Michael Shulman1,2, Eunyoung Cho1,2, Bipin Aasi1,2, Jin Cheng1,2, Saiee Nithiyanantham1,2, Nicole Waddell1,2, Dafna Sussman3,4,5,6. 1. Department of Electrical, Computer, and Biomedical Engineering, Ryerson University, Toronto, ON, M5B 2K3, Canada. 2. Institute for Biomedical Engineering, Science and Technology (iBEST), Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1T8, Canada. 3. Department of Electrical, Computer, and Biomedical Engineering, Ryerson University, Toronto, ON, M5B 2K3, Canada. dafna.sussman@ryerson.ca. 4. Institute for Biomedical Engineering, Science and Technology (iBEST), Ryerson University and St. Michael's Hospital, Toronto, ON, M5B 1T8, Canada. dafna.sussman@ryerson.ca. 5. The Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, M5B 1T8, Canada. dafna.sussman@ryerson.ca. 6. Department of Biomedical Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada. dafna.sussman@ryerson.ca.
Abstract
OBJECTIVE: To provide a review and quantitative analysis of the available fetal MR imaging phantoms. MATERIALS AND METHODS: A literature search was conducted across Pubmed, Google Scholar, and Ryerson University Library databases to identify fetal MR imaging phantoms. Phantoms were graded on a semi-quantitative scale in regards to four evaluation categories: (1) anatomical accuracy in size and shape, (2) dielectric conductivity similar to the simulated tissue, (3) relaxation times similar to simulated tissue, and (4) physiological motion similar to fetal gross body, cardiovascular, and breathing motion. This was followed by statistical analysis to identify significant findings. RESULTS: Seventeen fetal phantoms were identified and had an average overall percentage accuracy of 26%, with anatomical accuracy being satisfied the most (56%) and physiological motion the least (7%). Phantoms constructed using 3D printing were significantly more accurate than conventionally constructed phantoms. DISCUSSION: Currently available fetal phantoms lack accuracy and motion simulation. 3D printing may lead to higher accuracy compared with traditional manufacturing. Future research needs to focus on properly simulating both fetal anatomy and physiological motion to produce a phantom that is appropriate for fetal MRI sequence development and optimization.
OBJECTIVE: To provide a review and quantitative analysis of the available fetal MR imaging phantoms. MATERIALS AND METHODS: A literature search was conducted across Pubmed, Google Scholar, and Ryerson University Library databases to identify fetal MR imaging phantoms. Phantoms were graded on a semi-quantitative scale in regards to four evaluation categories: (1) anatomical accuracy in size and shape, (2) dielectric conductivity similar to the simulated tissue, (3) relaxation times similar to simulated tissue, and (4) physiological motion similar to fetal gross body, cardiovascular, and breathing motion. This was followed by statistical analysis to identify significant findings. RESULTS: Seventeen fetal phantoms were identified and had an average overall percentage accuracy of 26%, with anatomical accuracy being satisfied the most (56%) and physiological motion the least (7%). Phantoms constructed using 3D printing were significantly more accurate than conventionally constructed phantoms. DISCUSSION: Currently available fetal phantoms lack accuracy and motion simulation. 3D printing may lead to higher accuracy compared with traditional manufacturing. Future research needs to focus on properly simulating both fetal anatomy and physiological motion to produce a phantom that is appropriate for fetal MRI sequence development and optimization.
Keywords:
3D printing; Accuracy assessment; Artifacts; Fetus; Imaging; Magnetic Resonance Imaging; Phantoms; Synthesis methods
Authors: Michael S Jansz; Mike Seed; Joshua F P van Amerom; Derek Wong; Lars Grosse-Wortmann; Shi-Joon Yoo; Christopher K Macgowan Journal: Magn Reson Med Date: 2010-11 Impact factor: 4.668
Authors: Dimitris Mitsouras; Thomas C Lee; Peter Liacouras; Ciprian N Ionita; Todd Pietilla; Stephan E Maier; Robert V Mulkern Journal: Magn Reson Med Date: 2016-02-11 Impact factor: 4.668
Authors: Melanie Freed; Jacco A de Zwart; Jennifer T Loud; Riham H El Khouli; Kyle J Myers; Mark H Greene; Jeff H Duyn; Aldo Badano Journal: Med Phys Date: 2011-02 Impact factor: 4.071
Authors: Ali Gholipour; Judith A Estroff; Carol E Barnewolt; Richard L Robertson; P Ellen Grant; Borjan Gagoski; Simon K Warfield; Onur Afacan; Susan A Connolly; Jeffrey J Neil; Adam Wolfberg; Robert V Mulkern Journal: Concepts Magn Reson Part A Bridg Educ Res Date: 2014-11 Impact factor: 0.481
Authors: Datta Singh Goolaub; Christopher W Roy; Eric Schrauben; Dafna Sussman; Davide Marini; Mike Seed; Christopher K Macgowan Journal: J Cardiovasc Magn Reson Date: 2018-11-29 Impact factor: 5.364