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Three-Dimensional Printed Anatomic Models Derived From Magnetic Resonance Imaging Data: Current State and Image Acquisition Recommendations for Appropriate Clinical Scenarios.
Talanki, Varsha R; Peng, Qi; Shamir, Stephanie B; Baete, Steven H; Duong, Timothy Q; Wake, Nicole.
Afiliación
  • Talanki VR; Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.
  • Peng Q; Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.
  • Shamir SB; Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.
  • Baete SH; 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.
  • Duong TQ; Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.
  • Wake N; Department of Radiology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, USA.
J Magn Reson Imaging ; 55(4): 1060-1081, 2022 Apr.
Article en En | MEDLINE | ID: mdl-34046959
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagenología Tridimensional / Modelos Anatómicos Tipo de estudio: Guideline / Risk_factors_studies Límite: Humans Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Imagenología Tridimensional / Modelos Anatómicos Tipo de estudio: Guideline / Risk_factors_studies Límite: Humans Idioma: En Revista: J Magn Reson Imaging Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos