Creation of a High-Fidelity, Low-Cost, Intraosseous Line Placement Task Trainer via 3D Printing
August 17th, 2022
2.3K views
We describe a procedure to process computed tomography (CT) scans into high-fidelity, reclaimable, and low-cost procedural task trainers. The CT scan identification processes, export, segmentation, modeling, and 3D printing are all described, along with the issues and lessons learned in the process.
Overview
This article details a protocol for creating high-fidelity, anatomically accurate procedural task trainers using CT scan data, 3D printing technology, and reusable tissue media. The method addresses common limitations of existing trainers by enabling realistic anatomy, customizable models, and the ability to refresh the trainer after each use, supporting effective and safe procedural skills training.
Key Study Components
Area of Science
- Medical simulation
- 3D printing technology
- Medical education
Background
- Procedural task trainers are essential for developing technical skills in a safe environment.
- Many current trainers lack anatomical realism and degrade with repeated use, leading to inaccurate skill development.
- Advances in 3D printing and imaging allow for more precise anatomical replication.
- Reusable components can reduce costs and maintain training quality.
Purpose of Study
- To develop a protocol for producing high-fidelity, anatomically accurate task trainers from CT scans.
- To enable repeated, realistic procedural practice without degradation of the trainer.
- To demonstrate the feasibility and effectiveness of this approach for various anatomical models.
Methods Used
- Selection and processing of CT scan data to obtain the desired anatomical section.
- 3D modeling and editing of bone and tissue structures using specialized software (e.g., Autodesk Fusion 360).
- 3D printing of molds, bones, and support components with polylactic acid filament.
- Preparation of a tissue medium (gelatin, cilium husk fiber, chlorhexidine, sodium hypochlorite) and simulated bone marrow solution.
- Assembly of the trainer by pouring tissue medium into the mold, positioning bones, and finalizing with simulated marrow.
- Disassembly and reclamation of components for reuse after training sessions.
Main Results
- Successfully produced anatomically accurate task trainers for various bones (e.g., humerus, tibia) with high fidelity to CT scan data.
- Trainers allowed for realistic procedural practice, such as intraosseous line placement, including aspiration of simulated marrow.
- Components (tissue media, molds, bones) were reclaimable and reusable, enabling cost-effective repeated training.
- Customization of tissue opacity allowed for different visualization needs during training.
Conclusions
- The described protocol enables creation of high-fidelity, reusable procedural task trainers tailored to specific anatomical needs.
- These trainers support effective skill transfer from simulation to clinical practice due to their anatomical realism.
- The approach is cost-effective and adaptable for a range of procedures and anatomical sites.
Frequently Asked Questions
What is the main advantage of using CT-derived 3D printed task trainers?
They provide anatomically accurate models that closely replicate real human anatomy, improving the realism and effectiveness of procedural training.
How are the anatomical models created from CT scans?
CT scan data is processed and edited using 3D modeling software to generate printable files for bones and surrounding tissue structures.
What materials are used for the tissue medium and bone simulation?
The tissue medium is made from gelatin, cilium husk fiber, chlorhexidine, and sodium hypochlorite, while bones are 3D printed using polylactic acid filament.
Can the task trainers be reused after a training session?
Yes, the tissue media, molds, and bones can be reclaimed and reused to create a fresh trainer for subsequent sessions.
What types of procedures can be practiced with these trainers?
Procedures such as intraosseous line placement and other bone-related interventions can be practiced, with trainers customizable for different anatomical sites.
How is the simulated bone marrow created and used?
A mixture of water, ultrasound gel, and red food coloring is used to simulate bone marrow, which is placed in the marrow cavity after assembly.
What are key considerations for successful 3D printing of the molds?
Using strong adhesives to prevent warping, applying a releasing spray to the mold interior, and optimizing print settings are important for high-quality results.
Executive Industry Relevance
High-fidelity, anatomically accurate 3D printed task trainers derived from CT data address critical gaps in procedural simulation by enabling reproducible, realistic skill acquisition. This approach supports translational continuity from preclinical modeling to clinical training, reducing variability and enhancing predictive confidence in procedural outcomes. The reclaimable and customizable nature of these trainers offers scalable, cost-effective solutions for enterprise-level R&D and training programs.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables precise modeling of human anatomical structures for hypothesis-driven procedural development.
- Supports biological de-risking by providing anatomically accurate, reproducible models for technical validation.
- Facilitates predictive confidence in procedural feasibility and technique optimization.
Screening & Assay Development
- Provides standardized, reusable platforms for evaluating device or tool performance in simulated tissue environments.
- Ensures reproducibility and quantitative assessment of procedural endpoints through consistent anatomical replication.
- Enables scalable preparation of validated models for iterative testing and screening workflows.
Translational & Preclinical Research
- Aligns simulation models with disease-relevant human anatomy for translational research continuity.
- Supports risk-adjusted advancement decisions by enabling robust preclinical procedural validation.
- Reduces late-stage technical risk by standardizing skill transfer from simulation to clinical environments.
Pipeline & Workflow Integration
This protocol integrates into the discovery-to-preclinical continuum by providing anatomically accurate, customizable models for procedural development, validation, and training.
- Discovery Biology: Facilitates hypothesis testing and anatomical pathway clarification for procedural innovation.
- Screening: Delivers reproducible, quantitative outputs for device or technique evaluation.
- Analytics: Supports measurement of procedural accuracy, repeatability, and technical endpoints.
- Translational Research: Bridges preclinical and clinical workflows through anatomically aligned simulation models.
- Enterprise Reuse: Offers reclaimable components and customizable designs for broad R&D applicability.
Operational & Enterprise Impact
- Scientific Value: Enhances predictive confidence and reduces mechanistic ambiguity in procedural development.
- Operational Value: Standardizes training and validation with reusable, cost-effective models.
- Strategic Value: Improves go/no-go decisions and capital efficiency by reducing technical variability.
- Portfolio Impact: Enables risk-adjusted prioritization and advancement of procedural innovations.
Implementation Considerations
- Requires expertise in 3D modeling, CT data processing, and additive manufacturing.
- Needs access to 3D printing infrastructure and compatible materials for anatomical fidelity.
- Demands cross-team standardization for model preparation and procedural assessment.
- Adaptable across anatomical sites and procedural types with protocol modifications.
- Dependent on quality of imaging data and print optimization for reproducibility.
Biopharma FAQs
Why does null hypothesis testing matter for anatomical model validation?
Null hypothesis testing ensures that observed procedural outcomes using the 3D printed task trainer are not due to random variation, supporting robust validation of anatomical fidelity and technical reproducibility.
How does independent variable isolation fit in 3D printed trainer development?
Isolating variables such as tissue density or bone geometry during model creation allows teams to systematically assess their impact on procedural performance, strengthening discovery-stage optimization.
What do quantitative dependent variable measurements enable in procedural simulation?
Quantitative measurements, such as accuracy of intraosseous line placement or aspiration success, provide objective endpoints for comparing techniques and refining procedural protocols.
Why are replication requirements critical for cross-functional procedural training?
Replication ensures that each training session uses a defect-free, anatomically consistent model, supporting reliable skill transfer and cross-team comparability in procedural outcomes.
What statistical analysis capabilities are needed before implementing 3D printed trainers?
Teams must be able to analyze procedural accuracy, reproducibility, and technical endpoints across multiple sessions to validate model performance and inform R&D decision-making.
