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Wendo K, Behets C, Barbier O, Herman B, Schubert T, Raucent B, Olszewski R. Dimensional Accuracy Assessment of Medical Anatomical Models Produced by Hospital-Based Fused Deposition Modeling 3D Printer. J Imaging 2025; 11:39. [PMID: 39997541 PMCID: PMC11856956 DOI: 10.3390/jimaging11020039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2024] [Revised: 01/13/2025] [Accepted: 01/23/2025] [Indexed: 02/26/2025] Open
Abstract
As 3D printing technology expands rapidly in medical disciplines, the accuracy evaluation of 3D-printed medical models is required. However, no established guidelines to assess the dimensional error of anatomical models exist. This study aims to evaluate the dimensional accuracy of medical models 3D-printed using a hospital-based Fused Deposition Modeling (FDM) 3D printer. Two dissected cadaveric right hands were marked with Titanium Kirshner wires to identify landmarks on the heads and bases of all metacarpals and proximal and middle phalanges. Both hands were scanned using a Cone Beam Computed Tomography scanner. Image post-processing and segmentation were performed on 3D Slicer software. Hand models were 3D-printed using a professional hospital-based FDM 3D printer. Manual measurements of all landmarks marked on both pairs of cadaveric and 3D-printed hands were taken by two independent observers using a digital caliper. The Mean Absolute Difference (MAD) and Mean Dimensional Error (MDE) were calculated. Our results showed an acceptable level of dimensional accuracy. The overall study's MAD was 0.32 mm (±0.34), and its MDE was 1.03% (±0.83). These values fall within the recommended range of errors. A high level of dimensional accuracy of the 3D-printed anatomical models was achieved, suggesting their reliability and suitability for medical applications.
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Affiliation(s)
- Kevin Wendo
- Neuro Musculo Skeletal Lab (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium; (O.B.); (T.S.); (R.O.)
- Oral and Maxillofacial Surgery Lab (OMFS Lab), NMSK, IREC, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium
- Department of Pediatrics, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Catherine Behets
- Morphology Lab (MORF), IREC, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium;
| | - Olivier Barbier
- Neuro Musculo Skeletal Lab (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium; (O.B.); (T.S.); (R.O.)
- Department of Orthopedic Surgery, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Benoit Herman
- Institute of Mechanics, Materials and Civil Engineering, Université Catholique de Louvain (UCLouvain), 1348 Louvain-La-Neuve, Belgium; (B.H.); (B.R.)
| | - Thomas Schubert
- Neuro Musculo Skeletal Lab (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium; (O.B.); (T.S.); (R.O.)
- Department of Orthopedic Surgery, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
| | - Benoit Raucent
- Institute of Mechanics, Materials and Civil Engineering, Université Catholique de Louvain (UCLouvain), 1348 Louvain-La-Neuve, Belgium; (B.H.); (B.R.)
| | - Raphael Olszewski
- Neuro Musculo Skeletal Lab (NMSK), Institut de Recherche Expérimentale et Clinique (IREC), Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium; (O.B.); (T.S.); (R.O.)
- Oral and Maxillofacial Surgery Lab (OMFS Lab), NMSK, IREC, Université Catholique de Louvain (UCLouvain), 1200 Brussels, Belgium
- Department of Oral and Maxillofacial Surgery, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium
- Department of Perioperative Dentistry, L. Rydygiera Collegium Medicum, Nicolaus Copernicus University, 85-067 Bydgoszcz, Poland
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Mersanne A, Foresti R, Martini C, Caffarra Malvezzi C, Rossi G, Fornasari A, De Filippo M, Freyrie A, Perini P. In-House Fabrication and Validation of 3D-Printed Custom-Made Medical Devices for Planning and Simulation of Peripheral Endovascular Therapies. Diagnostics (Basel) 2024; 15:8. [PMID: 39795536 PMCID: PMC11719810 DOI: 10.3390/diagnostics15010008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2024] [Revised: 12/23/2024] [Accepted: 12/23/2024] [Indexed: 01/13/2025] Open
Abstract
Objectives: This study aims to develop and validate a standardized methodology for creating high-fidelity, custom-made, patient-specific 3D-printed vascular models that serve as tools for preoperative planning and training in the endovascular treatment of peripheral artery disease (PAD). Methods: Ten custom-made 3D-printed vascular models were produced using computed tomography angiography (CTA) scans of ten patients diagnosed with PAD. CTA images were analyzed using Syngo.via by a specialist to formulate a medical prescription that guided the model's creation. The CTA data were then processed in OsiriX MD to generate the .STL file, which is further refined in a Meshmixer. Stereolithography (SLA) 3D printing technology was employed, utilizing either flexible or rigid materials. The dimensional accuracy of the models was evaluated by comparing their CT scan images with the corresponding patient data, using OsiriX MD. Additionally, both flexible and rigid models were evaluated by eight vascular surgeons during simulations in an in-house-designed setup, assessing both the technical aspects and operator perceptions of the simulation. Results: Each model took approximately 21.5 h to fabricate, costing €140 for flexible and €165 for rigid materials. Bland-Alman plots revealed a strong agreement between the 3D models and patient anatomy, with outliers ranging from 4.3% to 6.9%. Simulations showed that rigid models performed better in guidewire navigation and catheter stability, while flexible models offered improved transparency and lesion treatment. Surgeons confirmed the models' realism and utility. Conclusions: The study highlights the cost-efficient, high-fidelity production of 3D-printed vascular models, emphasizing their potential to enhance training and planning in endovascular surgery.
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Affiliation(s)
- Arianna Mersanne
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, 43126 Parma, Italy
| | - Ruben Foresti
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy; (R.F.)
- Center of Excellence for Toxicological Research (CERT), University of Parma, 43126 Parma, Italy
- Italian National Research Council, Institute of Materials for Electronics and Magnetism (CNR-IMEM), 43124 Parma, Italy
| | - Chiara Martini
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy; (R.F.)
- Diagnostic Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | | | - Giulia Rossi
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, 43126 Parma, Italy
| | - Anna Fornasari
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, 43126 Parma, Italy
| | - Massimo De Filippo
- Department of Medicine and Surgery, Section of Radiology, University of Parma, Maggiore Hospital, Via Gramsci 14, 43126 Parma, Italy
| | - Antonio Freyrie
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, 43126 Parma, Italy
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy; (R.F.)
| | - Paolo Perini
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, 43126 Parma, Italy
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy; (R.F.)
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Jung S, Hoffmann M, Winkler D, Güresir E, Kropla F, Scholz S, Grunert R. Influence of the orientation of constructed blood vessels during the 3D printing on the measurement of the pseudo-oxygen saturation of an artificial blood substitute using conventional oxygen sensors: a test series. 3D Print Med 2024; 10:40. [PMID: 39592528 PMCID: PMC11600587 DOI: 10.1186/s41205-024-00246-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 11/15/2024] [Indexed: 11/28/2024] Open
Abstract
BACKGROUND The development of phantoms to reduce animal testing or to validate new instruments or operation techniques is of increasing importance. For this reason, a blood circulation phantom was developed to test a newly designed retractor system with an integrated oxygen sensor. This phantom was used to evaluate the impact of the 3D printed blood vessel on the measurement of the oxygen saturation. METHODS A solution of nickel sulfate and copper sulfate was prepared as a substitute for real blood. The absorption spectra of these solutions were recorded and compared with those of blood. Subsequently, the oxygen sensor used was calibrated to the blood substitute. Additionally, blood vessels with a simplified geometry were designed and manufactured using inverted vat polymerization and an elastic material (Formlabs Elastic 50 A). To determine the orientation during the printing process, various vessels were printed. Measurements to assess the effects of disturbance (rotation of the vessels during measurements) on the sensor readouts were prepared. RESULTS The impact of disturbances was verified through the rotation of the 3D printed vessels. It was demonstrated that a direct measurement on the disturbances led to outliers and higher values. An optimal orientation was determined to be a lateral placement (90° or 270°) of the sensor. Regarding the orientation of the vessels within the printing space, an orientation of 45° yielded the best results, as the individual layers had the least impact on the light emitted and received by the oxygen sensor. CONCLUSION The achieved results demonstrate the influence of the orientation of the vessel during 3D printing as well as the influence of the position of the vessel during the measurement using a conventional oxygen sensor.
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Affiliation(s)
- Svenja Jung
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany.
| | - Martin Hoffmann
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany
| | - Dirk Winkler
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany
| | - Erdem Güresir
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany
| | - Fabian Kropla
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany
| | - Sebastian Scholz
- Fraunhofer-Institute for Machine Tools and Forming Technology, 02763, Zittau, Germany
| | - Ronny Grunert
- Department of Neurosurgery, University of Leipzig Medical Center, Liebigstr.20, 04103, Leipzig, Germany
- Fraunhofer-Institute for Machine Tools and Forming Technology, 02763, Zittau, Germany
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Sakai AKF, Cestari IN, de Sales E, Mazzetto M, Cestari IA. Metamaterial design for aortic aneurysm simulation using 3D printing. 3D Print Med 2024; 10:29. [PMID: 39110290 PMCID: PMC11304610 DOI: 10.1186/s41205-024-00219-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 05/18/2024] [Indexed: 08/10/2024] Open
Abstract
INTRODUCTION The use of three-dimensional (3D) printed anatomic models is steadily increasing in research and as a tool for clinical decision-making. The mechanical properties of polymers and metamaterials were investigated to evaluate their application in mimicking the biomechanics of the aortic vessel wall. METHODOLOGY Uniaxial tensile tests were performed to determine the elastic modulus, mechanical stress, and strain of 3D printed samples. We used a combination of materials, designed to mimic biological tissues' properties, the rigid VeroTM family, and the flexible Agilus30™. Metamaterials were designed by tessellating unit cells that were used as lattice-reinforcement to tune their mechanical properties. The lattice-reinforcements were based on two groups of patterns, mainly responding to the movement between links/threads (chain and knitted) or to deformation (origami and diamond crystal). The mechanical properties of the printed materials were compared with the characteristics of healthy and aneurysmal aortas. RESULTS Uniaxial tensile tests showed that the use of a lattice-reinforcement increased rigidity and may increase the maximum stress generated. The pattern and material of the lattice-reinforcement may increase or reduce the strain at maximum stress, which is also affected by the base material used. Printed samples showed max stress ranging from 0.39 ± 0.01 MPa to 0.88 ± 0.02 MPa, and strain at max stress ranging from 70.44 ± 0.86% to 158.21 ± 8.99%. An example of an application was created by inserting a metamaterial designed as a lattice-reinforcement on a model of the aorta to simulate an abdominal aortic aneurysm. CONCLUSION The maximum stresses obtained with the printed models were similar to those of aortic tissue reported in the literature, despite the fact that the models did not perfectly reproduce the biological tissue behavior.
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Affiliation(s)
- Arthur K F Sakai
- Electrical Engineering Graduate Program, Telecommunications and Control Engineering Department, Polytechnic School, University of São Paulo, São Paulo, Brazil
| | - Ismar N Cestari
- Laboratório de Bioengenharia, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Eraldo de Sales
- Laboratório de Bioengenharia, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Marcelo Mazzetto
- Laboratório de Bioengenharia, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Idágene A Cestari
- Electrical Engineering Graduate Program, Telecommunications and Control Engineering Department, Polytechnic School, University of São Paulo, São Paulo, Brazil.
- Laboratório de Bioengenharia, Instituto do Coração, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
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Catasta A, Martini C, Mersanne A, Foresti R, Bianchini Massoni C, Freyrie A, Perini P. Systematic Review on the Use of 3D-Printed Models for Planning, Training and Simulation in Vascular Surgery. Diagnostics (Basel) 2024; 14:1658. [PMID: 39125534 PMCID: PMC11312310 DOI: 10.3390/diagnostics14151658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2024] [Revised: 07/22/2024] [Accepted: 07/30/2024] [Indexed: 08/12/2024] Open
Abstract
The use of 3D-printed models in simulation-based training and planning for vascular surgery is gaining interest. This study aims to provide an overview of the current applications of 3D-printing technologies in vascular surgery. We performed a systematic review by searching four databases: PubMed, Web of Science, Scopus, and Cochrane Library (last search: 1 March 2024). We included studies considering the treatment of vascular stenotic/occlusive or aneurysmal diseases. We included papers that reported the outcome of applications of 3D-printed models, excluding case reports or very limited case series (≤5 printed models or tests/simulations). Finally, 22 studies were included and analyzed. Computed tomography angiography (CTA) was the primary diagnostic method used to obtain the images serving as the basis for generating the 3D-printed models. Processing the CTA data involved the use of medical imaging software; 3DSlicer (Brigham and Women's Hospital, Harvard University, Boston, MA), ITK-Snap, and Mimics (Materialise NV, Leuven, Belgium) were the most frequently used. Autodesk Meshmixer (San Francisco, CA, USA) and 3-matic (Materialise NV, Leuven, Belgium) were the most frequently employed mesh-editing software during the post-processing phase. PolyJet™, fused deposition modeling (FDM), and stereolithography (SLA) were the most frequently employed 3D-printing technologies. Planning and training with 3D-printed models seem to enhance physicians' confidence and performance levels by up to 40% and lead to a reduction in the procedure time and contrast volume usage to varying extents.
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Affiliation(s)
- Alexandra Catasta
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Chiara Martini
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy
- Diagnostic Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Arianna Mersanne
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Ruben Foresti
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy
- Center of Excellence for Toxicological Research (CERT), University of Parma, 43126 Parma, Italy
- Italian National Research Council, Institute of Materials for Electronics and Magnetism (CNR-IMEM), 43124 Parma, Italy
| | - Claudio Bianchini Massoni
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Antonio Freyrie
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy
| | - Paolo Perini
- Vascular Surgery, Cardio-Thoracic and Vascular Department, University-Hospital of Parma, Via Gramsci 14, 43126 Parma, Italy
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43126 Parma, Italy
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Schulze M, Juergensen L, Rischen R, Toennemann M, Reischle G, Puetzler J, Gosheger G, Hasselmann J. Quality assurance of 3D-printed patient specific anatomical models: a systematic review. 3D Print Med 2024; 10:9. [PMID: 38536566 PMCID: PMC10967057 DOI: 10.1186/s41205-024-00210-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 03/14/2024] [Indexed: 01/03/2025] Open
Abstract
BACKGROUND The responsible use of 3D-printing in medicine includes a context-based quality assurance. Considerable literature has been published in this field, yet the quality of assessment varies widely. The limited discriminatory power of some assessment methods challenges the comparison of results. The total error for patient specific anatomical models comprises relevant partial errors of the production process: segmentation error (SegE), digital editing error (DEE), printing error (PrE). The present review provides an overview to improve the general understanding of the process specific errors, quantitative analysis, and standardized terminology. METHODS This review focuses on literature on quality assurance of patient-specific anatomical models in terms of geometric accuracy published before December 4th, 2022 (n = 139). In an attempt to organize the literature, the publications are assigned to comparable categories and the absolute values of the maximum mean deviation (AMMD) per publication are determined therein. RESULTS The three major examined types of original structures are teeth or jaw (n = 52), skull bones without jaw (n = 17) and heart with coronary arteries (n = 16). VPP (vat photopolymerization) is the most frequently employed basic 3D-printing technology (n = 112 experiments). The median values of AMMD (AMMD: The metric AMMD is defined as the largest linear deviation, based on an average value from at least two individual measurements.) are 0.8 mm for the SegE, 0.26 mm for the PrE and 0.825 mm for the total error. No average values are found for the DEE. CONCLUSION The total error is not significantly higher than the partial errors which may compensate each other. Consequently SegE, DEE and PrE should be analyzed individually to describe the result quality as their sum according to rules of error propagation. Current methods for quality assurance of the segmentation are often either realistic and accurate or resource efficient. Future research should focus on implementing models for cost effective evaluations with high accuracy and realism. Our system of categorization may be enhancing the understanding of the overall process and a valuable contribution to the structural design and reporting of future experiments. It can be used to educate specialists for risk assessment and process validation within the additive manufacturing industry.
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Affiliation(s)
- Martin Schulze
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany.
| | - Lukas Juergensen
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany
| | - Robert Rischen
- Clinic for Radiology, University Hospital Muenster, 48149, Muenster, Germany
| | - Max Toennemann
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany
| | | | - Jan Puetzler
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany
| | - Georg Gosheger
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany
| | - Julian Hasselmann
- Department of General Orthopedics and Tumor Orthopedics, University Hospital Muenster, 48149, Münster, Germany
- Department of Mechanical Engineering, Materials Engineering Laboratory, University of Applied Sciences Muenster, 48565, Steinfurt, Germany
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Lee J, Chadalavada SC, Ghodadra A, Ali A, Arribas EM, Chepelev L, Ionita CN, Ravi P, Ryan JR, Santiago L, Wake N, Sheikh AM, Rybicki FJ, Ballard DH. Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions. 3D Print Med 2023; 9:34. [PMID: 38032479 PMCID: PMC10688120 DOI: 10.1186/s41205-023-00196-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Medical three-dimensional (3D) printing has demonstrated utility and value in anatomic models for vascular conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (3DPSIG) provides appropriateness recommendations for vascular 3D printing indications. METHODS A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with vascular indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings. RESULTS Evidence-based recommendations for when 3D printing is appropriate are provided for the following areas: aneurysm, dissection, extremity vascular disease, other arterial diseases, acute venous thromboembolic disease, venous disorders, lymphedema, congenital vascular malformations, vascular trauma, vascular tumors, visceral vasculature for surgical planning, dialysis access, vascular research/development and modeling, and other vasculopathy. Recommendations are provided in accordance with strength of evidence of publications corresponding to each vascular condition combined with expert opinion from members of the 3DPSIG. CONCLUSION This consensus appropriateness ratings document, created by the members of the 3DPSIG, provides an updated reference for clinical standards of 3D printing for the care of patients with vascular conditions.
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Affiliation(s)
- Joonhyuk Lee
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | | | - Anish Ghodadra
- Department of Radiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Arafat Ali
- Department of Radiology, Henry Ford Health, Detroit, MI, USA
| | - Elsa M Arribas
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Leonid Chepelev
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Ciprian N Ionita
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
| | - Prashanth Ravi
- Department of Radiology, University of Cincinnati Medical Center, Cincinnati, OH, USA
| | - Justin R Ryan
- Webster Foundation 3D Innovations Lab, Rady Children's Hospital, San Diego, CA, USA
- Department of Neurological Surgery, University of California San Diego Health, San Diego, CA, USA
| | - Lumarie Santiago
- Department of Breast Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nicole Wake
- Department of Research and Scientific Affairs, GE HealthCare, New York, NY, USA
- Center for Advanced Imaging Innovation and Research, Department of Radiology, NYU Langone Health, New York, NY, USA
| | - Adnan M Sheikh
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - Frank J Rybicki
- Department of Radiology, University of Arizona - Phoenix, Phoenix, AZ, USA
| | - David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, Saint Louis, MO, USA.
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Paxton NC. Navigating the intersection of 3D printing, software regulation and quality control for point-of-care manufacturing of personalized anatomical models. 3D Print Med 2023; 9:9. [PMID: 37024730 PMCID: PMC10080800 DOI: 10.1186/s41205-023-00175-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
3D printing technology has become increasingly popular in healthcare settings, with applications of 3D printed anatomical models ranging from diagnostics and surgical planning to patient education. However, as the use of 3D printed anatomical models becomes more widespread, there is a growing need for regulation and quality control to ensure their accuracy and safety. This literature review examines the current state of 3D printing in hospitals and FDA regulation process for software intended for use in producing 3D printed models and provides for the first time a comprehensive list of approved software platforms alongside the 3D printers that have been validated with each for producing 3D printed anatomical models. The process for verification and validation of these 3D printed products, as well as the potential for inaccuracy in these models, is discussed, including methods for testing accuracy, limits, and standards for accuracy testing. This article emphasizes the importance of regulation and quality control in the use of 3D printing technology in healthcare, the need for clear guidelines and standards for both the software and the printed products to ensure the safety and accuracy of 3D printed anatomical models, and the opportunity to expand the library of regulated 3D printers.
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Affiliation(s)
- Naomi C Paxton
- Phil & Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, Eugene, OR, USA.
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Nguyen P, Stanislaus I, McGahon C, Pattabathula K, Bryant S, Pinto N, Jenkins J, Meinert C. Quality assurance in 3D-printing: A dimensional accuracy study of patient-specific 3D-printed vascular anatomical models. FRONTIERS IN MEDICAL TECHNOLOGY 2023; 5:1097850. [PMID: 36824261 PMCID: PMC9941637 DOI: 10.3389/fmedt.2023.1097850] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 01/03/2023] [Indexed: 02/10/2023] Open
Abstract
3D printing enables the rapid manufacture of patient-specific anatomical models that substantially improve patient consultation and offer unprecedented opportunities for surgical planning and training. However, the multistep preparation process may inadvertently lead to inaccurate anatomical representations which may impact clinical decision making detrimentally. Here, we investigated the dimensional accuracy of patient-specific vascular anatomical models manufactured via digital anatomical segmentation and Fused-Deposition Modelling (FDM), Stereolithography (SLA), Selective Laser Sintering (SLS), and PolyJet 3D printing, respectively. All printing modalities reliably produced hand-held patient-specific models of high quality. Quantitative assessment revealed an overall dimensional error of 0.20 ± 3.23%, 0.53 ± 3.16%, -0.11 ± 2.81% and -0.72 ± 2.72% for FDM, SLA, PolyJet and SLS printed models, respectively, compared to unmodified Computed Tomography Angiograms (CTAs) data. Comparison of digital 3D models to CTA data revealed an average relative dimensional error of -0.83 ± 2.13% resulting from digital anatomical segmentation and processing. Therefore, dimensional error resulting from the print modality alone were 0.76 ± 2.88%, + 0.90 ± 2.26%, + 1.62 ± 2.20% and +0.88 ± 1.97%, for FDM, SLA, PolyJet and SLS printed models, respectively. Impact on absolute measurements of feature size were minimal and assessment of relative error showed a propensity for models to be marginally underestimated. This study revealed a high level of dimensional accuracy of 3D-printed patient-specific vascular anatomical models, suggesting they meet the requirements to be used as medical devices for clinical applications.
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Affiliation(s)
- Philip Nguyen
- School of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Ivan Stanislaus
- Faculty of Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Clover McGahon
- Faculty of Engineering, Queensland University of Technology, Brisbane, QLD, Australia
| | - Krishna Pattabathula
- Vascular Surgery Department, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Services, Brisbane, QLD, Australia,Vascular Biofabrication Program, Herston Biofabrication Institute, Metro North Hospital and Health Services, Brisbane, QLD, Australia
| | - Samuel Bryant
- Vascular Surgery Department, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Services, Brisbane, QLD, Australia,Vascular Biofabrication Program, Herston Biofabrication Institute, Metro North Hospital and Health Services, Brisbane, QLD, Australia
| | - Nigel Pinto
- Vascular Surgery Department, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Services, Brisbane, QLD, Australia,Vascular Biofabrication Program, Herston Biofabrication Institute, Metro North Hospital and Health Services, Brisbane, QLD, Australia
| | - Jason Jenkins
- Vascular Surgery Department, Royal Brisbane and Women's Hospital, Metro North Hospital and Health Services, Brisbane, QLD, Australia,Vascular Biofabrication Program, Herston Biofabrication Institute, Metro North Hospital and Health Services, Brisbane, QLD, Australia
| | - Christoph Meinert
- Faculty of Engineering, Queensland University of Technology, Brisbane, QLD, Australia,Vascular Biofabrication Program, Herston Biofabrication Institute, Metro North Hospital and Health Services, Brisbane, QLD, Australia,Faculty of Engineering, Architecture and Information Technology, University of Queensland, Brisbane, QLD, Australia,Correspondence: Christoph Meinert
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10
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Wickramasinghe N, Thompson BR, Xiao J. The Opportunities and Challenges of Digital Anatomy for Medical Sciences: Narrative Review. JMIR MEDICAL EDUCATION 2022; 8:e34687. [PMID: 35594064 PMCID: PMC9166657 DOI: 10.2196/34687] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 01/23/2022] [Accepted: 03/25/2022] [Indexed: 05/09/2023]
Abstract
BACKGROUND Anatomy has been the cornerstone of medical education for centuries. However, given the advances in the Internet of Things, this landscape has been augmented in the past decade, shifting toward a greater focus on adopting digital technologies. Digital anatomy is emerging as a new discipline that represents an opportunity to embrace advances in digital health technologies and apply them to the domain of modern medical sciences. Notably, the use of augmented or mixed and virtual reality as well as mobile and platforms and 3D printing in modern anatomy has dramatically increased in the last 5 years. OBJECTIVE This review aims to outline the emerging area of digital anatomy and summarize opportunities and challenges for incorporating digital anatomy in medical science education and practices. METHODS Literature searches were performed using the PubMed, Embase, and MEDLINE bibliographic databases for research articles published between January 2005 and June 2021 (inclusive). Out of the 4650 articles, 651 (14%) were advanced to full-text screening and 77 (1.7%) were eligible for inclusion in the narrative review. We performed a Strength, Weakness, Opportunity, and Threat (SWOT) analysis to evaluate the role that digital anatomy plays in both the learning and teaching of medicine and health sciences as well as its practice. RESULTS Digital anatomy has not only revolutionized undergraduate anatomy education via 3D reconstruction of the human body but is shifting the paradigm of pre- and vocational training for medical professionals via digital simulation, advancing health care. Importantly, it was noted that digital anatomy not only benefits in situ real time clinical practice but also has many advantages for learning and teaching clinicians at multiple levels. Using the SWOT analysis, we described strengths and opportunities that together serve to underscore the benefits of embracing digital anatomy, in particular the areas for collaboration and medical advances. The SWOT analysis also identified a few weaknesses associated with digital anatomy, which are primarily related to the fact that the current reach and range of applications for digital anatomy are very limited owing to its nascent nature. Furthermore, threats are limited to technical aspects such as hardware and software issues. CONCLUSIONS This review highlights the advances in digital health and Health 4.0 in key areas of digital anatomy analytics. The continuous evolution of digital technologies will increase their ability to reinforce anatomy knowledge and advance clinical practice. However, digital anatomy education should not be viewed as a simple technical conversion and needs an explicit pedagogical framework. This review will be a valuable asset for educators and researchers to incorporate digital anatomy into the learning and teaching of medical sciences and their practice.
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Affiliation(s)
- Nilmini Wickramasinghe
- School of Health Sciences, Swinburne University of Technology, Victoria, Australia
- Epworth Healthcare, Melbourne, Australia
| | - Bruce R Thompson
- School of Health Sciences, Swinburne University of Technology, Victoria, Australia
- Alfred Health, Melbourne, Australia
- School of Health Sciences, University of Melbourne, Parkville, Australia
| | - Junhua Xiao
- School of Health Sciences, Swinburne University of Technology, Victoria, Australia
- School of Allied Health, La Trobe University, Bundoora, Australia
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11
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Rynio P, Wojtuń M, Wójcik Ł, Kawa M, Falkowski A, Gutowski P, Kazimierczak A. The accuracy and reliability of 3D printed aortic templates: a comprehensive three-dimensional analysis. Quant Imaging Med Surg 2022; 12:1385-1396. [PMID: 35111632 DOI: 10.21037/qims-21-529] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 10/13/2021] [Indexed: 12/21/2022]
Abstract
Background Advances in 3D printing technology allow us to continually find new medical applications. One of them is 3D printing of aortic templates to guide vascular surgeons or interventional radiologists to create fenestrations in the stent-graft surface for the implantation procedure called fenestrated endovascular aortic aneurysm repair. It is believed that the use of 3D printing significantly improves the quality of modified fenestrated stent-grafts. However, the accuracy and reliability of personalized 3D printed models of aortic templates are not well established. Methods Thirteen 3D printed templates of the visceral aorta and sixteen of the aortic arch and their corresponding computer tomography of angiography images were included in this accuracy study. The 3D models were scanned in the same conditions on computed tomography (CT) and evaluated by three physicians experienced in vascular CT assessment. Model and patient CT measurements were performed at key landmarks to maintain quality for stent-graft modification, including side branches and aortic diameters. CT-scanned aortic templates were segmented, aligned with sourced patient data, and evaluated for the Hausdorff matrix. Next, Bland-Altman plots determined the degree of agreement. Results The Intraclass Correlation Coefficients values were more than 0.9 for all measurements of aortic diameters and aortic branches diameter in all landmark locations. Therefore, the reliability of the aortic templates was considered excellent. The Bland-Altman plots analysis indicated measurement biases of 0.05 to 0.47 for aortic arch templates and 0.06 to 0.38 for reno-visceral aortic templates. The arithmetic mean of Hausdorff's mean distances of the aortic arch templates was 0.47 mm (SD =0.06) and ranged from 0.34 to 0.58. The mean metrics for abdominal models was 0.24 mm (SD =0.03) and ranged from 0.21 to 0.31. Conclusions The printed models of 3D aortic templates are accurate and reliable, thus can be widely used in endovascular surgery and interventional radiology departments as aortic templates to guide the physician-modified fenestrated stent-graft fabrication.
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Affiliation(s)
- Pawel Rynio
- Department of Vascular Surgery, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Maciej Wojtuń
- Department of Radiology, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Łukasz Wójcik
- Department of Radiology, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Miłosz Kawa
- Department of Radiology, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Aleksander Falkowski
- Department of Radiology, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Piotr Gutowski
- Department of Vascular Surgery, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Arkadiusz Kazimierczak
- Department of Vascular Surgery, Pomeranian Medical University in Szczecin, Szczecin, Poland
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12
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Hopfner C, Jakob A, Tengler A, Grab M, Thierfelder N, Brunner B, Thierij A, Haas NA. Design and 3D printing of variant pediatric heart models for training based on a single patient scan. 3D Print Med 2021; 7:25. [PMID: 34463879 PMCID: PMC8406574 DOI: 10.1186/s41205-021-00116-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 08/15/2021] [Indexed: 11/24/2022] Open
Abstract
Background 3D printed models of pediatric hearts with congenital heart disease have been proven helpful in simulation training of diagnostic and interventional catheterization. However, anatomically accurate 3D printed models are traditionally based on real scans of clinical patients requiring specific imaging techniques, i.e., CT or MRI. In small children both imaging technologies are rare as minimization of radiation and sedation is key. 3D sonography does not (yet) allow adequate imaging of the entire heart for 3D printing. Therefore, an alternative solution to create variant 3D printed heart models for teaching and hands-on training has been established. Methods In this study different methods utilizing image processing and computer aided design software have been established to overcome this shortage and to allow unlimited variations of 3D heart models based on single patient scans. Patient-specific models based on a CT or MRI image stack were digitally modified to alter the original shape and structure of the heart. Thereby, 3D hearts showing various pathologies were created. Training models were adapted to training level and aims of hands-on workshops, particularly for interventional cardiology. Results By changing the shape and structure of the original anatomy, various training models were created of which four examples are presented in this paper: 1. Design of perimembranous and muscular ventricular septal defect on a heart model with patent ductus arteriosus, 2. Series of heart models with atrial septal defect showing the long-term hemodynamic effect of the congenital heart defect on the right atrial and ventricular wall, 3. Implementation of simplified heart valves and addition of the myocardium to a right heart model with pulmonary valve stenosis, 4. Integration of a constructed 3D model of the aortic valve into a pulsatile left heart model with coarctation of the aorta. All presented models have been successfully utilized and evaluated in teaching or hands-on training courses. Conclusions It has been demonstrated that non-patient-specific anatomical variants can be created by modifying existing patient-specific 3D heart models. This way, a range of pathologies can be modeled based on a single CT or MRI dataset. Benefits of designed 3D models for education and training purposes have been successfully applied in pediatric cardiology but can potentially be transferred to simulation training in other medical fields as well.
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Affiliation(s)
- Carina Hopfner
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany.
| | - Andre Jakob
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Anja Tengler
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Maximilian Grab
- Department of Cardiac Surgery, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Nikolaus Thierfelder
- Department of Cardiac Surgery, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Barbara Brunner
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Alisa Thierij
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
| | - Nikolaus A Haas
- Department of Pediatric Cardiology and Pediatric Intensive Care, LMU Klinikum, Campus Großhadern, Marchioninistr. 15, 81377, Munich, Germany
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