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Ford JM, Rybicki FJ, Morris JM, Decker SJ. Stratifying complexity among the widespread use of 3D printing in United States health care facilities. 3D Print Med 2024; 10:37. [PMID: 39565493 PMCID: PMC11577914 DOI: 10.1186/s41205-024-00243-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Accepted: 11/05/2024] [Indexed: 11/21/2024] Open
Affiliation(s)
- Jonathan M Ford
- Department of Radiology, Keck School of Medicine of the University of Southern California, 1975 Zonal Avenue Suite B22, Los Angeles, CA, 90033, USA
| | - Frank J Rybicki
- Department of Radiology, University of Arizona College of Medicine - Phoenix, 475 N 5th Street, Phoenix, AZ, 85004, USA
- Department of Medical Imaging, Banner University Medical Center - Phoenix, 1111 E McDowell Road, Phoenix, AZ, 85006, USA
| | - Jonathan M Morris
- Department of Radiology, Mayo Clinic, Mayo Building West, 2nd Floor, 200 First St. SW, Rochester, MN, 55905, USA
| | - Summer J Decker
- Department of Radiology, Keck School of Medicine of the University of Southern California, 1975 Zonal Avenue Suite B22, Los Angeles, CA, 90033, USA.
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2
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Wang KC, Ryan JR, Chepelev L, Wake N, Quigley EP, Santiago L, Wentworth A, Alexander A, Morris JM, Fleischmann D, Ballard DH, Ravi P, Hirsch JD, Sturgeon GM, Huang YH, Decker SJ, von Windheim N, Pugliese RS, Hidalgo RV, Patel P, Colon J, Thieringer FM, Rybicki FJ. Demographics, Utilization, Workflow, and Outcomes Based on Observational Data From the RSNA-ACR 3D Printing Registry. J Am Coll Radiol 2024; 21:1781-1791. [PMID: 39117182 DOI: 10.1016/j.jacr.2024.07.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 07/23/2024] [Accepted: 07/24/2024] [Indexed: 08/10/2024]
Abstract
PURPOSE The aim of this study was to report data from the first 3 years of operation of the RSNA-ACR 3D Printing Registry. METHODS Data from June 2020 to June 2023 were extracted, including demographics, indications, workflow, and user assessments. Clinical indications were stratified by 12 organ systems. Imaging modalities, printing technologies, and numbers of parts per case were assessed. Effort data were analyzed, dividing staff members into provider and nonprovider categories. The opinions of clinical users were evaluated using a Likert scale questionnaire, and estimates of procedure time saved were collected. RESULTS A total of 20 sites and 2,637 cases were included, consisting of 1,863 anatomic models and 774 anatomic guides. Mean patient ages for models and guides were 42.4 ± 24.5 years and 56.3 ± 18.5 years, respectively. Cardiac models were the most common type of model (27.2%), and neurologic guides were the most common type of guide (42.4%). Material jetting, vat photopolymerization, and material extrusion were the most common printing technologies used overall (85.6% of all cases). On average, providers spent 92.4 min and nonproviders spent 335.0 min per case. Providers spent most time on consultation (33.6 min), while nonproviders focused most on segmentation (148.0 min). Confidence in treatment plans increased after using 3-D printing (P < .001). Estimated procedure time savings for 155 cases was 40.5 ± 26.1 min. CONCLUSIONS Three-dimensional printing is performed at health care facilities for many clinical indications. The registry provides insight into the technologies and workflows used to create anatomic models and guides, and the data show clinical benefits from 3-D printing.
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Affiliation(s)
- Kenneth C Wang
- Imaging Service, Baltimore VA Medical Center, Baltimore, Maryland; Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland; and Co-chair, 3D Printing Registry Committee, American College of Radiology.
| | - Justin R Ryan
- 3D Innovations Lab, Rady Children's Hospital, San Diego, California; and Department of Neurological Surgery, University of California San Diego Health, San Diego, California
| | - Leonid Chepelev
- Joint Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Nicole Wake
- Director, Department of Research and Scientific Affairs, GE Healthcare, New York, New York; and Department of Radiology, NYU Grossman School of Medicine, New York, New York. https://twitter.com/Wake_Imaging
| | - Edward P Quigley
- Department of Radiology and Imaging Sciences, University of Utah School of Medicine, Salt Lake City, Utah
| | - Lumarie Santiago
- Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas. https://twitter.com/LumarieSantiago
| | - Adam Wentworth
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Amy Alexander
- Division of Engineering, Mayo Clinic, Rochester, Minnesota. https://twitter.com/AmyAlexanderMC
| | - Jonathan M Morris
- Department of Radiology, Mayo Clinic, Rochester, Minnesota; Leadership roles: Executive Medical Director, Immersive and Experiential Learning, Mayo Clinic; Medical Director, Anatomic Modeling Unit, Mayo Clinic; and Medical Director, Biomedical and Scientific Visualization, Mayo Clinic
| | - Dominik Fleischmann
- Department of Radiology, Stanford University School of Medicine, Palo Alto, California; Director, Computed Tomography, Stanford University; Chief, Cardiovascular Imaging, Stanford University; and Medical Director, 3DQ Lab, Stanford University
| | - David H Ballard
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri. https://twitter.com/DavidBallardMD
| | - Prashanth Ravi
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Jeffrey D Hirsch
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Gregory M Sturgeon
- Duke Children's Pediatric and Congenital Heart Center, Durham, North Carolina
| | - Yu-Hui Huang
- Department of Radiology, University of Minnesota, Minneapolis, Minnesota. https://twitter.com/yuhuihuang
| | - Summer J Decker
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California; Department of Radiology, University of South Florida, Morsani College of Medicine, Tampa, Florida; and Director, Center for Advanced Visualization Technologies in Medicine, University of Southern California
| | - Natalia von Windheim
- Department of Otolaryngology-Head and Neck Surgery, The Ohio State University, Columbus, Ohio; and KLS Martin, Jacksonville, Florida
| | - Robert S Pugliese
- Health Design Lab, Thomas Jefferson University, Philadelphia, Pennsylvania. https://twitter.com/RSPugliese
| | - Ronald V Hidalgo
- Imagineering Lab, Southern Illinois University School of Medicine, Springfield, Illinois; and Department of Radiology, Springfield Clinic, Springfield, Illinois
| | | | - Joseb Colon
- Atrium Health Levine Children's HEARTest Yard Congenital Heart Center, Charlotte, North Carolina
| | - Florian M Thieringer
- Chair, Department of Oral and Cranio-Maxillofacial Surgery, and 3D Print Lab, University Hospital Basel, Basel, Switzerland; and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frank J Rybicki
- Chair, Department of Radiology, University of Arizona College of Medicine, Phoenix, Arizona; Department of Radiology, Banner University Medical Group, Phoenix, Arizona; and Co-chair, 3D Printing Registry Committee, American College of Radiology. https://twitter.com/FrankRybicki
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Fidvi S, Holder J, Li H, Parnes GJ, Shamir SB, Wake N. Advanced 3D Visualization and 3D Printing in Radiology. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1406:103-138. [PMID: 37016113 DOI: 10.1007/978-3-031-26462-7_6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
Since the discovery of X-rays in 1895, medical imaging systems have played a crucial role in medicine by permitting the visualization of internal structures and understanding the function of organ systems. Traditional imaging modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound (US) present fixed two-dimensional (2D) images which are difficult to conceptualize complex anatomy. Advanced volumetric medical imaging allows for three-dimensional (3D) image post-processing and image segmentation to be performed, enabling the creation of 3D volume renderings and enhanced visualization of pertinent anatomic structures in 3D. Furthermore, 3D imaging is used to generate 3D printed models and extended reality (augmented reality and virtual reality) models. A 3D image translates medical imaging information into a visual story rendering complex data and abstract ideas into an easily understood and tangible concept. Clinicians use 3D models to comprehend complex anatomical structures and to plan and guide surgical interventions more precisely. This chapter will review the volumetric radiological techniques that are commonly utilized for advanced 3D visualization. It will also provide examples of 3D printing and extended reality technology applications in radiology and describe the positive impact of advanced radiological image visualization on patient care.
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Affiliation(s)
- Shabnam Fidvi
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA.
| | - Justin Holder
- Department of Radiology, Montefiore Medical Center, Bronx, NY, USA
| | - Hong Li
- Department of Radiology, Jacobi Medical Center, Bronx, NY, USA
| | | | | | - Nicole Wake
- GE Healthcare, Aurora, OH, USA
- Center for Advanced Imaging Innovation and Research, NYU Langone Health, New York, NY, USA
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Ganapathy A, Chen D, Elumalai A, Albers B, Tappa K, Jammalamadaka U, Hoegger MJ, Ballard DH. Guide for starting or optimizing a 3D printing clinical service. Methods 2022; 206:41-52. [PMID: 35964862 DOI: 10.1016/j.ymeth.2022.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 10/15/2022] Open
Abstract
Three-dimensional (3D) printing has applications in many fields and has gained substantial traction in medicine as a modality to transform two-dimensional scans into three-dimensional renderings. Patient-specific 3D printed models have direct patient care uses in surgical and procedural specialties, allowing for increased precision and accuracy in developing treatment plans and guiding surgeries. Medical applications include surgical planning, surgical guides, patient and trainee education, and implant fabrication. 3D printing workflow for a laboratory or clinical service that produces anatomic models and guides includes optimizing imaging acquisition and post-processing, segmenting the imaging, and printing the model. Quality assurance considerations include supervising medical imaging expert radiologists' guidance and self-implementing in-house quality control programs. The purpose of this review is to provide a workflow and guide for starting or optimizing laboratories and clinical services that 3D-print anatomic models or guides for clinical use.
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Affiliation(s)
- Aravinda Ganapathy
- School of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
| | - David Chen
- School of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
| | - Anusha Elumalai
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Brian Albers
- 3D Printing Center, Barnes Jewish Hospital, St. Louis, MO, USA.
| | - Karthik Tappa
- Anatomic 3D Printing and Visualization Program, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | | | - Mark J Hoegger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA.
| | - David H Ballard
- School of Medicine, Washington University School of Medicine, St. Louis, MO, USA.
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5
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DeCampos D, Teixeira R, Saleiro C, Oliveira-Santos M, Paiva L, Costa M, Botelho A, Gonçalves L. 3D printing for left atrial appendage closure: A meta-analysis and systematic review. Int J Cardiol 2022; 356:38-43. [PMID: 35358638 DOI: 10.1016/j.ijcard.2022.03.042] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/15/2022] [Accepted: 03/18/2022] [Indexed: 01/03/2023]
Abstract
BACKGROUND Three-dimensional printing (3D) has emerged as an alternative to imaging to guide left atrial appendage closure (LAAC) device sizing. AIMS We assessed the usefulness of 3D printing compared to a standard imaging-only approach for LAAC. METHODS We identified studies comparing an imaging-only with a 3D printing approach in LAAC. A fixed-effects meta-analysis was performed targeting a co-primary endpoint of disagreement in device sizing and leaks. RESULTS Eight studies that assigned 283 participants to an imaging-only approach and 3D printing approach (145 patients) were included. 3D printing significantly reduced the risk of the co-primary endpoint (risk raio (RR) = 0.19; 95% confidence interval (CI) 0.09-0.37), with consistency across the studies (I2 = 0%). Individually, both device size disagreements [RR 0.13 (95% CI 0.06-0.29), P < 0.001] and leaks [RR 0.24 (95% CI 0.09-0.64) P = 0.004] were reduced under a 3D printing modeling strategy. CONCLUSION Compared with an imaging-only strategy, 3D printing is associated with reduction in device size disagreements and leaks.
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Affiliation(s)
- Diana DeCampos
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal.
| | - Rogério Teixeira
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal; Faculdade de Medicina da Universidade de Coimbra, R. Larga 2, Diana de Campos, 3000-370 Coimbra. Portugal
| | - Carolina Saleiro
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal
| | - Manuel Oliveira-Santos
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal
| | - Luis Paiva
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal
| | - Marco Costa
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal
| | - Ana Botelho
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal
| | - Lino Gonçalves
- Centro Hospitalar e Universitário de Coimbra - Hospital Geral, Quinta dos Vales, São Martinho do Bispo 108, 3041-801 Coimbra, Portugal; Faculdade de Medicina da Universidade de Coimbra, R. Larga 2, Diana de Campos, 3000-370 Coimbra. Portugal
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6
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Mao Y, Liu Y, Ma Y, Jin P, Li L, Yang J. Mitral Valve-in-Valve Implant of a Balloon-Expandable Valve Guided by 3-Dimensional Printing. Front Cardiovasc Med 2022; 9:894160. [PMID: 35711355 PMCID: PMC9195497 DOI: 10.3389/fcvm.2022.894160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 05/03/2022] [Indexed: 11/27/2022] Open
Abstract
Background Our goal was to explore the role of 3-dimensional (3D) printing in facilitating the outcome of a mitral valve-in-valve (V-in-V) implant of a balloon-expandable valve. Methods From November 2020 to April 2021, 6 patients with degenerated mitral valves were treated by a transcatheter mitral V-in-V implant of a balloon-expandable valve. 3D printed mitral valve pre- and post-procedure models were prepared to facilitate the process by making individualized plans and evaluating the outcomes. Results Each of the 6 patients was successfully implanted with a balloon-expandable valve. From post-procedural images and the 3D printed models, we could clearly observe the valve at the ideal position, with the proper shape and no regurgitation. 3D printed mitral valve models contributed to precise decisions, the avoidance of complications, and the valuation of outcomes. Conclusions 3D printing plays an important role in guiding the transcatheter mitral V-in-V implant of a balloon-expandable valve. Clinical Trial Registration ClinicalTrials.gov Protocol Registration System (NCT02917980).
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Affiliation(s)
| | | | | | | | | | - Jian Yang
- Department of Cardiovascular Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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Bastawrous S, Wu L, Liacouras PC, Levin DB, Ahmed MT, Strzelecki B, Amendola MF, Lee JT, Coburn J, Ripley B. Establishing 3D Printing at the Point of Care: Basic Principles and Tools for Success. Radiographics 2022; 42:451-468. [PMID: 35119967 DOI: 10.1148/rg.210113] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
As the medical applications of three-dimensional (3D) printing increase, so does the number of health care organizations in which adoption or expansion of 3D printing facilities is under consideration. With recent advancements in 3D printing technology, medical practitioners have embraced this powerful tool to help them to deliver high-quality patient care, with a focus on sustainability. The use of 3D printing in the hospital or clinic at the point of care (POC) has profound potential, but its adoption is not without unanticipated challenges and considerations. The authors provide the basic principles and considerations for building the infrastructure to support 3D printing inside the hospital. This process includes building a business case; determining the requirements for facilities, space, and staff; designing a digital workflow; and considering how electronic health records may have a role in the future. The authors also discuss the supported applications and benefits of medical 3D printing and briefly highlight quality and regulatory considerations. The information presented is meant to be a practical guide to assist radiology departments in exploring the possibilities of POC 3D printing and expanding it from a niche application to a fixture of clinical care. An invited commentary by Ballard is available online. ©RSNA, 2022.
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Affiliation(s)
- Sarah Bastawrous
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Lei Wu
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Peter C Liacouras
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Dmitry B Levin
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Mohamed Tarek Ahmed
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Brian Strzelecki
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Michael F Amendola
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - James T Lee
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - James Coburn
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
| | - Beth Ripley
- Department of Radiology (S.B., L.W., B.R.) and Department of Medicine, Division of Cardiology (D.B.L.), University of Washington School of Medicine, Seattle, Wash; Departments of Radiology (S.B., L.W., B.R.) and Research and Development (B.S.), VA Puget Sound Health Care System, Mailbox S-114, Radiology, 1660 S Columbian Way, Seattle, WA 98108-1597; 3D Medical Applications Center, Walter Reed National Military Medical Center, Bethesda, Md (P.C.L.); Department of Radiology, University of Kentucky College of Medicine, Lexington, Ky (M.T.A., J.T.L.); Department of Surgery, Division of Vascular Surgery, Surgical Services (112), Virginia Commonwealth University School of Medicine, Richmond, Va (M.F.A.); and Department of Bioengineering, University of Maryland, College Park, Md (J.C.)
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8
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Gillett D, Bashari W, Senanayake R, Marsden D, Koulouri O, MacFarlane J, van der Meulen M, Powlson AS, Mendichovszky IA, Cheow H, Bird N, Kolias A, Mannion R, Gurnell M. Methods of 3D printing models of pituitary tumors. 3D Print Med 2021; 7:24. [PMID: 34462823 PMCID: PMC8406959 DOI: 10.1186/s41205-021-00118-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/15/2021] [Indexed: 12/21/2022] Open
Abstract
Background Pituitary adenomas can give rise to a variety of clinical disorders and surgery is often the primary treatment option. However, preoperative magnetic resonance imaging (MRI) does not always reliably identify the site of an adenoma. In this setting molecular (functional) imaging (e.g. 11C-methionine PET/CT) may help with tumor localisation, although interpretation of these 2D images can be challenging. 3D printing of anatomicalal models for other indications has been shown to aid surgical planning and improve patient understanding of the planned procedure. Here, we explore the potential utility of four types of 3D printing using PET/CT and co-registered MRI for visualising pituitary adenomas. Methods A 3D patient-specific model based on a challenging clinical case was created by segmenting the pituitary gland, pituitary adenoma, carotid arteries and bone using contemporary PET/CT and MR images. The 3D anatomical models were printed using VP, MEX, MJ and PBF 3D printing methods. Different anatomicalal structures were printed in color with the exception of the PBF anatomical model where a single color was used. The anatomical models were compared against the computer model to assess printing accuracy. Three groups of clinicians (endocrinologists, neurosurgeons and ENT surgeons) assessed the anatomical models for their potential clinical utility. Results All of the printing techniques produced anatomical models which were spatially accurate, with the commercial printing techniques (MJ and PBF) and the consumer printing techniques (VP and MEX) demonstrating comparable findings (all techniques had mean spatial differences from the computer model of < 0.6 mm). The MJ, VP and MEX printing techniques yielded multicolored anatomical models, which the clinicians unanimously agreed would be preferable to use when talking to a patient; in contrast, 50%, 40% and 0% of endocrinologists, neurosurgeons and ENT surgeons respectively would consider using the PBF model. Conclusion 3D anatomical models of pituitary tumors were successfully created from PET/CT and MRI using four different 3D printing techniques. However, the expert reviewers unanimously preferred the multicolor prints. Importantly, the consumer printers performed comparably to the commercial MJ printing technique, opening the possibility that these methods can be adopted into routine clinical practice with only a modest investment.
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Affiliation(s)
- Daniel Gillett
- Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK. .,Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK.
| | - Waiel Bashari
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Russell Senanayake
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Daniel Marsden
- Clinical Engineering, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Olympia Koulouri
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - James MacFarlane
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Merel van der Meulen
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew S Powlson
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Iosif A Mendichovszky
- Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK.,Department of Radiology, University of Cambridge, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Heok Cheow
- Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Nick Bird
- Department of Nuclear Medicine, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK
| | - Angelos Kolias
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge & Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Richard Mannion
- Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge & Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK
| | - Mark Gurnell
- Cambridge Endocrine Molecular Imaging Group, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, Biomedical Campus, Hills Road, Cambridge, CB2 0QQ, UK.,Metabolic Research Laboratories, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, National Institute for Health Research, Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
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9
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Talanki VR, Peng Q, Shamir SB, Baete SH, Duong TQ, Wake N. Three-Dimensional Printed Anatomic Models Derived From Magnetic Resonance Imaging Data: Current State and Image Acquisition Recommendations for Appropriate Clinical Scenarios. J Magn Reson Imaging 2021; 55:1060-1081. [PMID: 34046959 DOI: 10.1002/jmri.27744] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2020] [Revised: 05/08/2021] [Accepted: 05/10/2021] [Indexed: 12/18/2022] Open
Abstract
Three-dimensional (3D) printing technologies have been increasingly utilized in medicine over the past several years and can greatly facilitate surgical planning thereby improving patient outcomes. Although still much less utilized compared to computed tomography (CT), magnetic resonance imaging (MRI) is gaining traction in medical 3D printing. The purpose of this study was two-fold: 1) to determine the prevalence in the existing literature of using MRI to create 3D printed anatomic models for surgical planning and 2) to provide image acquisition recommendations for appropriate clinical scenarios where MRI is the most suitable imaging modality. The workflow for creating 3D printed anatomic models from medical imaging data is complex and involves image segmentation of the regions of interest and conversion of that data into 3D surface meshes, which are compatible with printing technologies. CT is most commonly used to create 3D printed anatomic models due to the high image quality and relative ease of performing image segmentation from CT data. As compared to CT datasets, 3D printing using MRI data offers advantages since it provides exquisite soft tissue contrast needed for accurate organ segmentation and it does not expose patients to unnecessary ionizing radiation. MRI, however, often requires complicated imaging techniques and time-consuming postprocessing procedures to generate high-resolution 3D anatomic models needed for 3D printing. Despite these challenges, 3D modeling and printing from MRI data holds great clinical promises thanks to emerging innovations in both advanced MRI imaging and postprocessing techniques. EVIDENCE LEVEL: 2 TECHNICAL EFFICATCY: 5.
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Affiliation(s)
- Varsha R Talanki
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Qi Peng
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Stephanie B Shamir
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Steven H Baete
- Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York, USA
| | - Timothy Q Duong
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA
| | - Nicole Wake
- Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.,Center for Advanced Imaging Innovation and Research (CAI2R) and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, NYU Grossman School of Medicine, New York, New York, USA
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