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3D printing for heart valve disease: a systematic review
BACKGROUND: Current developments showed a fast-increasing implementation and use of three-dimensional (3D) printing in medical applications. Our aim was to review the literature regarding the application of 3D printing to cardiac valve disease. METHODS: A PubMed search for publications in English wi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377684/ https://www.ncbi.nlm.nih.gov/pubmed/30771098 http://dx.doi.org/10.1186/s41747-018-0083-0 |
Sumario: | BACKGROUND: Current developments showed a fast-increasing implementation and use of three-dimensional (3D) printing in medical applications. Our aim was to review the literature regarding the application of 3D printing to cardiac valve disease. METHODS: A PubMed search for publications in English with the terms “3D printing” AND “cardiac valve”, performed in January 2018, resulted in 64 items. After the analysis of the abstract and text, 27 remained related to the topic. From the references of these 27 papers, 7 papers were added resulting in a total of 34 papers. Of these, 5 were review papers, thus reducing the papers taken into consideration to 29. RESULTS: The 29 papers showed that about a decade ago, the interest in 3D printing for this application area was emerging, but only in the past 2 to 3 years it really gained interest. Computed tomography is the most common imaging modality taken into consideration (62%), followed by ultrasound (28%), computer-generated models (computer-aided design) (7%), and magnetic resonance imaging (3%). Acrylonitrile butadiene styrene (4/14, 29%) and TangoPlus FullCure 930 (5/14, 36%) are the most used printing materials. Stereolithography (40%) and fused deposition modeling (30%) are the preferred printing techniques, while PolyJet (25%) and laser sintering (4%) are used in a minority of cases. The reported time ranges from 30 min to 3 days. The most reported application area is preoperative planning (63%), followed by training (19%), device testing (11%), and retrospective procedure evaluation (7%). CONCLUSIONS: In most cases, CT datasets are used and models are printed for preoperative planning. |
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