simply press the Control key + Z key to undo previous work or click on the X box in the top right corner of each pane and return to step 4.3.1.</li>
		<li>Perform these steps until the alignment result preview is accurate.</li>
	</ol>
	</li>
	<li>Select the square Global Optimization button on the bottom right toolbar. Proceed through the optimization screens, clicking the Confirm button each time it is prompted.</li>
	<li>Once optimization is complete, select the triangular Mesh Model button on the bottom right side of the screen.</li>
	<li>Choose the watertight model option when prompted. Click on the option for Medium Detail. 
	NOTE: High detail takes much longer to render and is not visually better than medium detail.</li>
	<li>Use the slider bars that appear on the left hand side of the screen to adjust the brightness to 50 and the contrast to 0 when prompted.</li>
	<li>Click on the Save Your Scan button at the bottom right toolbar. Keep the scaling ratio at 100% to preserve all original dimensions of the specimen.</li>
	<li>Export the model into 3MF and OBJ file formats and save the file within the folder created at the beginning of the scan. Use the naming convention as outlined in step 2.3.</li>
</ol>
5. Cleanup
<ol>
	<li>Using gloves, remove the specimen from the turn table. Return the specimen safely to the pathology team.</li>
	<li>Remove the plastic sheet and sanitize it with a wipe. Return it to its bag.</li>
	<li>Return the scanner turntable and camera to their respective slots in the box. Ensure the camera is protected with a plastic bag or a box.</li>
	<li>Unplug all cords and replace them in the box.</li>
	<li>Clean the scanning area with a sanitizing wipe.</li>
</ol>
6. Virtual 3D specimen mapping
<ol>
	<li>When the specimen is ready for processing, set up the workstation to work alongside the pathology team member who will be grossing the specimen. 
	NOTE: It is helpful to utilize a rolling computer stand to allow for mobility and to facilitate communication with the pathology team.</li>
	<li>Set up the laptop computer and external mouse on the workstation. Open the computer-aided design software from the laptop desktop to virtually annotate the 3D model.</li>
	<li>Click on the Import button indicated by the plus sign icon and import the previously saved 3mf file of the raw scan from step 4.9. 
	NOTE: This software does not have an erase function; it only allows the user to undo prior work by pressing Ctrl Z. Be wary that the user cannot go back and change or erase markings on the specimen once the map is saved.</li>
	<li>Virtual inking
	<ol>
		<li>Select the paintbrush tool on size setting 15-30 to outline the borders of each inked region. Use the color palette to graphically represent each inked surface using software paint colors concurrent with the true ink colors.</li>
		<li>Use the paintbrush tool on size setting 35-45 to fill in each inked section with its corresponding color.</li>
		<li>Confirm with the prosector that all inked sides are correct and take note of the anatomic orientation (anterior, posterior, medial, lateral, deep) of each inked side for the key.</li>
	</ol>
	</li>
	<li>Margin sampling
	<ol>
		<li>Use the paintbrush tool on size setting 20-25 to diagram perpendicular and shave (en face) margins, distinguished using color coding. 
		NOTE: For example, use white to denote perpendicular margins and fuschia to denote shave margins.</li>
		<li>Label each sampled section with the number or letter that corresponds to the cassette each section is placed within.</li>
	</ol>
	</li>
	<li>Plane cuts
	<ol>
		<li>For any plane cuts (i.e., breadloaf cuts completely through the specimen), select the Plane Cut tool from the left-side toolbar. Select Keep Both in the upper left hand toolbar.</li>
		<li>Draw the plane cuts through the specimen exactly as the prosector performed. Ensure that the cuts are correct and then click on accept.</li>
	</ol>
	</li>
	<li>3D specimen map completion and export
	<ol>
		<li>Confirm with the prosector to verify the accuracy of the completed 3D specimen map. Revise any discrepancies and finalize the map. 
		NOTE: An example of a completed specimen map is shown in Figure 4.</li>
		<li>In the upper toolbar, click File | Save to save the specimen map. Click File | Export | select .3mf to export the file as a .3mf file.</li>
	</ol>
	</li>
</ol>
7. Creating a distributable video
<ol>
	<li>Open the presentation software from the laptop desktop.</li>
	<li>Title the slide file with the corresponding name of the specimen that was mapped.</li>
	<li>Insert the 2D images taken of the specimen and arrange them on one side of the slide.</li>
	<li>Select Insert from the top toolbar. Click on the rubber duck icon and select Insert 3D model.</li>
	<li>Import the .3mf file of the raw scan generated in step 4.9 and the .3mf file of the mapped specimen generated in step 6.7.2.</li>
	<li>Arrange the 3D models with the raw scan and mapped scan side by side. Arrange the two models so they are in the same orientation/alignment and are the same size.</li>
	<li>Click on Animations on the upper toolbar | select model #1 | select Add animation | Turntable | change the duration to 10 s | select On click.</li>
	<li>Select model #2 and repeat step 6.8 for the mapped scan, but at the last step, select With previous instead of On click.</li>
	<li>Select model #1 and repeat step 6.8, but select Effect Options, change the turntable direction to Up, and select After previous.</li>
	<li>Select model #2 and repeat step 7.9, but at the last step, select With previous.</li>
	<li>Select the Animation Pane and click on Play all to check that the scans are rotating at the same time in the same direction.</li>
	<li>To create a shareable video, click on File | Export | Create video | select medium size file to export a .mp4 video to be shared by email or integrated into a presentation. 
	NOTE: An example of the final video is shown in Figure 5.</li>
</ol>

Advanced CAD Imaging for Surgical Margin Analysis in Cancer Care

<ol>
	<li>Looser, K. G., Shah, J. P., Strong, E. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+significance+of+&amp;#34;positive&amp;#34;+margins+in+surgically+resected+epidermoid+carcinomas.">The significance of &amp;#34;positive&amp;#34; margins in surgically resected epidermoid carcinomas.</a> Head Neck Surg. 1 (2), 107-111 (1978).</li><li>Binahmed, A., Nason, R. W., Abdoh, A. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+clinical+significance+of+the+positive+surgical+margin+in+oral+cancer.">The clinical significance of the positive surgical margin in oral cancer.</a> Oral Oncol. 43 (8), 780-784 (2007).</li><li>Orosco, R. K., 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=Positive+surgical+margins+in+the+10+most+common+solid+cancers.">Positive surgical margins in the 10 most common solid cancers.</a> Sci Rep. 8 (1), 5686 (2018).</li><li>Prasad, K., 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=Trends+in+positive+surgical+margins+in+cT3-T4+oral+cavity+squamous+cell+carcinoma.">Trends in positive surgical margins in cT3-T4 oral cavity squamous cell carcinoma.</a> Otolaryngol Head Neck Surg. 169 (5), 1200-1207 (2023).</li><li>Byers, R. M., Bland, K. I., Borlase, B., Luna, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+prognostic+and+therapeutic+value+of+frozen+section+determinations+in+the+surgical+treatment+of+squamous+carcinoma+of+the+head+and+neck.">The prognostic and therapeutic value of frozen section determinations in the surgical treatment of squamous carcinoma of the head and neck.</a> Am J Surg. 136 (4), 525-528 (1978).</li><li>DiNardo, L. J., Lin, J., Karageorge, L. S., Powers, C. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Accuracy,+utility,+and+cost+of+frozen+section+margins+in+head+and+neck+cancer+surgery.">Accuracy, utility, and cost of frozen section margins in head and neck cancer surgery.</a> Laryngoscope. 110 (10 Pt 1), 1773-1776 (2000).</li><li>Gandour-Edwards, R. F., Donald, P. J., Lie, J. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+utility+of+intraoperative+frozen+section+diagnosis+in+head+and+neck+surgery:+a+quality+assurance+perspective.">Clinical utility of intraoperative frozen section diagnosis in head and neck surgery: a quality assurance perspective.</a> Head Neck. 15 (5), 373-376 (1993).</li><li>Ikemura, K., Ohya, 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+accuracy+and+usefulness+of+frozen-section+diagnosis.">The accuracy and usefulness of frozen-section diagnosis.</a> Head Neck. 12 (4), 298-302 (1990).</li><li>Remsen, K. A., Lucente, F. E., Biller, H. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Reliability+of+frozen+section+diagnosis+in+head+and+neck+neoplasms.">Reliability of frozen section diagnosis in head and neck neoplasms.</a> Laryngoscope. 94 (4), 519-524 (1984).</li><li>Weinstock, Y. E., Alava, I., Dierks, E. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Pitfalls+in+determining+head+and+neck+surgical+margins.">Pitfalls in determining head and neck surgical margins.</a> Oral Maxillofac Surg Clin North Am. 26 (2), 151-162 (2014).</li><li>Catanzaro, S., 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=Intraoperative+navigation+in+complex+head+and+neck+resections:+indications+and+limits.">Intraoperative navigation in complex head and neck resections: indications and limits.</a> Int J Comput Assist Radiol Surg. 12 (5), 881-887 (2017).</li><li>Black, C., Marotti, J., Zarovnaya, E., Paydarfar, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Critical+evaluation+of+frozen+section+margins+in+head+and+neck+cancer+resections.">Critical evaluation of frozen section margins in head and neck cancer resections.</a> Cancer. 107 (12), 2792-2800 (2006).</li><li>Miller, 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=Virtual+3D+specimen+mapping+in+head+&amp;+neck+oncologic+surgery.">Virtual 3D specimen mapping in head &amp; neck oncologic surgery.</a> Laryngoscope. , (2023).</li><li>Sharif, K. F., 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=The+computer-aided+design+margin:+Ex+vivo+3D+specimen+mapping+to+improve+communication+between+surgeons+and+pathologists.">The computer-aided design margin: Ex vivo 3D specimen mapping to improve communication between surgeons and pathologists.</a> Head Neck. 45 (1), 22-31 (2023).</li><li>Sharif, K. F., 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=Enhanced+intraoperative+communication+of+tumor+margins+using+3D+scanning+and+mapping:+the+computer-aided+design+margin.">Enhanced intraoperative communication of tumor margins using 3D scanning and mapping: the computer-aided design margin.</a> The Laryngoscope. 133 (8), 1914-1918 (2023).</li></ol>

The authors have no competing financial interests to be disclosed.

Traditionally, there is no visual representation of a resected cancer specimen. Pathologic processing often destroys the specimen. Prior work has demonstrated the feasibility and utility of 3D scanning of oncologic specimens followed by virtual annotation of the models to create 3D specimen maps which are representative of pathologic processing13,14,15. This provides the multidisciplinary care team with a visual model of the ana...

The goal of oncologic resection is the complete removal of cancer with surgical margins microscopically clear of tumor cells. In head and neck cancer, the surgical margin status is the most important pathologic risk factor1. A positive surgical margin increases the risk of 5-year local recurrence and all-cause mortality by &#62;90%2. Despite advances in medical technology and surgical techniques in recent years, positive margin rates in head and neck cancer remain high3. For locally advanced oral cavity cancers, the positive margin rate within the United States is 18.1%4.
For head and neck surgeons to ensure complete oncologic resection while minimizing disruption of surrounding structures, intraoperative sampling of margins via frozen section analysis (FSA) is performed. FSA provides a rapid intraoperative pathology consultation that is widely used and is the standard of care5,6,7,8,9. Fresh tissue is frozen, thinly sliced, placed on a glass slide, and stained for immediate interpretation while the patient is still under anesthesia.
Head and neck oncologic specimens present several distinct challenges in accurately assessing margin status, including the anatomic complexity of head and neck cancer specimens, the minimal reserve in the head and neck region for wide excision given the proximity to vital structures such as the eyes, face, and important nerves and vasculature, and the multiple tissue types often present in the resected specimen (i.e., mucosa, cartilage, muscle, bone)10,11. Thus, a specimen-based approach to margin analysis requires an enhanced level of communication between surgeon and pathologist12. A face-to-face conversation is often warranted to ensure correct specimen orientation and discussion of concerning margins. However, this is not always safe or feasible as it requires either the surgeon to leave the operating room (OR) while the patient remains under general anesthesia or the pathologist to leave the gross pathology lab, interrupting their workflow. In addition, there may be a significant travel time between the OR and the pathology lab, or in some cases, the pathology lab may be off-site altogether.
Following FSA, the oncologic specimen is fixed in formalin and formally processed through inking, sectioning, and margin sampling. Slides are created and microscopically interpreted by the pathologist to create a final pathology report. For complex head and neck cancer resection, this can often take 1-2 weeks. Unfortunately, processing of the specimen commonly results in the destruction of the resected cancer specimen. This may create further confusion as the final pathology report, multidisciplinary tumor board discussions, adjuvant radiation therapy planning, and re-resection in the setting of positive margins, must all proceed without a visual record of the oncologic specimen and its pathologic processing.
To address this clinical unmet need, we have developed a 3D scanning and specimen mapping protocol to enhance communication between surgeons, pathologists, and other members of the multidisciplinary cancer care team.

<table><tbody><tr><td>Computer Aided Design Software</td><td>MeshMixer</td><td></td><td>Virtual annotation software for 3D models</td></tr><tr><td>Digital Camera or Cameraphone</td><td>iPhone</td><td></td><td>May use iPhone camera or any digital camera available&amp;nbsp;</td></tr><tr><td>EinScan SP V2 Platinum Desktop 3D Scanner</td><td>Shining 3D</td><td></td><td>3D scanner hardware</td></tr><tr><td>ExScan Software; Solid Edge SHINING 3D Edition</td><td>Shining 3D</td><td></td><td>3D capture software included with purchase of 3D Scanner</td></tr><tr><td>External Mouse</td><td>Microsoft&amp;nbsp;</td><td></td><td></td></tr><tr><td>Laptop Computer</td><td>Dell XP5</td><td>00355-60734-40310-AAOEM</td><td>Laptop Requirements:&lt;br/&gt; USB: 1 &amp;times;USB 2.0 or 3.0; OS: Win 7, 8 or 10 (64 bit);&lt;br/&gt; Graphic Card: Nvidia series; Graphic memory: &gt;1 G;&lt;br/&gt; CPU: Dual-core i5 or higher; Memory: &gt;8 G</td></tr><tr><td>Microsoft Office Suite</td><td>Microsoft</td><td></td><td></td></tr><tr><td>Mobile Presentation Cart</td><td>Oklahoma Sound</td><td>PRC450</td><td></td></tr><tr><td>PowerPoint Software</td><td>Microsoft Office</td><td></td><td>Presentation software</td></tr><tr><td>Sit-Stand Mobile Desk Cart</td><td>Seville Classics</td><td></td><td></td></tr><tr><td>USB-c Device Converter</td><td>TRIPP-LITE</td><td>U442-DOCK3-B</td><td>Necessary only if laptop does not have USB</td></tr></tbody></table>

enhanced communication of tumor margins using 3d scanning and mapping

After oncologic resection of malignant tumors, specimens are sent to pathology for processing to determine the surgical margin status. These results are communicated in the form of a written pathology report. The current standard-of-care pathology report provides a written description of the specimen and the sites of margin sampling without any visual representation of the resected tissue. The specimen itself is typically destroyed during sectioning and analysis. This often leads to challenging communication between pathologists and surgeons when the final pathology report is confirmed. Furthermore, surgeons and pathologists are the only members of the multidisciplinary cancer care team to visualize the resected cancer specimen. We have developed a 3D scanning and specimen mapping protocol to address this unmet need. Computer-aided design (CAD) software is used to annotate the virtual specimen clearly showing sites of inking and margin sampling. This map can be utilized by various members of the multidisciplinary cancer care team.

From October 2021 to April 2023, 28 head and neck oncologic specimens were 3D scanned and virtually mapped according to this protocol. These results were previously published13. The majority of the surgical specimens were squamous cell carcinoma (SCC) (86%, n = 24), with the most common anatomic subsites being oral cavity (54%, n = 15) and larynx (29%, n = 8).
In all cases, specimen maps were shared with attending surgeons and pathologists prior to the evaluation of the...

Watch this Scientific Journal Video about Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping at JoVE.com

Author Spotlight: 3D Scanning and Augmented Reality for Enhanced Cancer Surgery Communication

A novel method for 3D scanning and virtual mapping of cancer resections is proposed with the goal of improving communication among the multidisciplinary cancer care team.

Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping

After oncologic resection of malignant tumors, specimens are sent to pathology for processing to determine the surgical margin status. These results are ...

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Research

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Medicine

599 Views.  Vanderbilt University Medical Center. De reikwijdte van ons onderzoek is het gebruik van 3D-scanning en augmented reality-technologie om de communicatie van de resultaten van kankeroperaties tussen het multidisciplinaire kankerzorgteam te verbeteren. Meer specifiek hopen we een chirurg in staat te stellen kanker nauwkeuriger te re-ecteren en nauwkeurigere bestralingstherapie mogelijk te maken. In de ziekenhuisomgeving is de ruimte vaak beperkt en kan het moeilijk zijn om extra ruimte te vinden voor extra personeel en apparatuur.

Video: Auteur in de schijnwerpers: 3D-scannen en augmented reality voor verbeterde communicatie over kankerchirurgie

Multi-photon Imaging of Tumor Cell Invasion in an Orthotopic Mouse Model of Oral Squamous Cell Carcinoma

Loco-regional invasion of head and neck cancer is linked to metastatic risk and presents a difficult challenge in designing and implementing patient management strategies. Orthotopic mouse models of oral cancer have been developed to facilitate the study of factors that impact invasion and serve as model system for evaluating anti-tumor therapeutics. In these systems, visualization of disseminated tumor cells within oral cavity tissues has typically been conducted by either conventional histology or with in vivo bioluminescent methods. A primary drawback of these techniques is the inherent inability to accurately visualize and quantify early tumor cell invasion arising from the primary site in three dimensions. Here we describe a protocol that combines an established model for squamous cell carcinoma of the tongue (SCOT) with two-photon imaging to allow multi-vectorial visualization of lingual tumor spread. The OSC-19 head and neck tumor cell line was stably engineered to express the F-actin binding peptide LifeAct fused to the mCherry fluorescent protein (LifeAct-mCherry). Fox1nu/nu mice injected with these cells reliably form tumors that allow the tongue to be visualized by ex-vivo application of two-photon microscopy. This technique allows for the orthotopic visualization of the tumor mass and locally invading cells in excised tongues without disruption of the regional tumor microenvironment. In addition, this system allows for the quantification of tumor cell invasion by calculating distances that invaded cells move from the primary tumor site. Overall this procedure provides an enhanced model system for analyzing factors that contribute to SCOT invasion and therapeutic treatments tailored to prevent local invasion and distant metastatic spread. This method also has the potential to be ultimately combined with other imaging modalities in an in vivo setting.

A comprehensive overview of the techniques involved in generating a mouse model of oral cancer and quantitative monitoring of tumor invasion within the tongue through multi-photon microscopy of labeled cells is presented. This system can serve as a useful platform for the molecular assessment and drug efficacy of anti-invasive compounds.

Loco-regional invasion of head and neck cancer is linked to metastatic risk and presents a difficult challenge in designing and implementing patient ...

Characterization of Tumor Cells Using a Medical Wire for Capturing Circulating Tumor Cells: A 3D Approach Based on Immunofluorescence and DNA FISH

Circulating tumor cells (CTCs) are associated with poor survival in metastatic cancer. Their identification, phenotyping, and genotyping could lead to a better understanding of tumor heterogeneity and thus facilitate the selection of patients for personalized treatment. However, this is hampered because of the rarity of CTCs. We present an innovative approach for sampling a high volume of the patient blood and obtaining information about presence, phenotype, and gene translocation of CTCs. The method combines immunofluorescence staining and DNA fluorescent-in-situ-hybridization (DNA FISH) and is based on a functionalized medical wire. This wire is an innovative device that permits the in vivo isolation of CTCs from a large volume of peripheral blood. The blood volume screened by a 30-min administration of the wire is approximately 1.5-3 L. To demonstrate the feasibility of this approach, epithelial cell adhesion molecule (EpCAM) expression and the chromosomal translocation of the ALK gene were determined in non-small-cell lung cancer (NSCLC) cell lines captured by the functionalized wire and stained with an immuno-DNA FISH approach. Our main challenge was to perform the assay on a 3D structure, the functionalized wire, and to determine immuno-phenotype and FISH signals on this support using a conventional fluorescence microscope. The results obtained indicate that catching CTCs and analyzing their phenotype and chromosomal rearrangement could potentially represent a new companion diagnostic approach and provide an innovative strategy for improving personalized cancer treatments.

We present a new approach to characterize tumor cells. We combined immunofluorescence with DNA fluorescent-in-situ-hybridization to evaluate cells captured by a functionalized medical wire capable of in vivo enriching CTCs directly from patient blood.

Circulating tumor cells (CTCs) are associated with poor survival in metastatic cancer. Their identification, phenotyping, and genotyping could lead to a ...

Cancer Research

Quantifying the Brain Metastatic Tumor Micro-Environment using an Organ-On-A Chip 3D Model, Machine Learning, and Confocal Tomography

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, depending on the cancer type. To reduce the brain metastatic tumor burden, gaps in basic and translational knowledge need to be addressed. Major challenges include a paucity of reproducible preclinical models and associated tools. Three-dimensional models of brain metastasis can yield the relevant molecular and phenotypic data used to address these needs when combined with dedicated analysis tools. Moreover, compared to murine models, organ-on-a-chip models of patient tumor cells traversing the blood brain barrier into the brain microenvironment generate results rapidly and are more interpretable with quantitative methods, thus amenable to high throughput testing. Here we describe and demonstrate the use of a novel 3D microfluidic blood brain niche (&#181;mBBN) platform where multiple elements of the niche can be cultured for an extended period (several days), fluorescently imaged by confocal microscopy, and the images reconstructed using an innovative confocal tomography technique; all aimed to understand the development of micro-metastasis and changes to the tumor micro-environment (TME) in a repeatable and quantitative manner. We demonstrate how to fabricate, seed, image, and analyze the cancer cells and TME cellular and humoral components, using this platform. Moreover, we show how artificial intelligence (AI) is used to identify the intrinsic phenotypic differences of cancer cells that are capable of transit through a model &#181;mBBN and to assign them an objective index of brain metastatic potential. The data sets generated by this method can be used to answer basic and translational questions about metastasis, the efficacy of therapeutic strategies, and the role of the TME in both.

Here, we present a protocol for preparing and culturing a blood brain barrier metastatic tumor micro-environment and then quantifying its state using confocal imaging and artificial intelligence (machine learning).

Brain metastases are the most lethal cancer lesions; 10-30% of all cancers metastasize to the brain, with a median survival of only ~5-20 months, ...

Dual-phase Cone-beam Computed Tomography to See, Reach, and Treat Hepatocellular Carcinoma during Drug-eluting Beads Transarterial Chemo-embolization

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 dimensional&#160;(3D) diagnostic imaging in the interventional suite and can enhance minimally-invasive therapy beyond the limitations of 2D angiography alone. The role of CBCT has been recognized in transarterial chemo-embolization (TACE) treatment of hepatocellular carcinoma (HCC). The recent introduction of a CBCT technique: dual-phase CBCT (DP-CBCT) improves intra-arterial HCC treatment with drug-eluting beads (DEB-TACE). DP-CBCT can be used to localize liver tumors with the diagnostic accuracy of multi-phasic multidetector computed tomography (M-MDCT) and contrast enhanced magnetic resonance imaging (CE-MRI) (See the tumor), to guide intra-arterially guidewire and microcatheter to the desired location for selective therapy (Reach the tumor), and to evaluate treatment success during the procedure (Treat the tumor). The purpose of this manuscript is to illustrate how DP-CBCT is used in DEB-TACE to see, reach, and treat HCC.

Dual-phase cone-beam computed tomography (DP-CBCT) is a useful intraprocedural imaging technique for transarterial chemo-embolization treatment with drug-eluting beads of hepatocellular carcinoma. DP-CBCT has been used to perform three major steps in oncologic interventional radiology: tumor localization (see), navigation and intraprocedural catheter guidance (reach), and intraprocedural evaluation of treatment success (treat).

The advent of cone-beam computed tomography (CBCT) in the angiography suite has been revolutionary in interventional radiology. CBCT offers 3 ...

A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment

The ability to visualize complex and dynamic physiological interactions between numerous cell types and the extracellular matrix (ECM) within a live tumor microenvironment is an important step toward understanding mechanisms that regulate tumor progression. While this can be accomplished through current intravital imaging techniques, it remains challenging due to the heterogeneous nature of tissues and the need for spatial context within the experimental observation. To this end, we have developed an intravital imaging workflow that pairs collagen second harmonic generation imaging, endogenous fluorescence from the metabolic co-factor NAD(P)H, and fluorescence lifetime imaging microscopy (FLIM) as a means to non-invasively compartmentalize the tumor microenvironment into basic domains of the tumor nest, the surrounding stroma or ECM, and the vasculature. This non-invasive protocol details the step-by-step process ranging from the acquisition of time-lapse images of mammary tumor models to post-processing analysis and image segmentation. The primary advantage of this workflow is that it exploits metabolic signatures to contextualize the dynamically changing live tumor microenvironment without the use of exogenous fluorescent labels, making it advantageous for human patient-derived xenograft (PDX) models and future clinical use where extrinsic fluorophores are not readily applicable.

The intravital imaging method described here utilizes collagen second harmonic generation and endogenous fluorescence from the metabolic co-factor NAD(P)H to non-invasively segment an unlabeled tumor microenvironment into tumor, stromal, and vascular compartments for in-depth analysis of 4D intravital images.

The ability to visualize complex and dynamic physiological interactions between numerous cell types and the extracellular matrix (ECM) within a live tumor ...

Guided Tumor Inoculation and Multimodal Imaging in Mice

A Dorsal Skinfold Window Chamber Tumor Mouse Model for Combined Intravital Microscopy and Magnetic Resonance Imaging in Translational Cancer Research

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the tumor microenvironment and its response to therapy. These imaging modalities have micron-scale resolution but have limited use in the clinic due to their shallow penetration depth into tissue. More clinically applicable imaging modalities such as CT, MRI, and PET have much greater penetration depth but have comparatively lower spatial resolution (mm scale). 
To translate preclinical intravital imaging findings into the clinic, new methods must be developed to bridge this micro-to-macro resolution gap. Here we describe a dorsal skinfold window chamber tumor mouse model designed to enable preclinical intravital and clinically applicable (CT and MR) imaging in the same animal, and the image analysis platform that links these two disparate visualization methods. Importantly, the described window chamber approach enables the different imaging modalities to be co-registered in 3D using fiducial markers on the window chamber for direct spatial concordance. This model can be used for validation of existing clinical imaging methods, as well as for the development of new ones through direct correlation with "ground truth" high-resolution intravital findings. 
Finally, the tumor response to various treatments-chemotherapy, radiotherapy, photodynamic therapy-can be monitored longitudinally with this methodology using preclinical and clinically applicable imaging modalities. The dorsal skinfold window chamber tumor mouse model and imaging platforms described here can thus be used in a variety of cancer research studies, for example, in translating preclinical intravital microscopy findings to more clinically applicable imaging modalities such as CT or MRI.

Author Spotlight: Integrating High-Resolution Intravital Imaging and MRI to Enhance Stereotactic Body Radiation Therapy Planning

Translation of Intravital microscopy findings is challenged by its shallow depth penetration into tissue. Here we describe a dorsal window chamber mouse model that enables co-registration of intravital microscopy and clinically applicable imaging modalities (e.g., CT, MRI) for direct spatial correlation, potentially streamlining clinical translation of intravital microscopy findings.

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the ...

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

The immune landscape of the tumor microenvironment (TME) is a determining factor in cancer progression and response to therapy. Specifically, the density and the location of immune cells in the TME have important diagnostic and prognostic values. Multiomic profiling of the TME has exponentially increased our understanding of the numerous cellular and molecular networks regulating tumor initiation and progression. However, these techniques do not provide information about the spatial organization of cells or cell-cell interactions. Affordable, accessible, and easy to execute multiplexing techniques that allow spatial resolution of immune cells in tissue sections are needed to complement single cell-based high-throughput technologies. Here, we describe a strategy that integrates serial imaging, sequential labeling, and image alignment to generate virtual multiparameter slides of whole tissue sections. Virtual slides are subsequently analyzed in an automated fashion using user-defined protocols that enable identification, quantification, and mapping of cell populations of interest. The image analysis is done, in this case using the analysis modules Tissuealign, Author, and HISTOmap. We present an example where we applied this strategy successfully to one clinical specimen, maximizing the information that can be obtained from limited tissue samples and providing an unbiased view of the TME in the entire tissue section.

Here, we describe a simple and accessible strategy for visualizing, quantifying, and mapping immune cells in formalin-fixed paraffin-embedded tumor tissue sections. This methodology combines existing imaging and digital analysis techniques with the purpose of expanding the multiplexing capability and multiparameter analysis of imaging assays.

The immune landscape of the tumor microenvironment (TME) is a determining factor in cancer progression and response to therapy. Specifically, the density ...

Immunology and Infection

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. ...

Computer-Aided Three-Dimensional Visualization in the Treatment of Locally Advanced Thyroid Cancer

The diagnosis and treatment of locally advanced thyroid carcinoma are challenging. The challenge lies in the evaluation of the tumor scope and the formulation of an individualized treatment plan. Three-dimensional (3D) visualization has a wide range of applications in the field of medicine, although there are limited applications in thyroid cancer. We previously applied 3D visualization for the diagnosis and treatment of thyroid cancer. Through data collection, 3D modeling, and preoperative evaluation, we can obtain 3D information regarding the tumor outline, determine the extent of tumor invasion, and conduct adequate preoperative preparation and surgical risk assessment. This study aimed to demonstrate the feasibility of 3D visualization in locally advanced thyroid cancer. Computer-aided 3D visualization can be an effective method for accurate preoperative evaluation, the development of surgical methods, shortening the surgical time, and reducing the surgical risks. Furthermore, it can contribute to medical education and doctor-patient communication. We believe that the application of 3D visualization technology can improve outcomes and quality of life in patients with locally advanced thyroid cancer.

In diagnosing and treating locally advanced thyroid cancer, the application of computer-aided three-dimensional reconstruction can provide additional information regarding the tumor scope and anatomic characteristics, thereby assisting in risk assessment and surgical planning.

The diagnosis and treatment of locally advanced thyroid carcinoma are challenging. The challenge lies in the evaluation of the tumor scope and the ...

Enhancing Tumor Content through Tumor Macrodissection

The presence of contaminating non-tumor tissues in formalin-fixed paraffin-embedded (FFPE) tissues can greatly undermine genomic studies. Herein we describe macrodissection, a method designed to augment the percentage tumor content of a tissue specimen by removing and eliminating unwanted tissue prior to performing downstream nucleic acid extractions. FFPE tissue blocks were sectioned to produce 4-5 &#181;m slide-mounted tissue sections. A representative section was submitted for hematoxylin and eosin (H&#38;E) staining and subsequently reviewed by a board-certified pathologist. During the review, the pathologist identified and marked the regions of tumor tissue in the H&#38;E. Once complete, the demarked H&#38;E was used to guide resection of the serial unstained sections from the same tissue block. To demonstrate the effects of macrodissection, RNA extracted from matched macrodissected and non-dissected Diffuse Large B-Cell Lymphomas (DLBCL) were run on a digital gene expression assay capable of determining DLBCL subtype and BCL2 translocation status. The results showed that macrodissection changed the subtype or BCL2 translocation status calls in 60% of the samples examined. In conclusion, macrodissection is a simple and effective method for performing tumor enrichment prior to nucleic acid extractions, the product of which can then be confidently used in downstream genomic studies.

This protocol presents a method to increase the percent tumor content of formalin-fixed paraffin-embedded tissue samples.

The presence of contaminating non-tumor tissues in formalin-fixed paraffin-embedded (FFPE) tissues can greatly undermine genomic studies. Herein we ...

Enhanced Communication of Tumor Margins Using 3D Scanning and Mapping

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