This study was approved by the Institutional Review Boards from the Authors&#39; Institutions. This protocol applies to node-positive (i.e., N&#62;1 according to the TNM staging system)14 breast cancers showing LVI and/or ENE.
1. Real time arm measurements
<ol>
	<li>Install the free downloadable application (e.g., Captevia) on a tablet computer.</li>
	<li>Take a marker of the highest-contrast color compared to the skin of the patient (e.g., white, black).
	<ol>
		<li>Mark the skin of the upper limb to be analyzed using point-landmarks at 5 cm starting from wrist to the elbow, and from elbow to proximal portion of the arm. Draw the circumferences on the skin of the upper limb to be analyzed at the level of each landmark.</li>
	</ol>
	</li>
	<li>Position the patient in an upright position in a room with sufficient space to move around her/him. Raise the patient&#39;s upper limb anteriorly by 90&#176;. Ask the patient to remain still in this position for all the scan duration. 
	NOTE: In case of difficulty of the patient to maintain this position, a support at hand level (e.g., a stick) can be used.</li>
	<li>Hook and link the 3DLS device to the tablet.</li>
	<li>Open the application from the tablet and enter the credentials of the subject to be examined within the patient database.
	<ol>
		<li>Click Connection and then + to enter a new patient. Enter the patient&#39;s Name and Surname together with other preset anamnestic variables (such as date of birth, height, weight, etc.) and others as desired in the dedicated space.</li>
	</ol>
	</li>
	<li>Click the 3D icon. Select the area to be examined by modulating the distance and size of the cube that appears on the screen using 2 fingers on the touch screen</li>
	<li>Click Scan and start the three-dimensional scan framing the upper limb of the patient on all the planes of the space. Rotate around the limb from all the views many times in order to optimize the quality of the acquired image. 
	NOTE: A good acquisition takes on average time of 30 seconds. Do not stray more than one meter from the limb to be examined. Do not move the tablet too quickly.</li>
	<li>Once the acquisition is completed, press Done. If needed, revise the form to assess any acquisition defects or missing part.</li>
	<li>Select the acquisition and press the icon at the bottom right of the screen to send the file. Enter an email to send the file to and click Send.</li>
	<li>Start the PC and download the data file sent by e-mail. Then insert the USB key with the software license, double click the software icon, confirm selected license type, and open the data file.</li>
	<li>View the scan and press Create New Patient. Name the patient&#39;s file, select the destination to save the file, and press Save.</li>
	<li>Select File in the upper left corner. Select the patient&#39;s file previously named.</li>
	<li>Select the scan and press Extract to extract the scan. Select the extracted scan and press Cleaning.</li>
	<li>Select the image. Clean the shape by orienting it in the space (x, y and z axis). Cut off any segments included in the scan on the various axes (x, y and z). It will also be possible to view any skin marks included in the scan to more precisely cut the scan. Validate the cut figure.</li>
	<li>Name the shape obtained from the scan. Press Create a new shape.</li>
	<li>Orient the shape axis on the 3 planes of the space and press End.</li>
	<li>Select the processed form and press Open: the software will provide the total volume of the processed form.</li>
	<li>Calculate the volume of different sections, press Volume. Move and select the upper and lower margin of the section from which to extract the volume.</li>
</ol>

<ol>
	<li>Michelotti, 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=Tackling+the+diversity+of+breast+cancer+related+lymphedema:+Perspectives+on+diagnosis,+risk+assessment,+and+clinical+management.">Tackling the diversity of breast cancer related lymphedema: Perspectives on diagnosis, risk assessment, and clinical management.</a> Breast. 44, 15-23 (2018).</li><li>Noguchi, M., Yokoi, M., Nakano, Y., Ohno, Y., Kosaka, T., Singh, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Axillary+reverse+mapping+in+breast+cancer.">Axillary reverse mapping in breast cancer.</a> Radioisotopes - Applications in Bio-Medical Science. , (2011).</li><li>Wilke, L. G., 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=Surgical+complications+associated+with+sentinel+lymph+node+biopsy:+results+from+a+prospective+international+cooperative+group+trial.">Surgical complications associated with sentinel lymph node biopsy: results from a prospective international cooperative group trial.</a> Annals of Surgical Oncology. 13 (4), 491-500 (2006).</li><li>Taghian, N. R., Miller, C. L., Jammallo, L. S., O'Toole, J., Skolny, M. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lymphedema+following+breast+cancer+treatment+and+impact+on+quality+of+life:+a+review.">Lymphedema following breast cancer treatment and impact on quality of life: a review.</a> Critical Reviews in Oncology/Hematology. 92 (3), 227-234 (2014).</li><li>Dean, L. T., 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=34;It+still+affects+our+economic+situation&amp;#34;:+long-term+economic+burden+of+breast+cancer+and+lymphedema.">34;It still affects our economic situation&amp;#34;: long-term economic burden of breast cancer and lymphedema.</a> Supportive Care in Cancer. , (2018).</li><li>Invernizzi, M., 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=Lymphovascular+invasion+and+extranodal+tumour+extension+are+risk+indicators+of+breast+cancer+related+lymphoedema:+an+observational+retrospective+study+with+long-term+follow-up.">Lymphovascular invasion and extranodal tumour extension are risk indicators of breast cancer related lymphoedema: an observational retrospective study with long-term follow-up.</a> BMC Cancer. 18 (1), 935 (2018).</li><li>Invernizzi, M., 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=Breast+Cancer+Systemic+Treatments+and+Upper+Limb+Lymphedema:+A+Risk-Assessment+Platform+Encompassing+Tumor-Specific+Pathological+Features+Reveals+the+Potential+Role+of+Trastuzumab.">Breast Cancer Systemic Treatments and Upper Limb Lymphedema: A Risk-Assessment Platform Encompassing Tumor-Specific Pathological Features Reveals the Potential Role of Trastuzumab.</a> Journal of Clinical Medicine. 8 (2), (2019).</li><li>Kilbreath, S. L., 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=Risk+factors+for+lymphoedema+in+women+with+breast+cancer:+A+large+prospective+cohort.">Risk factors for lymphoedema in women with breast cancer: A large prospective cohort.</a> Breast. 28, 29-36 (2016).</li><li>Sun, 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+need+for+preoperative+baseline+arm+measurement+to+accurately+quantify+breast+cancer-related+lymphedema.">The need for preoperative baseline arm measurement to accurately quantify breast cancer-related lymphedema.</a> Breast Cancer Research and Treatment. 157 (2), 229-240 (2016).</li><li>Deltombe, T., 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=Reliability+and+limits+of+agreement+of+circumferential,+water+displacement,+and+optoelectronic+volumetry+in+the+measurement+of+upper+limb+lymphedema.">Reliability and limits of agreement of circumferential, water displacement, and optoelectronic volumetry in the measurement of upper limb lymphedema.</a> Lymphology. 40 (1), 26-34 (2007).</li><li>Tewari, N., Gill, P. G., Bochner, M. A., Kollias, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+volume+displacement+versus+circumferential+arm+measurements+for+lymphoedema:+implications+for+the+SNAC+trial.">Comparison of volume displacement versus circumferential arm measurements for lymphoedema: implications for the SNAC trial.</a> ANZ Journal of Surgery. 78 (10), 889-893 (2008).</li><li>Cau, N., 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=Comparative+study+between+circumferential+method+and+laser+scanner+3D+method+for+the+evaluation+of+arm+volume+in+healthy+subjects.">Comparative study between circumferential method and laser scanner 3D method for the evaluation of arm volume in healthy subjects.</a> Journal of Vascular Surgery: Venous and Lymphatic Disorders. 4 (1), 64-72 (2016).</li><li>Hameeteman, M., Verhulst, A. C., Vreeken, R. D., Maal, T. J., Ulrich, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=3D+stereophotogrammetry+in+upper-extremity+lymphedema:+An+accurate+diagnostic+method.">3D stereophotogrammetry in upper-extremity lymphedema: An accurate diagnostic method.</a> Journal of Plastic, Reconstructive &amp; Aesthetic Surgery. 69 (2), 241-247 (2016).</li><li>Amin, M. B., 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=.">.</a> AJCC Cancer Staging Manual. , (2017).</li><li>Kamper, S. J., 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=Global+Perceived+Effect+scales+provided+reliable+assessments+of+health+transition+in+people+with+musculoskeletal+disorders,+but+ratings+are+strongly+influenced+by+current+status.">Global Perceived Effect scales provided reliable assessments of health transition in people with musculoskeletal disorders, but ratings are strongly influenced by current status.</a> Journal of Clinical Epidemiology. 63 (7), 760-766 (2010).</li></ol>

The use of an accurate and reliable tool for limb volume measurement is mandatory in breast cancer survivors, given that an early diagnosis of BCRL is related to improved outcomes. In addition, the identification of high-risk individuals should consider not only clinical and surgical data but also tumor-specific pathological features. This study demonstrates the reproducibility and reliability of a new portable 3DLS device in upper limb volume measurement both in healthy subjects and in a BCRL women with high-risk features. This method is safe, painless, cost-effective and can be carried out in most Institutions in large cohorts of patients.
The purpose of a 3D scanner is to create a point cloud of geometric shapes on the surface of the subject, which represent the 3D model. In particular, the 3DLS technology employs a triangulation mechanism projecting a laser dot into an object (in this case, the upper limb), then the sensor measures the distance to the surface of the object. This new standardized augmented reality-based protocol shows that 3DLS is a promising technique for quick volume measurement, not only in sanitary settings. Results obtained in both healthy subjects and BCRL patients are intriguing considering the relative quickness, accuracy and reproducibility of this device. One of the main critical points of this protocol is related to the 3DLS acquisition procedure which can lead to incomplete/incorrect images or errors in upper limb volumes quantification. To overcome this inconvenience, the acquisition in a room with ample free spaces is recommended, as well as to ask the patient to remain still with the upper limb anteriorly raised by 90&#176; for all the scan duration to avoid inaccuracies in the volumetric detection. Moreover, in order to obtain better volume acquisitions and to optimize the quality of the acquired image it is recommended to rotate the 3DLS around the limb from all the views many times. The acquisition should end only when the entire volumetric image of the upper limb has been acquired and the mean acquisition time is about 30 s. However, despite these potential drawbacks related to the acquisition procedure, these data about failed volume measure attempts suggest a relatively fast learning curve of 3DLS structure sensor, at least comparable to CM. Taken together all these points suggest important implications for the implementation of portable 3DLS techniques in different real-life clinical settings (i.e., outpatient or home care) and for the potential reduction of health sanitary costs in terms of both personnel and procedures costs. Therefore, structure sensor implementation in both diagnostic and therapeutic setting could have significant clinical implications for lymphedema management and rehabilitation confirming the capital role of augmented reality technologies in BCRL clinical workup, where reliable screening, diagnostic, and follow-up tools are needed to achieve the goal of precision medicine. It is important to note, however, that this protocol provide substantial improvements in the workup of BCRL only for selected groups of BCRL patients, particularly in the setting of an initial assessment. Hence, many patients with lymphedema unfortunately arrive at a treatment center with significant levels of swelling and often with comorbid conditions such as obesity. Furthermore, it must also be noted that the 3D scanning was always performed after the CM. The difference in acquisition time may reflect a learning curve. Another limitation of this study is represented by the randomization of the control group, where no matching for the age of the patients was made. On the other hand, this pilot study should be considered a proof-of-principle.
In conclusion, the paradigm-shift of using augmented reality tools in N&#62;1 breast cancer patients, coupled with a tumor-based risk stratification would represent a step toward precision medicine in BCRL clinical management.

Breast cancer related lymphedema (BCRL) is fluid retention in the upper extremity occurring after axillary surgery and/or radiation therapy in approximately 20-80% of breast cancer patients with lymph node metastases (N&#62;1)1,2,3. This condition results in swelling of the limb with subsequent reduced functionality, increased risk of comorbidities, frustration, anxiety, and depression4,5. BCRL is currently considered a long-standing threat for breast cancer survivors given that it can arise up to 9 years after surgery6.
BCRL pathogenesis is a subject of lively debate among breast cancer specialists. Hence, several studies have shown that it could be related not only to axillary interventions but also to systemic treatments, such as taxanes-based chemotherapy and anti-HER2 therapy7,8. Furthermore, there are recent lines of evidence to suggest that tumor-specific pathological characteristics are involved in its pathogenesis1,6,7. For this reason, the invasion of lymphovascular spaces at the periphery of the tumor by neoplastic cells (lymphovascular invasion, LVI) and of the extension of the metastasis beyond the lymph node capsule (extra-nodal extension, ENE) have been proposed as a complementary analysis for BCRL risk stratification6,7.
Despite the novel insights of BCRL biology, the arm volume measurement remains a cornerstone phase in the diagnosis and follow-up of these patients9. For this task, however, there are not widely-adopted guidelines. The measurement of multiple circumferences across the arm has been traditionally used to estimate its total volume using the truncated cone formula10. Despite its reliability, however, this circumferential method (CM) lack sensitivity and reproducibility, particularly in the case of arm shape irregularities11. Lately, augmented reality methods, such as three-dimensional laser scanner (3DLS), have emerged as promising tools for the measurement of the upper limb volume12. This technology is cheap, user-friendly, reproducible, and extremely precise also in the presence of gibbousness and swelling12,13.
The aim of this study was to assess the reliability of 3DLS in comparison to the circumferential method for BCRL diagnosis and quantification. Here, a protocol is detailed for real-time measurements of the upper limb volume by means of 3DLS in breast cancer patients at increased risk for BCRL.

<table><tbody><tr><td>Structure sensor + Captevia V3.1</td><td>Rodin4D, Rodin SAS</td><td></td><td>Three dimensional laser scanner</td></tr></tbody></table>

integrating augmented reality tools in breast cancer related lymphedema prognostication and diagnosis

Breast cancer related lymphedema (BCRL) is a detrimental condition characterized by fluid accumulation in the upper limb in breast cancer patients subjected to axillary surgery and/or radiations. Its etiology is multifactorial and include also tumor-specific pathological features, such as lymphovascular invasion (LVI) and extranodal extension (ENE). To date, no widely employed guidelines for the early diagnosis of BCRL are available. Here, we illustrate a protocol for a digitally assisted BCRL assessment using a 3D laser scanner (3DLS) and a tablet computer. It has been specifically optimized in a discovery cohort of high-risk breast cancer patients. This study provides a proof-of-principle that augmented reality tools, such as 3DLS, can be incorporated into the clinical workup of BCRL to allow for a precise, reproducible, reliable, and cheap diagnosis.

Watch this Scientific Journal Video about Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis at JoVE.com

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Breast cancer related lymphedema is frequent in breast cancer survivors, but there are not widely employed guidelines for its diagnosis and quantification. Here, we introduce a reliable and cost-effective protocol to define, quantify, and compare upper limb volume in breast cancer patients.

Breast cancer related lymphedema (BCRL) is a detrimental condition characterized by fluid accumulation in the upper limb in breast cancer patients ...

integrating-augmented-reality-tools-breast-cancer-related-lymphedema

Nanyang Technological University

Research

JoVE Journal

Medicine

6.5K Views.  University of Eastern Piedmont "A. Avogadro". De laser scan driedimensionale apparaat maakt een snelle en reproduceerbare meting van de bovenste ledematen volume zonder direct contact met de huid van patiënten. Bovendien is de technologie goedkoop, gebruiksvriendelijk, reproduceerbaar en uiterst nauwkeurig, zelfs in aanwezigheid van gibbousness en zwelling. Het aantonen van de procedure zal Dr. Lorenzo Lippi van onze onderzoeksgroep zijn.Begin met het installeren van een gratis downloadbare 3D-laserscantoepassing op een tabletcom...

Video: Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

Ultrasonographic Evaluation of Breast Cancer-related Lymphedema

Lymphedema is one of the most common complications after breast cancer surgery. There are many diagnostic tools for lymphedema, but no standard method yet exists. Progressive Resistance Exercise (PRE) is expected to improve lymphedema without additional swelling. This study showed the therapeutic effects of PRE on lymphedema by using ultrasonography to measure the change in thickness of the muscle and subcutaneous tissue. The thickness of subcutaneous tissue decreased more in the PRE group than in the non-PRE group. Ultrasonography is widely used in many clinics because of its easy accessibility, safety, and inexpensiveness. Ultrasound is one of the best tools for diagnosing and determining treatment efficacy on breast cancer-related lymphedema (BCRL).

This study utilized ultrasonography for diagnosis and follow-up tests to confirm treatment efficacy of Progressive Resistance Exercise (PRE) in breast cancer-related lymphedema (BCRL). Ultrasonography can be applied effectively to ensure diagnosis and treatment of lymphedema.

Lymphedema is one of the most common complications after breast cancer surgery. There are many diagnostic tools for lymphedema, but no standard method yet ...

Cancer Research

Using Computer-based Image Analysis to Improve Quantification of Lung Metastasis in the 4T1 Breast Cancer Model

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. The leading cause of breast cancer related deaths is the metastatic burden. Therefore, preclinical models for breast cancer need to analyze metastatic burden to be clinically relevant. The 4T1 breast cancer model provides a spontaneously-metastasizing, quantifiable mouse model for stage IV human breast cancer. However, most 4T1 protocols quantify the metastatic burden by manually counting stained colonies on tissue culture plates. While this is sufficient for tissues with lower metastatic burden, human error in manual counting causes inconsistent and variable results when plates are confluent and difficult to count. This method offers a computer-based solution to human counting error. Here, we evaluate the protocol using the lung, a highly metastatic tissue in the 4T1 model. Images of methylene blue-stained plates are acquired and uploaded for analysis in Fiji-ImageJ. Fiji-ImageJ then determines the percentage of the selected area of the image that is blue, representing the percentage of the plate with metastatic burden. This computer-based approach offers more consistent and expeditious results than manual counting or histopathological evaluation for highly metastatic tissues. The consistency of Fiji-ImageJ results depends on the quality of the image. Slight variations in results between images can occur, thus it is recommended that multiple images are taken and results averaged. Despite its minimal limitations, this method is an improvement to quantifying metastatic burden in the lung by offering consistent and rapid results.

We describe a more consistent and expeditious method to quantify lung metastasis in the 4T1 breast cancer model by using Fiji-ImageJ.

Breast cancer is a devastating malignancy, accounting for 40,000 female deaths and 30% of new female cancer diagnoses in the United States in 2019 alone. ...

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this study was to develop a method to predict response to intra-arterial treatment prior to intervention.
The method provides a general framework for predicting outcomes prior to intra-arterial therapy. It involves pooling clinical, demographic and imaging data across a cohort of patients and using these data to train a machine learning model. The trained model is applied to new patients in order to predict their likelihood of response to intra-arterial therapy.
The method entails the acquisition and parsing of clinical, demographic and imaging data from N patients who have already undergone trans-arterial therapies. These data are parsed into discrete features (age, sex, cirrhosis, degree of tumor enhancement, etc.) and binarized into true/false values (e.g., age over 60, male gender, tumor enhancement beyond a set threshold, etc.). Low-variance features and features with low univariate associations with the outcome are removed. Each treated patient is labeled according to whether they responded or did not respond to treatment. Each training patient is thus represented by a set of binary features and an outcome label. Machine learning models are trained using N - 1 patients with testing on the left-out patient. This process is repeated for each of the N patients. The N models are averaged to arrive at a final model.
The technique is extensible and enables inclusion of additional features in the future. It is also a generalizable process that may be applied to clinical research questions outside of interventional radiology. The main limitation is the need to derive features manually from each patient. A popular modern form of machine learning called deep learning does not suffer from this limitation, but requires larger datasets.

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. A method for predicting response to these therapies is proposed. The technique uses pre-procedural clinical, demographic, and imaging information to train machine learning models capable of predicting response prior to treatment.

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this ...

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

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

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

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

Advanced CAD Imaging for Surgical Margin Analysis in Cancer Care

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.

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.

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

Virtual Reality-3D Modeling for Minimally Invasive Neuro-Interventional Planning

Pioneering Patient-Specific Approaches for Precision Surgery Using Imaging and Virtual Reality

Endovascular treatment of complex vascular anomalies shifts the risk of open surgical procedures to the benefit of minimally invasive endovascular procedural solutions. Complex open surgical procedures used to be the only option for the treatment of a myriad of conditions like pulmonary and aortic valve replacement as well as cerebral aneurysm repair. However, due to advancements in catheter-delivered devices and operator expertise, these procedures (along with many others) can now be performed through minimally invasive procedures delivered through a central or peripheral vein or artery. The decision to shift from an open procedure to an endovascular approach is based on multi-modal imaging, often including 3D Digital Imaging and Communications in Medicine (DICOM) imaging datasets. Utilizing these 3D images, our lab generates 3D models of the pathologic anatomy, thereby allowing the pre-procedural analysis necessary to pre-plan critical components of the catheterization lab procedure, namely, C-arm positioning, 3D measurement, and idealized road-map generation. This article describes how to take segmented 3D models of patient-specific pathology and predict generalized C-arm positions, how to measure critical two-dimensional (2D) measurements of 3D structures relevant to the 2D fluoroscopy projections, and how to generate 2D fluoroscopy roadmap analogs that can assist in proper C-arm positioning during catheterization lab procedures.

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions

Advancements in endovascular treatment have replaced complex open surgical procedures with minimally invasive options, like valve replacement and aneurysm repair. This paper proposes using three-dimensional (3D) modeling and virtual reality to aid in C-arm positioning, angle measurements, and roadmap generation for neuro-interventional catheterization lab procedural planning, minimizing procedure time.

Endovascular treatment of complex vascular anomalies shifts the risk of open surgical procedures to the benefit of minimally invasive endovascular ...

Optimized 3D Reconstruction and Motion Mapping for Remote AR-Assisted Surgery

Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality

Augmented Reality (AR) is in high demand in medical applications. The aim of the paper is to provide automatic surgery using AR for the Transcatheter Aortic Valve Replacement (TAVR). TAVR is the alternate medical procedure for open-heart surgery. TAVR replaces the injured valve with the new one using a catheter. In the existing model, remote guidance is given, while the surgery is not automated based on AR. In this article, we deployed a spatially aligned camera that is connected to a motor for the automation of image capture in the surgical environment. The camera tracks the 2D high-resolution image of the patient's heart along with the catheter testbed. These captured images are uploaded using the mobile app to a remote surgeon who is a cardiology expert. This image is utilized for the 3D reconstruction from 2D image tracking. This is viewed in a HoloLens like an emulator in a laptop. The surgeon can remotely inspect the 3D reconstructed images with additional transformation features such as rotation and scaling. These transformation features are enabled through hand gestures. The surgeon's guidance is transmitted to the surgical environment to automate the process in real-time scenarios. The catheter testbed in the surgical field is controlled by the hand gesture guidance of the remote surgeon. The developed prototype model demonstrates the effectiveness of remote surgical guidance through AR.

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

This article presents the design and implementation of an automatic surgery module based on augmented reality (AR)- based 3D reconstruction. The system enables remote surgery by allowing surgeons to inspect reconstructed features and replicate surgical hand movements as if they were performing the surgery in close proximity.

Augmented Reality (AR) is in high demand in medical applications. The aim of the paper is to provide automatic surgery using AR for the Transcatheter ...

Mixed Reality Assisted Radical Endoscopic Thyroidectomy

Radical endoscopic thyroidectomy (ET) offers superior cosmetic outcomes and enhanced visibility of the surgical field compared to open surgery. However, the thyroid&#39;s unique physiological functions and intricate surrounding anatomy may result in various surgical complications. Mixed reality (MR), a real-time holographic visualization technology, enables the creation of highly realistic 3D models in the real world and facilitates multiple human-computer interactions. MR can be utilized for both preoperative evaluation and intraoperative navigation. First, semi-automatic 3D reconstruction of the neck from enhanced computed tomography images is performed using 3Dslicer. Next, the 3D model is imported into Unity3D to create a virtual hologram that can be displayed on an MR helmet-mounted display (HMD). During surgery, surgeons can wear the MR HMD to locate lesions and surrounding anatomy through the virtual hologram. In this study, patients requiring radical ET were randomly assigned to either the experimental group or the control group. Surgeons performed MR-assisted radical ET in the experimental group. A comparative analysis of surgical outcomes and the results of scales was conducted.&#160;This study successfully developed the neck 3D model and the virtual hologram. According to the NASA Task Load Index Scale, the experimental group exhibited significantly higher scores in &#39;Own Performance&#39; and lower scores in &#39;Effort&#39; compared to the control group (p = 0.002). Additionally, on the Likert Subjective Evaluation Scale, the mean scores for all questions exceeded 3. Although the incidence of surgical complications was lower in the experimental group than in the control group, the differences in surgical outcomes were not statistically significant.MR is beneficial for enhancing performance and alleviating the burden of surgeons during the perioperative period. Furthermore, MR has demonstrated the potential to enhance the safety of ET. Therefore, it is essential to further investigate the surgical applications of MR.

Radical endoscopic thyroidectomy is associated with various surgical complications. This study utilizes mixed reality techniques to assist surgeons in performing radical endoscopic thyroidectomy, aiming to enhance its safety and lower the surgical threshold.

Radical endoscopic thyroidectomy (ET) offers superior cosmetic outcomes and enhanced visibility of the surgical field compared to open surgery. However, ...

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

Lymph node status is a critical prognostic predictor for patients; however, the prognosis of colorectal signet-ring cell carcinoma (SRCC) has garnered limited attention. This study investigates the prognostic predictive capacity of the log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN staging in SRCC patients using machine learning models (Random Forest, XGBoost, and Neural Network) alongside competing risk models. Relevant data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. For the machine learning models, prognostic factors for cancer-specific survival (CSS) were identified through univariate and multivariate Cox regression analyses, followed by the application of three machine learning methods-XGBoost, RF, and NN-to ascertain the optimal lymph node staging system. In the competing risk model, univariate and multivariate competing risk analyses were employed to identify prognostic factors, and a nomogram was constructed to predict the prognosis of SRCC patients. The area under the receiver operating characteristic curve (AUC-ROC) and calibration curves were utilized to assess the model's performance. A total of 2,409 SRCC patients were included in this study. To validate the effectiveness of the model, an additional cohort of 15,122 colorectal cancer patients, excluding SRCC cases, was included for external validation. Both the machine learning models and the competing risk nomogram exhibited strong performance in predicting survival outcomes. Compared to pN staging, the LODDS staging systems demonstrated superior prognostic capability. Upon evaluation, machine learning models and competing risk models achieved excellent predictive performance characterized by good discrimination, calibration, and interpretability. Our findings may assist in informing clinical decision-making for patients.

This study evaluates prognostic systems for colorectal signet-ring cell carcinoma patients using machine learning models and competing risk analyses. It identifies log odds of positive lymph nodes as a superior predictor compared to pN staging, demonstrating strong predictive performance and aiding clinical decision-making through robust survival prediction tools.

Lymph node status is a critical prognostic predictor for patients; however, the prognosis of colorectal signet-ring cell carcinoma (SRCC) has garnered ...

Lymphedema Ultrasonography: A Technique to Measure the Change in Thickness of an Affected Tissue

Source: Jeon, Y., et al. <a href="https://www-jove-com.remotexs.ntu.edu.sg/v/54996/ultrasonographic-evaluation-of-breast-cancer-related-lymphedema">Ultrasonographic Evaluation of Breast Cancer-related Lymphedema.</a>&#160;J. Vis. Exp. (2017).
This video utilizes ultrasonography for diagnosis and follow-up tests to determine treatment efficacy of Progressive Resistance Exercise (PRE) in breast cancer-related lymphedema (BCRL). &#160;Ultrasonography can be applied effectively to ensure diagnosis and treatment of lymphedema.

Source: Jeon, Y., et al. Ultrasonographic Evaluation of Breast Cancer-related Lymphedema.&#160;J. Vis. Exp. (2017).
This video utilizes ultrasonography ...

Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis

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