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 border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<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&#160;</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&#160;</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Laptop Computer</td>
			<td>Dell XP5</td>
			<td>00355-60734-40310-AAOEM</td>
			<td>Laptop Requirements: 
			USB: 1 &#215;USB 2.0 or 3.0; OS: Win 7, 8 or 10 (64 bit); 
			Graphic Card: Nvidia series; Graphic memory: &#62;1 G; 
			CPU: Dual-core i5 or higher; Memory: &#62;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 ...

enhanced-communication-of-tumor-margins-using-3d-scanning-and-mapping

Microsoft Bing

Research

JoVE Journal

Medicine

544 Views.  Vanderbilt University Medical Center. 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. 

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

Contrast Enhanced Vessel Imaging using MicroCT

Microscopic computed tomography (microCT) offers high-resolution volumetric imaging of the anatomy of living small animals. However, the contrast between different soft tissues and body fluids is inherently poor in micro-CT images 1. Under these circumstances, visualization of blood vessels becomes a nearly impossible task. To overcome this and to improve the visualization of blood vessels exogenous contrast agents can be used. Herein, we present a methodology for visualizing the vascular network in a rodent model. By using a long-acting aqueous colloidal polydisperse iodinated blood-pool contrast agent, eXIA 160XL, we optimized image acquisition parameters and volume-rendering techniques for finding blood vessels in live animals. Our findings suggest that, to achieve a superior contrast between bone and soft tissue from vessel, multiple-frames (at least 5-8/ frames per view), and 360-720 views (for a full 360&deg; rotation) acquisitions were mandatory. We have also demonstrated the use of a two-dimensional transfer function (where voxel color and opacity was assigned in proportion to CT value and gradient magnitude), in visualizing the anatomy and highlighting the structure of interest, the blood vessel network. This promising work lays a foundation for the qualitative and quantitative assessment of anti-angiogenesis preclinical studies using transgenic or xenograft tumor-bearing mice.

Contrast enhanced small animal vessel imaging by microCT is a rapid, cost-effective and high-throughput technique for serial in situ examination for tumor development, for analyzing the network of blood vessels that nourish them, and for following the response of tumors to preclinical therapeutic intervention(s).

Microscopic computed tomography (microCT) offers high-resolution volumetric imaging of the anatomy of living small animals. However, the contrast between ...

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease. 
Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension3, or on macrodissection4. A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue5, providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ.
We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system6. Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index7.
To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of ...

Screening for Melanoma Modifiers using a Zebrafish Autochthonous Tumor Model

Genomic studies of human cancers have yielded a wealth of information about genes that are altered in tumors1,2,3. A challenge arising from these studies is that many genes are altered, and it can be difficult to distinguish genetic alterations that drove tumorigenesis from that those arose incidentally during transformation. To draw this distinction it is beneficial to have an assay that can quantitatively measure the effect of an altered gene on tumor initiation and other processes that enable tumors to persist and disseminate. Here we present a rapid means to screen large numbers of candidate melanoma modifiers in zebrafish using an autochthonous tumor model4 that encompasses steps required for melanoma initiation and maintenance. A key reagent in this assay is the miniCoopR vector, which couples a wild-type copy of the mitfa melanocyte specification factor to a Gateway recombination cassette into which candidate melanoma genes can be recombined5. The miniCoopR vector has a mitfa rescuing minigene which contains the promoter, open reading frame and 3'-untranslated region of the wild-type mitfa gene. It allows us to make constructs using full-length open reading frames of candidate melanoma modifiers. These individual clones can then be injected into single cell Tg(mitfa:BRAFV600E);p53(lf);mitfa(lf)zebrafish embryos. The miniCoopR vector gets integrated by Tol2-mediated transgenesis6 and rescues melanocytes. Because they are physically coupled to the mitfa rescuing minigene, candidate genes are expressed in rescued melanocytes, some of which will transform and develop into tumors. The effect of a candidate gene on melanoma initiation and melanoma cell properties can be measured using melanoma-free survival curves, invasion assays, antibody staining and transplantation assays.

A rapid way to screen for melanoma modifiers using a zebrafish autochthonous tumor model is presented. It takes advantage of the miniCoopR vector which allows for expression of candidate melanoma genes in melanocytes. A method to obtain melanoma-free survival curves, an invasion assay, a protocol for antibody staining of scale melanocytes and a melanoma transplantation assay are described.

Genomic studies of  human cancers have yielded a wealth of information about genes that are altered  in tumors1,2,3. A challenge arising from these ...

Patient Derived Cell Culture and Isolation of CD133+ Putative Cancer Stem Cells from Melanoma

Despite improved treatments options for melanoma available today, patients with advanced malignant melanoma still have a poor prognosis for progression-free and overall survival. Therefore, translational research needs to provide further molecular evidence to improve targeted therapies for malignant melanomas. In the past, oncogenic mechanisms related to melanoma were extensively studied in established cell lines. On the way to more personalized treatment regimens based on individual genetic profiles, we propose to use patient-derived cell lines instead of generic cell lines. Together with high quality clinical data, especially on patient follow-up, these cells will be instrumental to better understand the molecular mechanisms behind melanoma progression.
Here, we report the establishment of primary melanoma cultures from dissected fresh tumor tissue. This procedure includes mincing and dissociation of the tissue into single cells, removal of contaminations with erythrocytes and fibroblasts as well as primary culture and reliable verification of the cells' melanoma origin.
Recent reports revealed that melanomas, like the majority of tumors, harbor a small subpopulation of cancer stem cells (CSCs), which seem to exclusively fuel tumor initiation and progression towards the metastatic state. One of the key markers for CSC identification and isolation in melanoma is CD133. To isolate CD133+ CSCs from primary melanoma cultures, we have modified and optimized the Magnetic-Activated Cell Sorting (MACS) procedure from Miltenyi resulting in high sorting purity and viability of CD133+ CSCs and CD133- bulk, which can be cultivated and functionally analyzed thereafter.

Patient Derived Cell Culture and Isolation of CD133+ Putative Cancer Stem Cells from Melanoma

This article describes the preparation of freshly obtained melanoma tissue into primary cell cultures, and how to remove contaminations of erythrocytes and fibroblasts from the tumor cells. Finally, we describe how CD133+ putative melanoma stem cells are sorted from the CD133- bulk using Magnetic Activated Cell Sorting (MACS).

Despite improved treatments options for melanoma available today, patients with advanced malignant melanoma still have a poor prognosis for ...

In vivo Imaging of Tumor Angiogenesis using Fluorescence Confocal Videomicroscopy

Fibered confocal fluorescence in vivo imaging with a fiber optic bundle uses the same principle as fluorescent confocal microscopy. It can excite fluorescent in situ elements through the optical fibers, and then record some of the emitted photons, via the same optical fibers. The light source is a laser that sends the exciting light through an element within the fiber bundle and as it scans over the sample, recreates an image pixel by pixel. As this scan is very fast, by combining it with dedicated image processing software, images in real time with a frequency of 12 frames/sec can be obtained.
We developed a technique to quantitatively characterize capillary morphology and function, using a confocal fluorescence videomicroscopy device. The first step in our experiment was to record 5 sec movies in the four quadrants of the tumor to visualize the capillary network. All movies were processed using software (ImageCell, Mauna Kea Technology, Paris France) that performs an automated segmentation of vessels around a chosen diameter (10 &mu;m in our case). Thus, we could quantify the 'functional capillary density', which is the ratio between the total vessel area and the total area of the image. This parameter was a surrogate marker for microvascular density, usually measured using pathology tools.
The second step was to record movies of the tumor over 20 min to quantify leakage of the macromolecular contrast agent through the capillary wall into the interstitium. By measuring the ratio of signal intensity in the interstitium over that in the vessels, an 'index leakage' was obtained, acting as a surrogate marker for capillary permeability.

In vivo Imaging of Tumor Angiogenesis using Fluorescence Confocal Videomicroscopy

In this paper, we present a method to analyze tumor microvessels in vivo using dynamic contrast-enhanced fluorescence videomicroscopy. Two quantitative parameters were acquired: functional capillary density reflecting the vascularity of the tumor, and index leakage reflecting the leakiness of the endothelial wall.

Fibered confocal fluorescence in vivo imaging with a fiber optic bundle uses the same principle as fluorescent confocal microscopy. It can excite ...

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a novel platform that allows for direct long-term visualization of tissue structure changes intracranially. Imaging at a single cell resolution in a real-time fashion provides supplementary dynamic information beyond that provided by standard end-point histological analysis, which looks solely at 'snap-shot' cross sections of tissue.
Establishing this intravital imaging technique in fluorescent chimeric mice, we are able to image four fluorescent channels simultaneously. By incorporating fluorescently labeled cells, such as GFP+ bone marrow, it is possible to track the fate of these cells studying their long-term migration, integration and differentiation within tissue. Further integration of a secondary reporter cell, such as an mCherry glioma tumor line, allows for characterization of cell:cell interactions. Structural changes in the tissue microenvironment can be highlighted through the addition of intra-vital dyes and antibodies, for example CD31 tagged antibodies and Dextran molecules.
Moreover, we describe the combination of our ICW imaging model with a small animal micro-irradiator that provides stereotactic irradiation, creating a platform through which the dynamic tissue changes that occur following the administration of ionizing irradiation can be assessed.
Current limitations of our model include penetrance of the microscope, which is limited to a depth of up to 900 &mu;m from the sub cortical surface, limiting imaging to the dorsal axis of the brain. The presence of the skull bone makes the ICW a more challenging technical procedure, compared to the more established and utilized chamber models currently used to study mammary tissue and fat pads 5-7. In addition, the ICW provides many challenges when optimizing the imaging.

A Novel High-resolution In vivo Imaging Technique to Study the Dynamic Response of Intracranial Structures to Tumor Growth and Therapeutics

We describe a novel in vivo imaging technique that couples fluorescent chimeric mice with intracranial windows and high-resolution 2-photon microscopy. This imaging platform aids studies of dynamic changes in brain tissue and microvasculature, at a single-cell level, following pathological insults and is adaptable to assess intracranial drug delivery and distribution.

We have successfully integrated previously established Intracranial window (ICW) technology 1-4 with intravital 2-photon confocal microscopy to develop a ...

Quantification of Breast Cancer Cell Invasiveness Using a Three-dimensional (3D) Model

It is now well known that the cellular and tissue microenvironment are critical regulators influencing tumor initiation and progression. Moreover, the extracellular matrix (ECM) has been demonstrated to be a critical regulator of cell behavior in culture and homeostasis in vivo. The current approach of culturing cells on two-dimensional (2D), plastic surfaces results in the disturbance and loss of complex interactions between cells and their microenvironment. Through the use of three-dimensional (3D) culture assays, the conditions for cell-microenvironment interaction are established resembling the in vivo microenvironment. This article provides a detailed methodology to grow breast cancer cells in a 3D basement membrane protein matrix, exemplifying the potential of 3D culture in the assessment of cell invasion into the surrounding environment. In addition, we discuss how these 3D assays have the potential to examine the loss of signaling molecules that regulate epithelial morphology by immunostaining procedures. These studies aid to identify important mechanistic details into the processes regulating invasion, required for the spread of breast cancer.

Quantification of Breast Cancer Cell Invasiveness Using a Three-dimensional 3D Model

This article provides detailed methodologies for the use of three-dimensional (3D) assays to quantify breast cancer cell invasion. Specifically, we discuss the procedures required to set up such assays, quantification, and data analysis, as well as methods to examine the loss of membrane integrity that occurs when cells invade.

It is now well known that the cellular and tissue microenvironment are critical regulators influencing tumor initiation and progression. Moreover, the ...

Coordinate Mapping of Hyolaryngeal Mechanics in Swallowing

Characterizing hyolaryngeal movement is important to dysphagia research. Prior methods require multiple measurements to obtain one kinematic measurement whereas coordinate mapping of hyolaryngeal mechanics using Modified Barium Swallow (MBS) uses one set of coordinates to calculate multiple variables of interest. For demonstration purposes, ten kinematic measurements were generated from one set of coordinates to determine differences in swallowing two different bolus types. Calculations of hyoid excursion against the vertebrae and mandible are correlated to determine the importance of axes of reference.
To demonstrate coordinate mapping methodology, 40 MBS studies were randomly selected from a dataset of healthy normal subjects with no known swallowing impairment. A 5 ml thin-liquid bolus and a 5 ml pudding swallows were measured from each subject. Nine coordinates, mapping the cranial base, mandible, vertebrae and elements of the hyolaryngeal complex, were recorded at the frames of minimum and maximum hyolaryngeal excursion. Coordinates were mathematically converted into ten variables of hyolaryngeal mechanics.
Inter-rater reliability was evaluated by Intraclass correlation coefficients (ICC). Two-tailed t-tests were used to evaluate differences in kinematics by bolus viscosity. Hyoid excursion measurements against different axes of reference were correlated. Inter-rater reliability among six raters for the 18 coordinates ranged from ICC = 0.90 - 0.97. A slate of ten kinematic measurements was compared by subject between the six raters. One outlier was rejected, and the mean of the remaining reliability scores was ICC = 0.91, 0.84 - 0.96, 95% CI. Two-tailed t-tests with Bonferroni corrections comparing ten kinematic variables (5 ml thin-liquid vs. 5 ml pudding swallows) showed statistically significant differences in hyoid excursion, superior laryngeal movement, and pharyngeal shortening (p &#60; 0.005). Pearson correlations of hyoid excursion measurements from two different axes of reference were: r = 0.62, r2 = 0.38, (thin-liquid); r = 0.52, r2 = 0.27, (pudding).
Obtaining landmark coordinates is a reliable method to generate multiple kinematic variables from video fluoroscopic images useful in dysphagia research.

Coordinate mapping is a method of documenting salient features of hyolaryngeal biomechanics in the pharyngeal phase of swallowing. This methodology uses image analysis software to record coordinates of anatomical landmarks. These coordinates are imported into an excel macro and translated into kinematic variables of interest useful in dysphagia research.

Characterizing hyolaryngeal movement is important to dysphagia research. Prior methods require multiple measurements to obtain one kinematic measurement ...

Three-Dimensional (3D) Tumor Spheroid Invasion Assay

Invasion of surrounding normal tissues is generally considered to be a key hallmark of malignant (as opposed to benign) tumors. For some cancers in particular (e.g., brain tumors such as glioblastoma multiforme and squamous cell carcinoma of the head and neck &#8211; SCCHN) it is a cause of severe morbidity and can be life-threatening even in the absence of distant metastases. In addition, cancers which have relapsed following treatment unfortunately often present with a more aggressive phenotype. Therefore, there is an opportunity to target the process of invasion to provide novel therapies that could be complementary to standard anti-proliferative agents. Until now, this strategy has been hampered by the lack of robust, reproducible assays suitable for a detailed analysis of invasion and for drug screening. Here we provide a simple micro-plate method (based on uniform, self-assembling 3D tumor spheroids) which has great potential for such studies. We exemplify the assay platform using a human glioblastoma cell line and also an SCCHN model where the development of resistance against targeted epidermal growth factor receptor (EGFR) inhibitors is associated with enhanced matrix-invasive potential. We also provide two alternative methods of semi-automated quantification: one using an imaging cytometer and a second which simply requires standard microscopy and image capture with digital image analysis.

Three-Dimensional 3D Tumor Spheroid Invasion Assay

Invasion of surrounding normal tissues is a defining characteristic of malignant tumors. We provide here a simple, semi-automated micro-plate assay of invasion into a natural 3D biomatrix that has been exemplified with a number of models of advanced human cancers.

Invasion of surrounding normal tissues is generally considered to be a key hallmark of malignant (as opposed to benign) tumors. For some cancers in ...

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Cardiovascular diseases (CVDs) are the leading cause of death throughout the world. The total risk of developing CVD is determined by the combined effect of different cardiovascular risk factors (e.g., diabetes, raised blood pressure, unhealthy diet, tobacco use, stress, etc.) that commonly coexist and act multiplicatively. Most CVDs can be prevented by an early identification of the highest risk factors and an appropriate treatment. The stratification of cardiovascular risk factors involves a wide range of parameters and tests that specialists use in their clinical practice. In addition to cardiovascular (CV) risk stratification, ambulatory blood pressure monitoring (ABPM) also provides relevant information for diagnostic and treatment purposes. This work presents a list of protocols based on the Hydra platform, a web-based system for clinical decision support which incorporates a set of functionalities and services that are required for complete cardiovascular analysis, risk assessment, early diagnosis, treatment and monitoring of patients over time. The program includes tools for inputting and managing comprehensive patient data, organized into different checkups to track the evolution over time. It also has a risk stratification tool to compute a CV risk factor based upon several risk stratification tables of reference. Additionally, the program includes a tool that incorporates ABPM analysis and allows the extraction of valuable information by monitoring blood pressure over a specific period of time. Finally, the reporting service summarizes the most relevant information in a set of reports that aid clinicians in their clinical decision-making process.

This article presents a protocol based on Hydra &#8212; a web-based system for clinical decision support that integrates a full and detailed set of functionalities and services required by physicians for complete cardiovascular analysis, risk assessment, early diagnosis, treatment, and monitoring over time.

Cardiovascular diseases (CVDs) are the leading cause of death throughout the world. The total risk of developing CVD is determined by the combined effect ...