Kalina Jordanova1
1National Institute of Standards and Technology, Boulder, CO, United States
Synopsis
Evaluating the performance of MRI systems validates MR measurements. A phantom is an object used to ensure that MR systems and methods operate correctly. Phantom design requires identifying target measurements to be evaluated, and designing an object that can validate those measurements. Tradeoffs are made in phantom design to target specific properties or to accommodate different hardware configurations. Thus, physical properties of phantoms can be vastly different depending on the system and application being evaluated.
This talk discusses methods to design home-built phantoms that tackle many challenges in phantom design and highlights the most important considerations for open-source designs.
Target Audience
Those with an interest in building reference objects that evaluate and validate the performance of MR scanners, methods, and analytical tools.Objectives
Attendees will understand the considerations made in creating a phantom – an object that can be used to evaluate MR systems. They will learn the tools necessary to design their own phantom objects, and will be introduced to other open-source phantom designs that are available to them.Purpose
Evaluating the performance of MRI systems is valuable for increasing confidence in MR images and methods. This is especially true for applications like quantitative imaging, where the quantitative measurements must be insensitive to system changes or unwanted field fluctuations; or for open-source systems that may have increased variation in design depending on the user’s implementation.
A phantom is a physical object that can be used to ensure that MRI systems and methods for imaging the human body are operating correctly [1]. Many different phantoms have been developed for diverse applications. A small subset of previously developed phantoms include: structural phantoms to assess geometrical distortions due to system inhomogeneities [2-3]; diffusion phantoms to measure diffusion-related quantitative parameters [4-5]; flow phantoms for cardiac and other flow applications [6-7]; breast imaging phantoms [8-9]; fat fraction phantoms [10]; relaxation parameter quantitative imaging phantoms [11-12]; anthropomorphic phantoms [13-16]; and still many others [17-18].
As the open-source MR community grows, many developers will find it necessary to create a home-built phantom. This talk will highlight the various considerations that should be made depending on the system hardware and target imaging application of the open-source system. Methods
To design a well-characterized home-built phantom, the target values or properties to be measured must first be identified. Measurements can target system-related parameters (field homogeneity, geometric distortion, spatial resolution, etc), physiological properties (diffusion, relaxation, flow, different target tissues of interest, etc), or the specific imaging sequence(s) and analysis software to be evaluated. Thus, the physical properties of home-built designs can be vastly different depending on the MR system and application that are being evaluated. It is important to design a phantom that will test the imaging system in the way that it is intended to be used. For example, the same sequences should be used to assess the performance of the phantom that will be used for in vivo applications.
Properties of the phantom that can be tweaked include the physical dimensions and structure of the phantom, and the materials included in the phantom. It may be useful to consider a modular design, wherein some of the phantom properties can be altered by the user depending on the need.
Many guidelines exist for MR phantom designs [1, 19-21]. In this talk, existing guidelines and other considerations for phantom design are discussed. An emphasis is placed on the factors that are most relevant for an open-source phantom design, with the goal of encouraging contributions to the open-source imaging initiative resources (https://gitlab.com/osii-one). Discussion
Phantom design can vary based on MR systems and target applications. Often, tradeoffs must be made in phantom design between manufacturability and breadth of measurement. Additionally, variations of physical properties (e.g. bore or coil size and shape) between MR systems makes universal phantom design more challenging. Phantoms that are built for a particular set of hardware cannot always be adapted to other hardware. By expanding the open-source MR phantom availability, more designs will be available for more diverse applications, making phantom development more accessible.
In this talk we will discuss methods to design home-built phantoms that tackle many of the challenges written here, to aid in the quest for making accurate MR systems and measurements more widely available. Acknowledgements
No acknowledgement found.References
- Keenan, Kathryn E., Maureen Ainslie, Alex J. Barker, Michael A. Boss, Kim M. Cecil, Cecil Charles, Thomas L. Chenevert, et al. “Quantitative Magnetic Resonance Imaging Phantoms: A Review and the Need for a System Phantom: Quantitative MRI Phantoms Review.” Magnetic Resonance in Medicine 79, no. 1 (January 2018): 48–61. https://doi.org/10.1002/mrm.26982.
- Radiology ACo. Phantom Test Guidance for the ACR MRI Accreditation Program. (ACR, Reston, 1998)
- Jack Jr., Clifford R., Matt A. Bernstein, Nick C. Fox, Paul Thompson, Gene Alexander, Danielle Harvey, Bret Borowski, et al. “The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI Methods.” Journal of Magnetic Resonance Imaging 27, no. 4 (2008): 685–91. https://doi.org/10.1002/jmri.21049.
- Boss, Michael, Thomas Chenevert, John Waterton, D Morris, Hossein Ragheb, Alan Jackson, N deSouza, et al. “TU-C-12A-08: Thermally-Stabilized Isotropic Diffusion Phantom for Multisite Assessment of Apparent Diffusion Coefficient Reproducibilty.” Medical Physics 41 (June 1, 2014): 464–464. https://doi.org/10.1118/1.4889298.
- Perrin, Muriel, Cyril Poupon, Bernard Rieul, Patrick Leroux, André Constantinesco, Jean-François Mangin, and Denis LeBihan. “Validation of Q-Ball Imaging with a Diffusion Fibre-Crossing Phantom on a Clinical Scanner.” Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1457 (May 29, 2005): 881–91. https://doi.org/10.1098/rstb.2005.1650.
- Nordell, B., F. Ståhlberg, A. Ericsson, and C. Ranta. “A Rotating Phantom for the Study of Flow Effects in MR Imaging.” Magnetic Resonance Imaging 6, no. 6 (November 1, 1988): 695–705. https://doi.org/10.1016/0730-725X(88)90094-X.
- Chu, Kenneth C., and Brian K. Rutt. “Polyvinyl Alcohol Cryogel: An Ideal Phantom Material for MR Studies of Arterial Flow and Elasticity.” Magnetic Resonance in Medicine 37, no. 2 (February 1997): 314–19. https://doi.org/10.1002/mrm.1910370230.
- Tuong, Betty, and Ian Gardiner. “Development of a Novel Breast MRI Phantom for Quality Control.” American Journal of Roentgenology 201, no. 3 (September 2013): W511–15. https://doi.org/10.2214/AJR.12.9571.
- Keenan, Kathryn E., Lisa J. Wilmes, Sheye O. Aliu, David C. Newitt, Ella F. Jones, Michael A. Boss, Karl F. Stupic, Stephen E. Russek, and Nola M. Hylton. “Design of a Breast Phantom for Quantitative MRI.” Journal of Magnetic Resonance Imaging 44, no. 3 (2016): 610–19. https://doi.org/10.1002/jmri.25214.
- Hines, Catherine D. G., Huanzhou Yu, Ann Shimakawa, Charles A. McKenzie, Jean H. Brittain, and Scott B. Reeder. “T1 Independent, T2* Corrected MRI with Accurate Spectral Modeling for Quantification of Fat: Validation in a Fat-Water-SPIO Phantom.” Journal of Magnetic Resonance Imaging : JMRI 30, no. 5 (November 2009): 1215–22. https://doi.org/10.1002/jmri.21957.
- Hattori, Kengo, Yusuke Ikemoto, Wataru Takao, Seiichiro Ohno, Takashi Harimoto, Susumu Kanazawa, Masataka Oita, Koichi Shibuya, Masahiro Kuroda, and Hirokazu Kato. “Development of MRI Phantom Equivalent to Human Tissues for 3.0-T MRI.” Medical Physics 40, no. 3 (2013): 032303. https://doi.org/10.1118/1.4790023.
- Stupic, Karl F., Maureen Ainslie, Michael A. Boss, Cecil Charles, Andrew M. Dienstfrey, Jeffrey L. Evelhoch, Paul Finn, et al. “A Standard System Phantom for Magnetic Resonance Imaging.” Magnetic Resonance in Medicine 86, no. 3 (2021): 1194–1211. https://doi.org/10.1002/mrm.28779.
- Mitsouras, Dimitris, Thomas C. Lee, Peter Liacouras, Ciprian N. Ionita, Todd Pietilla, Stephan E. Maier, and Robert V. Mulkern. “Three-Dimensional Printing of MRI-Visible Phantoms and MR Image-Guided Therapy Simulation.” Magnetic Resonance in Medicine 77, no. 2 (2017): 613–22. https://doi.org/10.1002/mrm.26136.
- Wood, Sossena, Narayanan Krishnamurthy, Tales Santini, Shailesh Raval, Nadim Farhat, John Andy Holmes, and Tamer S. Ibrahim. “Design and Fabrication of a Realistic Anthropomorphic Heterogeneous Head Phantom for MR Purposes.” PLOS ONE 12, no. 8 (August 14, 2017): e0183168. https://doi.org/10.1371/journal.pone.0183168.
- In, E., E. Walker, and H. E. Naguib. “Novel Development of 3D Printable UV-Curable Silicone for Multimodal Imaging Phantom.” Bioprinting 7 (September 1, 2017): 19–26. https://doi.org/10.1016/j.bprint.2017.05.003.
- Saotome, Kousaku, Akira Matsushita, Koji Matsumoto, Yoshiaki Kato, Kei Nakai, Koichi Murata, Tetsuya Yamamoto, Yoshiyuki Sankai, and Akira Matsumura. “A Brain Phantom for Motion-Corrected PROPELLER Showing Image Contrast and Construction Similar to Those of in Vivo MRI.” Magnetic Resonance Imaging 36 (February 1, 2017): 32–39. https://doi.org/10.1016/j.mri.2016.10.003.
- Shmueli, Karin, David L. Thomas, and Roger J. Ordidge. “Design, Construction and Evaluation of an Anthropomorphic Head Phantom with Realistic Susceptibility Artifacts.” Journal of Magnetic Resonance Imaging 26, no. 1 (2007): 202–7. https://doi.org/10.1002/jmri.20993.
- Rai, Robba, Lois C. Holloway, Carsten Brink, Matthew Field, Rasmus L. Christiansen, Yu Sun, Michael B. Barton, and Gary P. Liney. “Multicenter Evaluation of MRI-Based Radiomic Features: A Phantom Study.” Medical Physics 47, no. 7 (July 2020): 3054–63. https://doi.org/10.1002/mp.14173.
- Raunig DL, McShane LM, Pennello G, Gatsonis C, Carson PL, Voyvodic JT, Wahl RL, Kurland BF, Schwarz AJ, Gonen M, Zahlmann G, Kondratovich M, O’Donnell K, Petrick N, Cole PE, Garra B, Sullivan DC, QIBA Technical Performance Working Group. Quantitative imaging biomarkers: A review of statistical methods for technical performance assessment. Statistical methods in medical research. 2014. doi: 10.1177/0962280214537344. PubMed PMID: 24919831.
- Filippou, Valeria, and Charalampos Tsoumpas. “Recent Advances on the Development of Phantoms Using 3D Printing for Imaging with CT, MRI, PET, SPECT, and Ultrasound.” Medical Physics 45, no. 9 (September 2018): e740–60. https://doi.org/10.1002/mp.13058.
- McGarry, Conor K., Lesley J. Grattan, Aoife M. Ivory, Francesca Leek, Gary P. Liney, Yang Liu, Piero Miloro, et al. “Tissue Mimicking Materials for Imaging and Therapy Phantoms: A Review.” Physics in Medicine & Biology, September 2020. https://doi.org/10.1088/1361-6560/abbd17.