Development of a virtual 3D renal corpuscle for educational environments

Understanding normal structural and functional anatomy is critical for health professionals across various fields such as medicine, veterinary, and dental courses. The landscape of anatomical education has evolved tremendously due to several challenges and advancements in blended learning approaches, which have led to the adoption of the use of high‐fidelity 3D digital models in anatomical education. Cost‐effective methods such as photogrammetry, which creates digital 3D models from aligning 2D photographs, provide a viable alternative to expensive imaging techniques (i.e. computed tomography and magnetic resonance imaging) whilst maintaining photorealism and serving multiple purposes, including surgical planning and research. This study outlines a comprehensive workflow for producing realistic 3D digital models from embalmed veterinary specimens. The process begins with the preservation of specimens using the modified‐WhitWell (WhitWell‐Liverpool) embalming protocol, which ensures optimal tissue rigidity and improved colour enhancement, facilitating easier manipulation and better photogrammetry outcomes. Once embalmed, specimens are photographed to create digital 3D models using photogrammetry. Briefly, all images are processed to generate a sparse point cloud, which is then rendered into a 3D mesh. The mesh undergoes decimation and smoothing to reduce computational load, and a texture is applied to create a lifelike model. Additional colour enhancements and adjustments are made using digital tools to restore the natural appearance of the specimens. The 3D models are stored on a cloud repository and integrated into the University of Liverpool's Virtual Learning Environment, providing continuous, remote access to high‐quality anatomical resources. The switch to embalmed specimens during the COVID‐19 pandemic allowed for longer‐term use and detailed dissections, enhancing the quality of digital models. Fresh specimens, though naturally coloured, are less stable for photogrammetry, making embalmed specimens preferable for accurate 3D modelling. Our method ensures embalmed specimens are rigid enough for precise modelling while allowing texture adjustments to enhance digital representation. This approach has improved logistical efficiency, educational delivery, and specimen quality. Innovative embalming techniques and advanced photogrammetry have the power to revolutionise anatomical education with the creation of a vast digital library accessible online to students at any time. This approach paves the way for integrating digital 3D models into immersive environments and assessing their impact on learning outcomes.

3D-Printed specimens as a valuable tool in anatomy education: A pilot study

Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Japan Organization of Occupational Health and Safety onbehalf J3D Introduction Improvements in cardiovascular imaging have contributed to the accurate diagnosis and treatment of cardiovascular diseases. In recent years, we can find a new demand from surgical departments, i.e., 3D heart models of patients for preoperative simulations. However, a 3D surgical model needs a detailed segmentation of heart structures from clinical images because these details are essential for achieving accurate polygon data of an exact 3D model. Thus, in most cases, manual segmentation is required for complicated heart shapes such as the chamber wall, valves, and papillary muscles, which causes a prolonged duration time. Purpose We aim to achieve an automated heart segmentation using a convolutional neural network (CNN) trained using deep learning techniques for the rapid creation of 3D surgical heart models of individual patients. Methods We constructed our original CNN program based on the latest artificial intelligence techniques and trained it to extract shapes of the heart from cardiac computed tomography (CT) images. The training data was 361 slices selected from CT scans of 10 patients. We used data augmentation to increase the amount and diversity of the data into 24,052 slices. The training result with the best Intersection over Union (IoU), one of the evaluation metrics used in deep learning, was saved. Finally, we used the best-trained CNN to construct 3D polygon data of two surgical cases of hypertrophic obstructive cardiomyopathy (HOCM) for preoperative assessments. Results The IoU attained 0.85 after deep learning. The time required to complete the 3D polygon data for the first HOCM case was 5 minutes for segmentation by the trained CNN and 3 hours for data correction by a human operator. Similarly, the time required for the second case was 5 minutes for segmentation without manual correction. We had to correct the segmentation for the first case because we needed an exact 3D model for the preoperative assessment (Fig. 1). According to our records of the other eight 3D heart models in the lab, the work for a 3D polygon shape from CT images needs a median 30 hours (quartiles 23-50 hours) when the procedure is fully manual and non-continuous with breaks in between. Conclusion The CNN-based segmentation aided the constructing heart shapes from cardiac CT images of preoperative patients. Although the performance, reaching IoU of 0.85, was insufficient for fully automatic segmentation, the methodology can shorten the process duration from several hours to several minutes for detailed segmentation of heart structures. We previously applied the CNN-based segmentation to the aorta, aortic stenosis valves, and atheromatous plaque in clinical images, demonstrating adequate segmentation performance. The proposed methodology can be applied as a fundamental technology of cardiovascular imaging for obtaining the actual structures of a target object as 3D coordinate values or a 3D model within a reasonable duration time. Abstract Figure 1

3D-technologies are a promising direction in the development of medicine. Numerous publications in recent years demonstrate the potential use of 3D-modeling in disease diagnosis, surgical planning, intraoperative navigation, development of individual implants, and specialist training. In this article, we present the experience of implementing 3D-technologies in the practice of a pediatric surgeon using three clinical cases where the use of 3D models based on computed tomography data allowed for more accurate diagnosis and surgical planning. The first patient was a 3-year-old boy with vascular compression of the left main bronchus and impaired ventilation of the left lung. After 3D-visualization of the area of interest, an arterial ligament causing the compression was visualized as the main cause. The second patient was a 6-month-old boy with confirmed bilateral chondromesenchymal hamartoma of the chest wall. The volume and staging of the surgical treatment, as well as the most suitable option for defect replacement, were developed after creating a polymer 3D-model of the child’s chest. The third patient was a 17-year-old girl with persistent hypercalcemia after removal of a parathyroid adenoma. A repeat computed tomography revealed an ectopic parathyroid tissue. The use of 3D-models and AR-technology for intraoperative navigation allowed for precise determination of the location of the pathological tissue. These clinical cases demonstrate the potential and effectiveness of using 3D-modeling in pediatric surgery and confirm that this is a promising direction in the development of medicine, opening up new possibilities for clinicians.

An approach to 3D model fusion in GIS systems and its application in a future ECDIS

When educating dental students or prosthodontic residents, a picture can be worth a thousand words. If that is so, then what could enhanced 3D modeling be worth relative to enhancing student learning? The answer is undoubtedly more than what a picture can provide. That is why the use of 3D models has become increasingly common with respect to patient care. The 3D modeling allows the patient to visualize more clearly the proposed treatments and outcomes; however, while 3D modeling has started to make an appearance in dental education, many of the current 3D modeling techniques do not offer the flexibility needed for dental education and enhanced student learning. At the University of Iowa, the use of 3D modeling software has enabled the creation of 3D models that can be altered or customized to be used in a more flexible way to teach students in the arts and complexities of removable partial denture (RPD) design and associated components. This educational technique article will: (1) demonstrate how these 3D models can be used to enhance student perception and learning regarding RPDs; and (2) will demonstrate using videos and web-based portals to show how the 3D RPD models were created and then used for educational purposes.

Insects are the most diverse group of living organisms on Earth, but their small size and structural complexity make species identification a challenging task, especially for those with less experience in entomology. Accurate identification is essential for pest management decisions in agriculture. Traditional 2D resources, such as field guides and taxonomic keys, may exhibit limitations when depicting complex insect structures, as exemplified by the intricate morphology of insect mouthparts. This study explores the use of 3D models to enhance the learning experience in insect identification and morphology education. We developed an online course that incorporated interactive digital 3D models alongside instructional videos and assessments. Participants (N = 102), primarily undergraduate students in natural sciences, completed pre- and posttests to assess knowledge gains. Additionally, they completed a survey designed to evaluate learning satisfaction, self-efficacy, limitations of the learning tools, and to collect open-ended written feedback. A paired samples t-test revealed a significant increase in posttest scores compared to pretest scores (t = −17.71, P < 0.001). Most participants rated learning satisfaction and self-efficacy above 9 on a 0 to 10-point Likert scale survey. Participants highlighted the effectiveness of 3D models in species differentiation and morphological understanding. Feedback suggested potential improvements, including expanded insect coverage and interactive comparison tools. This study demonstrates that 3D models can significantly enhance insect morphology education, providing an engaging and effective learning tool for students and pest management professionals.

This paper considers the use of 3d modeling to quantify the growth of pot holes. These are a common problem around the world and cause problems with the road user and those involved with its maintenance. Assessing the size of a pothole, or being able to understand their growth has not really been considered in the literature. 3D modeling techniques based on stereo photogrammetry were used to quantify 2d and 3d parameters of potholes. The experiment was carried out the laboratory. Roller compacted slabs were prepared and an artificial pothole created on its surface. This was photographed and a 3D model created. The artificial pothole was enlarged and the process repeated. At each stage the actual diameter, circumference and volume of the hole was determined. The 3D models were analyzed using DigitalSurf MountainsMap software. Good correlation was found between parameters from the 3d model and those measured. It is proposed that this method gives a simple and robust method to better understand potholes.

Three-dimensional (3D) modeling is increasingly used in hepatobiliary surgery to enhance anatomical understanding and operative planning. However, its impact on oncologic outcomes remains uncertain. This study evaluated whether preoperative 3D liver models influence resection margin status and survival after hepatectomy for malignant disease. In this retrospective case-control study, 59 patients undergoing hepatic resection for malignancy between May 2018 and May 2023 were included. Patients were managed either with patient-specific 3D models (n = 31) or conventional imaging (n = 28). Predictors of R0 resection were analyzed using logistic regression, and overall survival (OS) and disease-free survival (DFS) were assessed using Cox proportional hazards models. R0 resection was achieved in 79.7% of patients, with no significant difference between groups (77.4% vs. 82.1%; p = 0.865). Bilobar tumor distributionadjusted odds ratio [OR] 0.05, 95% confidence interval [CI] 0.00-0.76; p = 0.039) and a higher albumin-bilirubin score (adjusted OR 0.06, 95% CI 0.00-0.46; p = 0.029) were independently associated with lower odds of achieving R0 resection. In multivariable analysis, the use of 3D models was independently linked to improved 2-year DFS (adjusted hazard ratio 0.47, 95% CI 0.24-0.92; p = 0.028). Tumor type affected recurrence rates, with hepatocellular carcinoma and other tumors showing a lower risk of recurrence compared to colorectal liver metastases. No significant differences in OS were found. Preoperative 3D modeling was not associated with higher R0 resection rates but was independently associated with improved 2-year DFS. Given the retrospective design and potential residual confounding, these findings should be interpreted cautiously and considered hypothesis-generating pending prospective validation.

The Management of Cultural Heritage (MCH) is a very complex operation aimed at protecting the physical integrity of CH assets, while promoting their historical value and development of tourism industry. In recent years, the use of digital technologies has become an essential part of the MCH delicate process, but the use of 3D models is still limited to few academic research to date. Furthermore, very few supra-national standard guidelines regulating their use are available to date and the operator who decides to use a 3D model as a basis for management is faced with the scarcity and fragmentation of standards and guidelines.
\nThe aim of the PhD research is to develop guidelines to produce 3D models for MCH, with the purpose to efficiently entry, store and manage digital data. The here provided guidelines investigate every aspect of the process leading from data acquisition to cataloguing and archiving, processing and creation of a simplified information system for the management. In order to elaborate guidelines that could be suitable for as many typologies of CH as possible an international approach was chosen, developing the thesis in joint supervision under the University of Bologna and the Universitat Politècnica de València, and by applying the state-of-the-art technologies of acquisition, processing and use of 3D models to a variety of case studies.
\nThe investigation, by highlighting the problems inherent to the MCH, made it possible to identify the main open issues that need to be explored in future lines of research, such as the application of standards to a large number of cultural assets; the automatic classification of raw data; the processing of collected data for the creation of relations, strategies and methods for the classification, integration and optimisation of heterogeneous data.

<p>This article studies and analyzes the use of 3D models, built from magnetic resonance imaging (MRI) axial scans of the lumbar intervertebral disk, that are needed for the diagnosis of disk herniation. We study the possibility of assisting radiologists and orthopedists and increasing their quality of experience (QoE) during the diagnosis process. The main aim is to build a 3D model for the desired area of interest and ask the specialists to consider the 3D models in the diagnosis process instead of considering multiple axial MRI scans. We further propose an automated framework to diagnose the lumber disk herniation using the constructed 3D models. We evaluate the effectiveness of increasing the specialists QoE by conducting a questionnaire on 14 specialists with different experiences ranging from residents to consultants. We then evaluate the effectiveness of the automated diagnosis framework by training it with a set of 83 cases and then testing it on an unseen test set. The results show that the the use of 3D models increases doctors QoE and the automated framework gets 90% of diagnosis accuracy.</p>

IntroductionFor medical and allied health students, knowledge of anatomical variation is important as it may influence physical examination, diagnosis and treatment of patients. Recent studies indicate anatomical variation should be conceptually integrated early into the anatomy curriculum prior to the discipline specific variations taught in surgical and radiological postgraduate training programs. For academic institutions with limited access to cadaveric dissection and anatomy museums, the opportunity for students to appreciate the range of normality in anatomical structures is diminished. Thus, the purpose of this study was to demonstrate how 3D models of anatomical variations may be used to assess structure, function and spatial relationships by incorporating the concept of anatomical variations into assessment paradigms.MethodsTwo 3D digital models depicting upper limb muscular variations, and a 3D teratological model were evaluated by undergraduate kinesiology (KIN) (n = 30), and graduate clinical anatomy (CA) (n = 10) students. The study protocol consisted of the following instruments introduced in sequence: (1) 30‐question Spatial Ability Test (SAT), (2) 16‐question baseline upper limb anatomy test, (3) 13‐question multiple choice quiz based on the displayed 3D models, and (4) Student perception survey (5‐point Likert scale). Based on SAT scores, a median split was used stratify the students into high (KIN: 15, CA: 5) and low spatial ability (KIN: 15, CA: 5). All data are presented as Mean ± SD.ResultsBoth student groups scored similarly on the baseline anatomy knowledge test (KIN: 71 ± 17 %, CA: 71 ± 12%). The mean 3D model quiz scores for KIN students of high spatial ability were 72 ± 16% compared to those of lower spatial ability, 68 ± 14%. The 3D model quiz scores for CA students of high spatial ability were 88 ± 12% compared to CA students of lower spatial ability, 77 ± 15%. The models were perceived as useful in assessing spatial relationships (KIN: 4.4 ± 0.8, CA: 4.9 ± 0.3) and clinical concepts (KIN: 4.0 ± 0.9 CA: 3.9 ± 0.3). Student perceptions were positive for integrating the 3D models into lecture, or laboratory discussions, but KIN students were relatively neutral (3.2 ± 1.2) compared to CA students (3.9 ± 0.3) in their integrated use in bell‐ringer style laboratory assessments. The students expressed interest for a database of explorable 3D models of anatomical variations.ConclusionIntegration of the 3D variant models into anatomy curricula could be a useful means in assessing fundamental anatomical concepts, while demonstrating how deviations in structure can affect normal function. For institutions with computer access but limited cadaveric resources, the 3D models could be powerful supplementary teaching and assessment tools for anatomy students of all education levels and spatial abilities. Furthermore, development of a database of explorable anatomical variations for teaching and learning purposes would be valuable for allied health and medical programs in search of integrating variant anatomy into their anatomy curricula.Support or Funding InformationSupported by: American Association of Anatomists (AAA) Education Research Scholarship; Natural Sciences and Engineering Research Council of Canada (NSERC)This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Cardiovascular disease resulting from atypical cardiac structures continues to be a leading health concern despite advancements in diagnostic imaging and surgical techniques. However, the ability to visualize spatial relationships using current technologies remains a challenge. Therefore, 3D modeling has gained significant interest to understand complex and atypical cardiovascular disorders. Moreover, 3D modeling can be personalized and patient-specific. 3D models have been demonstrated to aid surgical planning and simulation, enhance communication among surgeons and patients, optimize medical device design, and can be used as a potential teaching tool in medical schools. In this review, we discuss the key components needed to generate cardiac 3D models. We highlight prevalent structural conditions that have utilized 3D modeling in pre-operative planning. Furthermore, we discuss the current limitations of routine use of 3D models in the clinic as well as future directions for utilization of this technology in the cardiovascular field.

Recent years have witnessed an increasing use of 3D models in general and 3D geometric models specifically of built environment for various applications, owing to the advancement of mapping techniques for accurate 3D information. Depending on the application scenarios, there exist various types of approaches to automate the construction of 3D building geometry. However, in those studies, less attention has been paid to watertight geometries derived from point cloud data, which are of use to the management and the simulations of building energy. To this end, an efficient reconstruction approach was introduced in this study and involves the following key steps. The point cloud data are first voxelised for the ray-casting analysis to obtain the 3D indoor space. By projecting it onto a horizontal plane, an image representing the indoor area is obtained and is used for the room segmentation. The 2D boundary of each room candidate is extracted using new grammar rules and is extruded using the room height to generate 3D models of individual room candidates. The room connection analyses are applied to the individual models obtained to determine the locations of doors and the topological relations between adjacent room candidates for forming an integrated and watertight geometric model. The approach proposed was tested using the point cloud data representing six building sites of distinct spatial confirmations of rooms, corridors and openings. The experimental results showed that accurate watertight building geometries were successfully created. The average differences between the point cloud data and the geometric models obtained were found to range from 12 to 21 mm. The maximum computation time taken was less than 5 min for the point cloud of approximately 469 million data points, more efficient than the typical reconstruction methods in the literature.

In this paper we focus our discussion on thermal plasmas created by electric arc. Due to the electrons mobility, the energy transferred by Joule effect to the gas, leads to temperature around 10 000 K. Thermal plasmas are very used in numerous processes like spraying, cutting, welding, waste treatment and are also present in numerous situations such as in interruption systems: high and low voltage circuit breakers or in natural phenomena: lightning strike. In order to be improved, thermal plasma processes necessitate a better understanding of the medium. Numerical modeling is now largely used to analyze and to predict the behavior of arcs and hydrodynamic flows to improve thermal plasma processes. Due to the increase of computer performances and to the availability of commercial computational fluid dynamics codes, the 2D modeling mainly developed in the 80’s and 90’s have been progressively replaced for a few years by 3D models. But is there always a real interest to develop such kind of codes if we consider the increase of accuracy in comparison with the increase of CPU time and the level of the assumptions? In order to give some elements for the discussion, we compare in the first part two physical conditions: one based on the flow injection and the other on the arc attachment, using 2D and 3D models. The legitimacy of the 2D model in then studied. In the second part, we illustrate through example the necessity of the use of 3D models due to complexities in configurations. Finally the difficulty of the 3D models validation is underlined.