BACKGROUND: 3D printing is increasingly utilized in medical education, providing a hands-on approach to anatomical learning, surgical planning, and interdisciplinary collaboration. Despite growing interest, standardized curricula incorporating 3D printing into medical education are lacking. METHODS: A multidisciplinary team of medical educators, engineers, and students developed three distinct curricular models to integrate 3D printing into undergraduate medical education. These models include (1) integration into anatomy coursework, (2) a fourth-year clerkship elective, and (3) a pre-clerkship elective. The outline for each curriculum was designed to be adaptable across institutions, emphasizing hands-on learning, imaging segmentation, basic elements of computer-aided design (CAD), and 3D printing applications in clinical care. RESULTS: The proposed curricula outlined provide structured pathways for incorporating 3D printing into medical education, enhancing student engagement and comprehension of complex anatomical structures. By integrating 3D printing into anatomy courses, clerkships, and elective rotations, students gain critical skills applicable to future clinical practice. The curricular models vary in scope and resource requirements, offering flexibility for adoption across medical schools. CONCLUSIONS: Standardizing 3D printing curricula in medical education enhances anatomical understanding, promote interdisciplinary collaboration, and prepare students for future applications of this technology in clinical practice. Our framework serves as a guide for institutions seeking to implement 3D printing curricula, fostering innovation and hands-on learning opportunities for medical trainees. TRIAL REGISTRATION: Not applicable. CLINICAL TRIAL NUMBER: Not applicable.
BACKGROUND AND OBJECTIVE: In medical education, the BOPPPS (Bridge-In, Objective, Preassessment, Participatory Learning, Post assessment, Summary) teaching model has gained traction for fostering student-centered learning, yet its efficacy in orthopedic education, particularly when integrated with 3D printing technology, remains understudied. This study aimed to evaluate the impact of combining the BOPPPS model with 3D printing on learning outcomes, student satisfaction, and clinical skill development in mainland China’s orthopedic curriculum. METHODS: A single-center, prospective observational study was conducted with 68 fifth-year clinical medical students at Tongji Medical College, randomized into a control group (n = 34, traditional lecture-based teaching) and an intervention group (n = 34, BOPPPS model + 3D printing). The intervention incorporated patient-specific 3D-printed pelvic fracture models into BOPPPS-structured sessions, focusing on participatory learning activities like fracture classification and surgical planning. Primary outcomes included theoretical knowledge (100-point exam), clinical practice ability (100-point skills assessment), self-ability evaluation (15-item questionnaire), student satisfaction (15-item Likert-scale survey), and learning quality indicators (input, process, outcome evaluations). RESULTS: The intervention group outperformed the control group in all primary outcomes. Theoretical knowledge scores were significantly higher in the intervention group (83.28 ± 10.74 vs. 68.94 ± 11.08, p < 0.001), as were clinical practice ability scores (82.64 ± 8.67 vs. 69.36 ± 10.93, p = 0.008). Self-ability evaluations showed a 18-percentage-point increase in “excellent” ratings (41.18% vs. 23.53%, p = 0.008), and teaching satisfaction was notably higher (97.06% vs. 76.47%, p = 0.012). Learning quality indicators—input (26.24 ± 3.58 vs. 12.46 ± 2.11), process (25.88 ± 3.37 vs. 12.34 ± 2.53), and outcome (25.34 ± 3.32 vs. 13.10 ± 2.27) all favored the intervention group (p < 0.001 for all). CONCLUSION: Integrating the BOPPPS teaching model with 3D printing technology enhances theoretical knowledge, clinical skills, self-perceived competence, and student satisfaction in orthopedic education. This hybrid approach addresses the spatial and practical challenges of orthopedic training, offering a scalable, effective framework for modern medical curricula.
Technological advancements have made 3D printing more accessible and affordable for both individuals and institutions. Despite significant efforts by the International Medical Device Regulators Forum to standardize 3D printing regulations for medical use, challenges remain. We conducted a survey to gather insights from physician end-users on their opinions regarding the regulation of 3D printing in medicine. Additionally, since FDA guidance is often adopted internationally, this survey aimed to capture the demographics of physician end-users globally and provide a snapshot of the current use of 3D printing in clinical practice and research. After developing and validating a 26-question survey, we emailed it to the corresponding authors of all PubMed-indexed publications on 3D printing in medicine. Participants received an introductory email explaining the survey's purpose and an invitation to participate. Only responses from participants who declared themselves to be physicians were accepted. The survey was open for responses from April 5th to May 3rd, 2022, with weekly reminders sent until the response period closed. Responses with at least 80% survey completion were accepted for analysis. Out of 951 surveys sent, we received 114 responses (11.9%) with an average completion rate of 89%. Most respondents were from Europe (35.5%) and North America (30.9%), followed by Australia and New Zealand (9.1%). The majority were affiliated with academic institutions (83.9%) and were primarily surgeons (49.1%). The most common application of 3D printing was surgical planning (74.1%), followed by medical education (61.6%). Nearly 50% of respondents used open-source segmentation software without FDA approval. Most had access to an onsite printer (82.2%) and specially trained staff to assist with segmentation (53.4%). The integration of 3D printing technologies into clinical practice will continue to grow. This paper presents the largest survey of physicians practicing 3D printing to date. Given the underrepresentation of this key demographic within regulatory bodies, the opinions and positions of physician respondents reported here should be considered in the development and application of new guidelines and regulations in the field.
Three-Dimensional (3D) printing, also known as additive manufacturing (Linke, Additive manufacturing, explained, 2017), has rapidly emerged as a transformative tool in healthcare simulation. This scoping review investigates simulation educators' knowledge, skills, and attitudes (KSAs) about the impact of 3D printing and explores 3D printing's broader applications in healthcare simulation. By synthesizing existing literature, this study aims to identify trends, challenges, and opportunities for integrating 3D printing into simulation-based education. The review followed the PRISMA-ScR framework, employing a six-step approach. A comprehensive search was conducted across databases, including PubMed, Medline, ERIC, CINAHL, and Google Scholar, covering studies published between 2000 and 2023. Keywords related to 3D printing and simulation-based education were used. Inclusion criteria focused on peer-reviewed articles discussing 3D printing's role in KSAs for simulation educators and its applications in healthcare simulation. Articles were charted and analyzed thematically to identify trends, challenges, and outcomes. A total of 181 studies were included, spanning 36 countries and 113 journals. Most studies focused on medical education, with 73% utilizing 3D-printed models for direct teaching. Key themes identified included realism, skill development, cost-effectiveness, and teaching effectiveness. Challenges included model accuracy, training gaps for educators, and resource limitations. Study designs were predominantly descriptive, with a significant portion being single-site case reports. 3D printing has the potential to revolutionize simulation-based education by enhancing realism, accessibility, and skill development. However, gaps in educator training and methodological rigor must be addressed. Future research should focus on multi-institutional studies and long-term outcomes to maximize the impact of the technology.
Three-dimensional (3D) printing is transforming medical education through the production of highly accurate anatomical models and personalised surgical training tools. Despite its growing influence, comprehensive bibliometric assessments in this domain remain scarce. This study aims to map the intellectual landscape and research trends of 3D printing in medical education from 2010 to 2025, offering evidence-based guidance for future innovation. A systematic literature search was conducted in Web of Science Core Collection and PubMed for original articles and reviews related to 3D printing in medical education. CiteSpace was employed to construct and visualise collaboration, co-occurrence, and co-citation networks. The study included 302 articles from 96 institutions across 49 countries. The United States of America led in publication output, followed by China and Australia. Curtin University, the University of Toronto, and Mayo Clinic were the top three publishing institutions. The most prolific author published 11 papers, while the highest number of cited author as defined by co-citation analysis was 79. "Anatomical Sciences Education" was the most published-in and cited journal. The co-citation network analysis identified 12 thematic clusters-spanning medical modelling, anatomical education, and biomechanical testing-interconnected through pivotal high-centrality publications, illustrating the interdisciplinary expansion and evolving applications of 3D printing in medical education. Keyword analysis identified three major research hotspots: skill development and pedagogical validation, clinical surgical planning and doctor-patient communication, and emerging technologies with cross-disciplinary integration. This bibliometric analysis highlights an ongoing paradigm shift in 3D printing for medical education-from initial technical exploration toward rigorous validation of educational efficacy. Current research hotspots encompass anatomical modelling, surgical simulation, and AI/AR integration. However, persistent challenges such as limited dynamic simulation capabilities, high costs, and the absence of standardised assessment frameworks hinder progress. To realise meaningful educational transformation, strengthened interdisciplinary collaboration and technological innovation are essential to advance beyond technical demonstration toward tangible pedagogical improvement. Not applicable.
BACKGROUND: In the 2019/2020 winter semester, the University of Augsburg’s Faculty of Medicine introduced a competence-oriented model degree program with a spiral curriculum integrating theory and practice. A key feature, the clinical longitudinal course, emphasizes practical skills such as skin examination. Existing training materials for punch biopsies, e.g., foam models and fruit, have proven insufficient. This project aimed to create a realistic, cost-effective, reusable three-dimensional (3D) skin model to improve the teaching of punch biopsy and suturing techniques. METHODS: The 3D skin model was developed in a multistage process. It began with a 3D scan created via a handheld 3D scanner and refined in 3D modeling software. A fused deposition modeling (FDM) printer produced negative molds that were filled with silicone, resulting in a realistic model. After several iterations, a design was achieved that successfully simulated the tactile and functional aspects of punch biopsy and skin suturing. Student feedback was collected through an anonymous online questionnaire assessing perceived realism, usefulness for practicing punch biopsies and suturing, and impact on their confidence. RESULTS: The silicone-based skin simulator debuted in the 2023–2024 winter semester’s ‘examination of the skin’ course. A total of 82 students participated in the course, of whom 58 completed the evaluation questionnaire. The students used the model to perform punch biopsies and suturing, reporting that its material properties allowed these procedures to be practiced under course conditions. With a low production cost (of 0.62 € per model) compared to commercial models, it is a cost-efficient alternative to previous materials. The students provided positive feedback, reporting increased confidence in performing these procedures on humans for the first time. CONCLUSIONS: The 3D training model is an important advancement in introducing 3D technologies in practical training, providing realistic, cost-effective practice for punch biopsy and suturing. Its successful integration into the curriculum highlights its potential for broader applications in medical education. The evaluation indicated that the model provided realistic skin properties and proved effective for practicing punch biopsies and suturing, thus addressing the limitations of traditional training materials.
BACKGROUND: Traditional methods for producing custom-made orthoses are often time-consuming, labor-intensive, and reliant on manual processes, which limit both scalability and the degree of individualization. The development of 3D scanning technologies, computer-aided design (CAD), and additive manufacturing offers a promising alternative enabling patient-specific solutions with greater precision, speed, and efficiency. This study aimed to create an algorithm for automating the design process of personalized knee orthoses based on 3D scanning and intended for 3D printing production. METHODS: A parametric modeling workflow was developed in the Rhino environment using the Grasshopper plug-in to streamline personalized knee orthoses creation. The process began with acquiring high-quality 3D scans using Structure Sensor Mark II scanner mounted on an iPad with 3DsizeMe software. The parametric algorithm was transformed into an autonomous Rhino plug-in using C# language and RhinoCommon API. As part of Post-Market Clinical Follow-up (PMCF), three participants with knee joint disorders used orthoses for one month. Assessment used a 5-point scale (1 = poor, 5 = excellent). Personalized orthoses were manufactured using powder-bed fusion technology with PA11 CF nylon powder reinforced with carbon fibers. RESULTS: Design time was reduced from approximately 8 h to 10,3 ± 1,4 min. In Grasshopper prototype phase, average design time was 26,7 ± 4,5 min. Following the implementation of the Rhino plug-in, the design time was further reduced to approximately 10 min. The tool was shown to meet user requirements and fulfill its intended purpose. All three PMCF participants rated orthoses positively, reporting high comfort, effective stabilization, increased physical activity, and overall satisfaction with functionality and appearance. Participants P1 and P2 noted a large increase in physical activity, with P1 indicating pain reduction that increased mobility. CONCLUSIONS: This study demonstrates that the combined use of Rhino and Grasshopper provides an effective platform for parametric design of personalized knee orthoses based on patient-specific 3D scans. The workflow reduced design time to approximately 10,3 ± 1,4 min, highlighting potential for routine clinical applications. This reduction is economically significant, lowering labor costs and implementation thresholds for personalized orthotic solutions in clinical practice.
The way in which patient education is delivered during clinical consultations can have an impact on cognitive and emotional outcomes in patients. 3D printing and imaging can be used in patient education to improve understanding of the information and satisfaction with care. This scoping review sought to explore the psychological impact of using 3D models in patient education. Searches were conducted in PsycINFO, PsycARTICLES, PubMed, Medline and CINAHL. Levac et al.'s enhanced version of Arksey & O'Malley's methodological framework for conducting scoping reviews, and the PRISMA-ScR, were used to guide the screening and identification of relevant studies. Studies were included if they investigated the effect of using 3D models in patient education and explored psychological outcomes. Both quantitative and qualitative research were included. Eleven studies were included in the review, including 2 qualitative studies. 3D models were most often used in educational consultations preceding a surgical procedure (n = 9). Psychological outcomes assessed were anxiety, quality of life, distress relief, and decisional conflict. The results were mixed, showing that using 3D models can have a positive as well as negative effect on psychological outcomes such as fear and disempowerment. Using 3D models in patient education has the potential to improve patient anxiety and other psychological outcomes. However, more research is required to identify which patients and types of consultations 3D models are most useful for. For example, appointments involving important decision-making may benefit from the inclusion of 3D models. It is also essential to consider the communicative approach of the healthcare professional in the delivery of patient education with 3D models, as this factor is key to the outcomes of shared decision-making.
With 3D printing technology, we can now use preoperative imaging for precise surgical plan. We can also use patient-specific surgical jig to improve the accuracy of osteotomy and 3D-printed custom-made endoprostheses combined with a screw-rod system to restore lumbosacral stability. The aim of this study was to evaluate the accuracy of 3D printing technology for precise osteotomy during total sacrectomy. Nine patients with primary malignant tumors of the sacrum who underwent total sacrectomy at our center were enrolled. Osteotomy was planned based on preoperative imaging (CT, MRI). Generally, an additional 8-10 mm margin beyond the tumor was determined by the fusion of MR and CT images. Patient-specific surgical jigs and 3D-printed sacral endoprostheses were then designed based on the planned osteotomy planes. Pre- and postoperative 3D models of the lumbosacral and pelvic regions were constructed using the fiducial registration model of 3D slicer software 5.1.0. Postoperative CT scans were compared with the planned osteomy planes based on preoperative CT scans, in order to evaluate the accuracy of the osteotomy and endoprosthetic reconstruction. For each patient, four levels of osteotomy planes were chosen, including the upper edge of the sacroiliac (SI) joint, the S1 and S2 foramen levels, and the caudal edge of the SI joint, for analyzing position and angular deviations between the preoperative plan and actual osteotomy along with the endoprosthesis position. Pathological diagnoses included four cases of osteosarcoma, four cases of chordoma, and one case of Ewing sarcoma. All osteotomies in nine patients achieved R0 resection, as verified pathologically. An average angular deviation of 4.27° (interquartile range[IQR] 4.15) and an osteotomy position deviation of 4.00 mm (IQR 2.90) were observed. The mean angular deviations of the four levels were 3.50° (IQR 6.02), 3.86° (IQR 2.55), 4.81° (IQR 4.37), and 4.92° (IQR 3.27). The mean position deviations at the four levels were 3.15 mm (IQR 3.54), 3.55 mm (IQR 1.37), 4.26 mm (IQR 2.61), and 4.86 mm (IQR 3.93). No significant difference was found among the angular and position deviations at different levels. However, the proportions of individuals with position deviations > 2 mm and > 5 mm were significantly greater at the caudal end of the SI joint than at the upper end. All position deviations were within 8 mm. The average follow-up duration was 24.4 months. At the last follow-up, three patients experienced local recurrence, and one patient died of disease. All endoprostheses were in place without significant displacement. The mean Musculoskeletal Tumor Society scoring system (MSTS93) and MUD scores (function and sensation of lower limbs (M), urination and uriesthesia (U), and defecation and rectal sensation (D)) were 19.4 (16 to 24) and 16.3 (12 to 24), respectively. Notably, 3D-printed patient-specific surgical jigs exhibit high accuracy of osteotomy and lead to optimal surgical margin and reconstruction in total sacrectomy. Effective and reliable reconstruction can be achieved with a custom-made 3D-printed endoprosthesis. The application of 3D printing technology using patient-specific surgical jigs and the custom-made 3D-printed implants exhibited high surgical accuracy in total sacrectomy, as evidenced by accuracy validation.
Radiological training is often underrepresented in medical education, despite its essential role in clinical practice. Innovations like 3D printing offer detailed anatomical models that enhance understanding. In kidney cancer management, imaging and tumor complexity scores are crucial. This study evaluated whether three-dimensional (3D) kidney models could improve medical students' anatomical and spatial understanding of renal tumors, as assessed through CT-based complexity scoring. Three kidney tumor cases of varying complexity were selected. CT scans were segmented using Synapse 3D® to create models printed with high-resolution, multi-material technology (Stratasys J750®). Twenty-three fifth-year medical students were randomized into three groups: CT-only, CT + 3D virtual model (3DV), and CT + 3D-printed model (3DP). Each group interpreted the same anonymized CT scans and completed questionnaires assessing complexity scores and anatomical understanding. Accuracy and time efficiency were compared across groups. The 3DV and 3DP groups showed significantly greater accuracy in completing complexity scores (91% [IQR 82-91] and 91% [IQR 73-100]) than the CT-only group (73% [IQR 64-82], p < 0.05), reflecting improved spatial understanding of renal anatomy. Total scores and satisfaction were higher in 3D groups, with students endorsing the educational value of both model types. Time to completion was shorter in 3D groups (3DV: 9.4 min ± 4.7; 3DP: 7.1 min ± 3.5) versus CT-only (11 min ± 5.3, p < 0.05). Total scores and satisfaction were higher in 3D groups, with students endorsing the educational value of both model types. 3D-printed and virtual kidney models improved students' spatial understanding and task performance in renal tumor complexity assessment, reflecting enhanced anatomical comprehension rather than pure CT interpretation skills. Virtual models, offering similar educational benefits at lower cost, may be especially valuable for integration into medical curricula.
BACKGROUND: The consequences of maxillofacial injuries are functionals and aesthetics. The initial treatment must lead to consolidation without any sequelae (complete healing with no clinical symptoms). 3D printing is increasingly used in maxillofacial surgery, but data on its use in the initial phase of trauma is scarce. METHOD: We conducted a bibliographic search in PubMed’s electronic database with the following terms: maxillofacial traumatology, maxillofacial fracture, mandible fracture, maxillary fracture, zygoma fracture, LeFort fracture, fracture of the naso-ethmoido-maxillo-fronto-orbital complex, orbital fracture, nasal bones fracture, frontal sinus fracture, 3D printing, 3-dimensional printing, virtual planning. Data included study characteristics, material used, evaluation criteria, advantages, and disadvantages of the use of 3D printing. RESULTS: Fifty-six articles were selected and divided into 3 groups (multiple facial fractures, mandible fractures, and zygoma and/or orbital wall fractures). There were mainly retrospective studies and case reports, and the authors used CT scans to plan surgery. Printed objects were occlusal splints (n = 11 from fractures with occlusal disorders), and a skull model with fracture or after virtual reduction (n = 42). 3D printing permits a reduction in operating time from 15 to 60 min. The authors often used them to preshape plates, and the evaluation criteria were essentially radiologic (position of the implant compared to planning, precision of the reduction, orbital volume, etc.). CONCLUSION: The use of 3D printing permits reduced operating times and better visibility of movements. However, this often requires a post-operative CT scan, and little account is taken of clinical criteria. 3D printing and acute maxillofacial trauma: an overview of the literature.
Given the established and reproducible benefit of 3D-printed models in complex congenital heart disease (CHD) surgical planning, the focus has shifted from validating their utility to refining anatomical fidelity through enhanced imaging integration. The purpose of this study is to evaluate the perceived clinical utility of multimodality fusion 3D-printed cardiac models and to determine whether inclusion of valve structures confers incremental benefit over conventional single-modality 3D models in enhancing anatomical understanding and preoperative surgical planning among pediatric cardiac surgeons and imaging cardiologists in complex CHD. In this feasibility study, multimodality fusion 3D models were successfully generated by integrating cross-sectional imaging (cardiac computed tomography and magnetic resonance) with 3D echocardiographic datasets to reproduce atrioventricular valve apparatus and subvalvular structures in 10 pediatric patients with complex CHD. Ten faculty members (7 pediatric cardiologists with advanced imaging expertise and 3 pediatric cardiothoracic surgeons) evaluated 10 patient-specific models using a structured Likert questionnaire. Surgeons assigned significantly higher ratings than imagers for anatomical understanding (median 5 vs 4; p = 0.002) and surgical planning (p < 0.001). Participants agreed that multimodality models are most valuable in complex congenital heart disease, particularly in cases requiring ventricular septal defect patching or intraventricular baffle repair involving the subvalvular apparatus. Multimodality imaging fusion for 3D printing is technically feasible and produces high-quality models with strong intraoperative correlation. Incorporation of atrioventricular valve anatomy provides meaningful incremental benefit-particularly for surgeons-enhancing operative planning in complex CHD.
This study validates the intra-hospital design and 3D printing process of personalized surgical guides to enhance the accuracy of pedicle screw insertion in patients with thoracic scoliotic deformities. It introduces a novel collaborative paradigm between surgeons and engineers, aiming to improve efficiency and reduce errors in the manufacturing of patient-specific instruments (PSIs). The process began with the generation of 3D biomodels of vertebrae from computed tomography scans. Surgical guides were then created using two 3D printing techniques: Fused Filament Fabrication (FFF) with polylactic acid (PLA) and Stereolithography (SLA) with photopolymer resin. Three different prototypes were compared based on multifactorial indicators, including economic cost, macroscopic surface finish, and mechanical stability. The mechanical performance of the guides was evaluated under loads generated during pedicle screw penetration and threading. PLA models printed using FFF were found to be cheaper and simpler to manufacture than SLA resin models. Despite differences observed under a microscope, PLA models exhibited a macroscopic surface finish comparable to that of SLA resin models. Both materials demonstrated similar mechanical properties, although their values were lower than those reported in the manufacturer's datasheet. Importantly, both types of guides successfully withstood the mechanical loads generated during surgical procedures. The intra-hospital collaboration between engineers and surgeons was identified as a key factor in improving outcomes and reducing error risks, showcasing the benefits of interdisciplinary teamwork. 3D-printed PSIs made from PLA using FFF are more cost-effective and quicker to produce compared to SLA resin models, while achieving similar results in surface finish and mechanical stability. The implementation of a collaborative approach between engineers and surgeons within hospital settings enhances the efficiency and accuracy of patient-specific surgical guide manufacturing, offering a promising solution for improving surgical outcomes in thoracic scoliotic deformities.
BACKGROUND: Point-of-care (POC) three-dimensional (3D) printing of medical devices presents a paradigm shift in personalized medicine, yet clinical implementation of polyetheretherketone (PEEK) implants remains limited by regulatory, technical, and quality assurance challenges. Traditional external manufacturing timelines of 2–6 weeks constrain immediate reconstruction capabilities, particularly in trauma and oncologic cases requiring rapid intervention. Structured frameworks enabling MDR-compliant hospital-based production of implantable devices remain limited in the literature. METHODS: We implemented a comprehensive European Union Medical Device Regulation (EU MDR) 2017/745 Article 5(5)-compliant POC manufacturing framework incorporating an electronic quality management system aligned with ISO 13,485, a manufacturing execution system enabling end-to-end device traceability, risk management, process validation, biocompatibility evaluation, and integrated post-market surveillance. Medical-grade PEEK was processed using validated high-temperature specialised material extrusion 3D printers. RESULTS: Representative clinical applications of the EU MDR-compliant point-of-care manufacturing framework are illustrated in two anatomical contexts: (1) a POC 3D-printed PEEK cranial implant and (2) a POC 3D-printed PEEK facial implant. Manufacturing turnaround from image acquisition to sterile delivery was operationally achievable within 3–5 days. The patient-matched implants demonstrated accurate anatomical fit without intraoperative modification, with no major device-related complications observed. The framework has supported the production of over 40 + POC 3D-printed PEEK implants at the index institution and has since been adopted at multiple European centres, demonstrating transferability beyond the index case series. CONCLUSIONS: This work describes a validated EU MDR Article 5(5)-compliant framework for hospital-based production of patient-matched 3D-printed PEEK implants, demonstrated across cranial and facial reconstruction. Early clinical results support safety and feasibility, with end-to-end manufacturing achievable within a week, enabling flexible surgical planning. The framework provides a replicable pathway for regulated POC implant production, with multi-centre adoption and long-term outcome surveillance as critical next steps.
Integrating 3D printing into orthopedic oncology enables the development of patient-specific cutting guides for specific anatomy. To preserve surgical precision, especially in tumor resections where the safety margins must balance minimization of recurrence with avoidance of excessive bone removal, it is critical to maintain the dimensional accuracy of these guides throughout all stages of fabrication, disinfection, cleaning, and sterilization. Personalized cutting guides were 3D printed using ten filaments, and 3D scanned before and after sterilization. Two sterilization methods were used: autoclave and vaporized hydrogen peroxide. Dimensional deviations were assessed by comparing the reference STL model with the scanned models using metrics such as root mean square, standard deviation, Gaussian mean, and maximum error. Pearson correlation analysis was conducted to evaluate inter-sample variability and metric interdependence. PLA and PETG showed the best dimensional accuracy in the as-printed state with RMS values of 0.093 mm and 0.093 mm, respectively, and standard deviations below 0.092 mm. After hydrogen peroxide sterilization, PETG, PC, and PETG-CF kept a high accuracy, while PLA, PLA-HP, PA, and PA6-CF showed significant deformations. Autoclave sterilization determined severe deformation in most materials, with PC showing unexpectedly changes of the geometrical form, increasing in RMS error from 0.127 mm to 3.642 mm. In the as-printed state, maximum error remained below 0.29 mm for all materials, with PLA having the highest localized deviation (0.283 mm). After hydrogen peroxide sterilization, PETG, PC, and ABS maintained maximum error values lower than 0.27 mm, while PLA increased to 0.274 mm and PLA-HP to 0.268 mm. These values, although moderate, showed geometric changes that affect fit in anatomically constrained regions. Pearson correlation analysis showed that hydrogen peroxide sterilization altered the relationship between accuracy metrics of prints after manufacturing, weakening the correlation between RMS and Gaussian mean. This suggested increased unpredictability in deformation direction and highlighted less consistent deformation patterns. Disinfection and sterilization processes were highly material-dependent, as expected. PETG, PC, and PETG-CF were the most stable materials for the 3D-printed surgical guides when using cold plasma sterilization. Materials like PLA, PLA-HP, and PA require caution due to their instability. Designers should take into account the deformation directionality loss post-sterilization and integrate fit allowances into surgical guide geometry.
BACKGROUND: To determine the reusability and robustness of three 3D-printing materials for anatomical vessels by evaluating their contrast agent uptake characteristics throughout different timeframes. METHODS: The tested samples were 3D-printed cylindrical samples that have the same diameter and wall thickness as a healthy adult aorta. Three different materials of varying degrees of Shore hardness were used to print these samples on a Stratasys J850 Prime PolyJet 3D printer (VeroClear, Agilus, and an Agilus/VeroClear mixture). Each sample was filled with one of three contrast agent dilutions or a control solution. Samples remained filled with their respective solution for one week, one day, or one hour. Computed tomography (CT) and magnetic resonance (MR) images were taken of all 54 samples. The CT and MR images were evaluated to determine the diameters of the samples, as well as the radiodensity/signal intensity of the samples. An Intraclass Correlation Coefficient (ICC) was calculated to determine the degree of measurement variation between the investigators. Sample mass increase was determined by weighing samples before and after exposure to the solutions. A generalized linear mixed model (GLMM) was used to evaluate the contrast agent uptake behavior of the materials based on CT and MR imaging data. RESULTS: A small relative mass increase in the 3D-printed materials was noted: VeroClear showed mass increases of between 1.1% and 2.5%, which is in line with the respective data sheet. Agilus showed mass increases of 2.9% to 4.4%. In CT images, very small, but statistically significant effects were detected for VeroClear in the measured diameters (t = −2.31, p = 0.02) and the signal intensity (t = 3.40, p < 0.001). All other tested material combinations revealed no significant effects in comparison to the reference sample. CONCLUSIONS: This study suggests that the tested materials using the Stratasys J850 3D printer can produce structures that do not absorb clinically detectable amounts of CT or MR imaging contrast agent solutions. Thus, the tested materials are suitable for the 3D printing of vascular phantoms that are filled with contrast agent solutions and can be reused in the time periods evaluated.
The optic pathway is a complex neural structure responsible for transmitting visual information from the retina to the brain. Traditionally, the optic pathway has been depicted using two-dimensional (2D) illustrations, which, while useful for simplification, can obscure depth, orientation, and connectivity, limiting a full understanding of its three-dimensional (3D) nature which is important for surgical planning and neuroanatomy education. Due to a convergence of advancing technologies in MRI image acquisition, medical CAD and 3D illustration software, as well as 3D printing technologies, these 3D visualizations can now be physically manufactured to provide life size, patient specific, physical, color-coded 3D models. 3D models manufactured from advanced imaging can provide a more accurate, interactive, non-invasive, cost-effective alternative to medical illustration and animation than traditional dissected cadaveric anatomical specimens for both clinical and educational purposes. The source data for this project came from both a 42 year old male patient and a 21 year old male volunteer after both had been scanned on the same seven tesla MRI including DTI for the patient and volumetric sequences for the volunteer. The model was created by segmenting the optic pathway using medical CAD software and 3D illustration software. The DTI tracts were coregistered to the anatomic brain. The model was optimized for printing and hypothetical "lesions" were added along the pathway with their corresponding visual deficits. The model was printed on an HP580 multijet fusion color printer and photorealistic eyes were printed using material jetting of photopolymer via a Stratasys J750 printer. Multiple challenges were overcome to successfully create a life size, physical, multicolor 3D printed representation of the optic pathway created from 7T MRI data. This workflow resulted in a unique educational 3D representation of the human optic pathway that allows for direct manipulation, haptic feedback, and clear understanding of the anatomic relations both of this system normally and the correlations between lesion location and resultant expected visual field impairment. As opposed to the inconvenience, costs, and limited access accompanying the classical standard of advanced dissections of human specimens, this model is available to all learners in all environments.
INTRODUCTION: Effective procedural training is crucial for emergency interventions such as percutaneous cricothyrotomy (PC). This study evaluated simulation-based training of PC by comparing two simulators, a commercially available conventional simulator (CSIM) and an innovative 3D-printed simulator (3DSIM), and assessed their impact on procedural performance and subjective safety perceptions using two different PC kits: Quicktrach II (direct puncture method) and Surgicric III (Seldinger technique). METHODS: Forty-four participants underwent standardized theoretical training and were randomized into two groups: Group A initially trained with CSIM and Group B with 3DSIM. In both groups, procedural performance was evaluated immediately after each simulation session on porcine trachea models by two blinded assessors. Outcomes included procedural time, standardized performance scores, and subjective safety ratings. Participant evaluations of educational benefit and simulator realism were also recorded. Training effectiveness was reassessed in a second session using a crossover design, allowing direct comparison of the two simulators and kits. RESULTS: Procedural performance improved significantly after repeated training, with no significant differences between CSIM and 3DSIM regarding procedural times (p = 0.98) or accuracy scores (p = 0.99). Both PC kits showed significantly reduced procedural times (Quicktrach II: 42 ± 46 to 19 ± 7 s, p < 0.01; Surgicric III: 119 ± 73 to 91 ± 51 s, p = 0.03). Accuracy improved significantly only for Surgicric III (95 ± 10% to 98 ± 4%, p = 0.04). Participants’ perceived safety improved similarly for both simulators (44 ± 20% to 94 ± 9%), without differences in educational benefit or realism ratings. CONCLUSION: Conventional and 3D-printed simulators were equally effective in enhancing procedural performance and subjective safety perceptions in PC training. Procedural time improvements differed by kit complexity, suggesting Quicktrach II offers quicker initial mastery, whereas Surgicric III may require additional practice due to its greater complexity. These results support flexible simulator choice based on local factors like cost and availability, underscoring the potential of 3D-printed simulators for procedural training programs. CLINICAL TRIAL NUMBER: Not applicable.
Acetaminophen is a widely used antipyretic and analgesic treatment. Becuase oral administration poses a risk of acute liver failure, researchers are exploring alternative routes of administration using 3D printing. This study reports a novel 3D-printed suppository using hot melt extrusion and melt deposition molding technologies. Through excipients screening, process screening and 3D printing, the production can be filtered to the most optimal state. After successfully prepared 3D printed acetaminophen suppository, the suppository's performance and pharmacokinetics profile were also evaluated. Prepared 3D printed suppository has a complete appearance, smooth interlayer stacking and qualified content determination with over 90% within 6 hours' in vitro release trend. The 3D printing acetaminophen suppository also has better release and distribution curve than the marketing acetaminophen suppository. The obtained product has a complete appearance, smooth interlayer stacking and stable drug active molecules (API) at the test temperature. Melt deposition molding technologies offers a viable option for the 3D printing preparation of acetaminophen suppository.
Cartilage repair is challenging due to the tissue's limited regenerative capacity. Synthetic 3D-printed scaffolds provide essential structural support, but typically lack the bioactivity needed for cell integration. A promising approach combines 3D-printed porous scaffolds filled with self-assembling peptide hydrogels, which serve as nanofiber scaffolds inside the macropores of the structural scaffold, creating a hybrid structure. The selection strategy for the 3D printing of the synthetic scaffolds was driven by two distinct cross-linking processes: a vinyl-ester based thiol-ene photopolymer crosslinked via free radical polymerization and printed with digital light processing, resulting in a stiff mechanical network and polydimethylsiloxane, namely AMSil™ 20503-50 from the AMSil™ 20,503 series, printed via liquid deposition modeling and crosslinked through polyaddition, which yields flexible scaffolds capable of adapting to dynamic mechanical environments. These properties make them suitable for load-bearing applications where structural integrity is paramount. Both 3D-printed scaffold types, characterized by interconnected macropores ranging from 0.8 to 1.2 mm, were augmented with a peptide hydrogel scaffold, such as RADA16 and IEIK13, that self-assembles inside the macropores to create a nanofiber network mimicking the extracellular matrix and enhancing bioactivity. The hybrid structure, combining the macropores of a structural 3D-printed scaffold and the nanofiber network of the peptide hydrogel scaffold improved cell adhesion, proliferation, and differentiation. Comparative analysis showed that, while both RADA16 and IEIK13 hydrogels enhanced cell integration within the macropores, RADA16 was especially effective in supporting cartilage-like ECM formation. The creation of a hybrid scaffold with hierarchical porosity-integrating the structural macropores of a synthetic 3D-printed scaffold with the bioactive nanofiber network of a peptide hydrogel-addresses the limitations of purely structural scaffolds. The hybrid approach not only enhances fast and accessible scaffold fabrication but also accelerates the development of functional scaffolds.