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Chytas D, Noussios G, Salmas M, Demesticha T, Vasiliadis AV, Troupis T. The effectiveness of three-dimensional printing in undergraduate and postgraduate anatomy education: A review of reviews. Morphologie 2024; 108:100759. [PMID: 38215686 DOI: 10.1016/j.morpho.2023.100759] [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: 10/30/2023] [Revised: 12/09/2023] [Accepted: 12/12/2023] [Indexed: 01/14/2024]
Abstract
PURPOSE Several reviews and meta-analyses about the value of three-dimensional (3D) printing in anatomy education have been published in the last years, with variable-and sometimes confusing- outcomes. We performed a review of those reviews, in order to shed light on the results concerning the effectiveness of 3D printing in anatomy education, compared to specific traditional methods and other technologies. METHODS The electronic databases PubMed, ERIC and Cochrane library were searched for reviews or meta-analyses with purpose to investigate the effectiveness of 3D printing in undergraduate and postgraduate anatomy education. RESULTS Seven papers were included: four systematic reviews with meta-analysis, one narrative, one scoping and one systematic review. Overall, it has been shown that 3D printing is more effective than two-dimensional (2D) images for undergraduate health science students, but not for medical residents. Also, it seems to be more effective than 2D methods for teaching anatomy of some relatively complex structures, such as the nervous system. However, there is generally lack of evidence about the effectiveness of 3D printing in comparison with other 3D visualization methods. CONCLUSIONS For students, the effectiveness of 3D printing in anatomy education is higher than 2D methods. There is need for studies to investigate the effectiveness of 3D printing in comparison with other 3D visualization methods, such as cadaveric dissection, prosection and virtual reality. There is also need for research to explore if 3D printing is effective as a supplementary tool in a blended anatomy learning approach.
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Affiliation(s)
- D Chytas
- Department of Physiotherapy, Basic Sciences Laboratory, University of Peloponnese, 20, Plateon Street, 23100 Sparta, Greece; European University of Cyprus, 6, Diogenous Street, 2404 Engomi, Nicosia, Cyprus.
| | - G Noussios
- Department of Physical Education and Sports Sciences of Serres, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
| | - M Salmas
- Department of Anatomy, School of Medicine, National and Kapodistrian University of Athens, 75, Mikras Asias Street, 11527 Athens, Greece
| | - T Demesticha
- Department of Anatomy, School of Medicine, National and Kapodistrian University of Athens, 75, Mikras Asias Street, 11527 Athens, Greece
| | - A V Vasiliadis
- Department of Orthopaedic Surgery, Sports Trauma Unit, St. Luke's Hospital, Panorama, 55236 Thessaloniki, Greece
| | - T Troupis
- Department of Anatomy, School of Medicine, National and Kapodistrian University of Athens, 75, Mikras Asias Street, 11527 Athens, Greece
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SUN ZH. Cardiovascular computed tomography in cardiovascular disease: An overview of its applications from diagnosis to prediction. J Geriatr Cardiol 2024; 21:550-576. [PMID: 38948894 PMCID: PMC11211902 DOI: 10.26599/1671-5411.2024.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
Cardiovascular computed tomography angiography (CTA) is a widely used imaging modality in the diagnosis of cardiovascular disease. Advancements in CT imaging technology have further advanced its applications from high diagnostic value to minimising radiation exposure to patients. In addition to the standard application of assessing vascular lumen changes, CTA-derived applications including 3D printed personalised models, 3D visualisations such as virtual endoscopy, virtual reality, augmented reality and mixed reality, as well as CT-derived hemodynamic flow analysis and fractional flow reserve (FFRCT) greatly enhance the diagnostic performance of CTA in cardiovascular disease. The widespread application of artificial intelligence in medicine also significantly contributes to the clinical value of CTA in cardiovascular disease. Clinical value of CTA has extended from the initial diagnosis to identification of vulnerable lesions, and prediction of disease extent, hence improving patient care and management. In this review article, as an active researcher in cardiovascular imaging for more than 20 years, I will provide an overview of cardiovascular CTA in cardiovascular disease. It is expected that this review will provide readers with an update of CTA applications, from the initial lumen assessment to recent developments utilising latest novel imaging and visualisation technologies. It will serve as a useful resource for researchers and clinicians to judiciously use the cardiovascular CT in clinical practice.
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Affiliation(s)
- Zhong-Hua SUN
- Discipline of Medical Radiation Science, Curtin Medical School, Curtin University, Perth, Australia
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth 6012, Australia
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Sun Z, Silberstein J, Vaccarezza M. Cardiovascular Computed Tomography in the Diagnosis of Cardiovascular Disease: Beyond Lumen Assessment. J Cardiovasc Dev Dis 2024; 11:22. [PMID: 38248892 PMCID: PMC10816599 DOI: 10.3390/jcdd11010022] [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: 11/22/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 01/23/2024] Open
Abstract
Cardiovascular CT is being widely used in the diagnosis of cardiovascular disease due to the rapid technological advancements in CT scanning techniques. These advancements include the development of multi-slice CT, from early generation to the latest models, which has the capability of acquiring images with high spatial and temporal resolution. The recent emergence of photon-counting CT has further enhanced CT performance in clinical applications, providing improved spatial and contrast resolution. CT-derived fractional flow reserve is superior to standard CT-based anatomical assessment for the detection of lesion-specific myocardial ischemia. CT-derived 3D-printed patient-specific models are also superior to standard CT, offering advantages in terms of educational value, surgical planning, and the simulation of cardiovascular disease treatment, as well as enhancing doctor-patient communication. Three-dimensional visualization tools including virtual reality, augmented reality, and mixed reality are further advancing the clinical value of cardiovascular CT in cardiovascular disease. With the widespread use of artificial intelligence, machine learning, and deep learning in cardiovascular disease, the diagnostic performance of cardiovascular CT has significantly improved, with promising results being presented in terms of both disease diagnosis and prediction. This review article provides an overview of the applications of cardiovascular CT, covering its performance from the perspective of its diagnostic value based on traditional lumen assessment to the identification of vulnerable lesions for the prediction of disease outcomes with the use of these advanced technologies. The limitations and future prospects of these technologies are also discussed.
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Affiliation(s)
- Zhonghua Sun
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
| | - Jenna Silberstein
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
| | - Mauro Vaccarezza
- Curtin Medical School, Curtin University, Perth, WA 6102, Australia; (J.S.); (M.V.)
- Curtin Health Innovation Research Institute (CHIRI), Curtin University, Perth, WA 6102, Australia
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Shabbak A, Masoumkhani F, Fallah A, Amani-Beni R, Mohammadpour H, Shahbazi T, Bakhshi A. 3D Printing for Cardiovascular Surgery and Intervention: A Review Article. Curr Probl Cardiol 2024; 49:102086. [PMID: 37716537 DOI: 10.1016/j.cpcardiol.2023.102086] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/18/2023]
Abstract
3D printing technology can be applied to practically every aspect of modern life, fulfilling the needs of people from various backgrounds. The utilization of 3D printing in the context of adult heart disease can be succinctly categorized into 3 primary domains: preoperative strategizing or simulation, medical instruction, and clinical consultations. 3D-printed model utilization improves surgical planning and intraoperative decision-making and minimizes surgical risks, and it has demonstrated its efficacy as an innovative educational tool for aspiring surgeons with limited practical exposure. Despite all the applications of 3D printing, it has not yet been shown to improve long-term outcomes, including safety. There are no data on the outcomes of controlled trials available. To appropriately diagnose heart disease, 3D-printed models of the heart can provide a better understanding of the intracardiac anatomy and provide all the information needed for operative planning. Experientially, 3D printing provides a wide range of perceptions for understanding lower extremity arteries' spatial geometry and anatomical features of pathology. Practicing cardiac surgery processes using objects printed using 3D imaging data can become the norm rather than the exception, leading to improved accuracy and quality of treatment. This study aimed to review the various applications of 3D printing technology in cardiac surgery and intervention.
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Affiliation(s)
- Ali Shabbak
- Research Committee, School of Medicine, Guilan University of Medical Science, Rasht, Iran
| | - Fateme Masoumkhani
- Department of cardiology, Mousavi Hospital, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Amir Fallah
- Research Committee, School of Medicine, Guilan University of Medical Science, Rasht, Iran
| | - Reza Amani-Beni
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Hanieh Mohammadpour
- Research Committee, School of Medicine, Guilan University of Medical Science, Rasht, Iran
| | - Taha Shahbazi
- Neurosurgery Research Group (NRG), Student Research Committee, Hamadan University of Medical Sciences, Hamadan, Iran
| | - Arash Bakhshi
- Remember of Research Committee, School of Medicine, Guilan University of Medical Sciences, Rasht, Iran.
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Zamponi M, Mollica PA, Khodour Y, Bjerring JS, Bruno RD, Sachs PC. Combined 3D bioprinting and tissue-specific ECM system reveals the influence of brain matrix on stem cell differentiation. Front Cell Dev Biol 2023; 11:1258993. [PMID: 37928905 PMCID: PMC10623327 DOI: 10.3389/fcell.2023.1258993] [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: 07/14/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
We have previously shown that human and murine breast extracellular matrix (ECM) can significantly impact cellular behavior, including stem cell fate determination. It has been established that tissue-specific extracellular matrix from the central nervous system has the capacity to support neuronal survival. However, the characterization of its influence on stem cell differentiation and its adaptation to robust 3D culture models is underdeveloped. To address these issues, we combined our 3D bioprinter with hydrogels containing porcine brain extracellular matrix (BMX) to test the influence of the extracellular matrix on stem cell differentiation. Our 3D bioprinting system generated reproducible 3D neural structures derived from mouse embryonic stem cells (mESCs). We demonstrate that the addition of BMX preferentially influences 3D bioprinted mESCs towards neural lineages compared to standard basement membrane (Geltrex/Matrigel) hydrogels alone. Furthermore, we demonstrate that we can transplant these 3D bioprinted neural cellular structures into a mouse's cleared mammary fat pad, where they continue to grow into larger neural outgrowths. Finally, we demonstrate that direct injection of human induced pluripotent stem cells (hiPSCS) and neural stem cells (NSCs) suspended in pure BMX formed neural structures in vivo. Combined, these findings describe a unique system for studying brain ECM/stem cell interactions and demonstrate that BMX can direct pluripotent stem cells to differentiate down a neural cellular lineage without any additional specific differentiation stimuli.
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Affiliation(s)
- Martina Zamponi
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
| | - Peter A. Mollica
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
| | - Yara Khodour
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
| | - Julie S. Bjerring
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
| | - Robert D. Bruno
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
| | - Patrick C. Sachs
- School of Medical Diagnostic and Translational Sciences, College of Health Sciences, Old Dominion University, Norfolk, VA, United States
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