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Development of a standard phantom for diffusion-weighted magnetic resonance imaging quality control studies: A review

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Various materials and compounds have been used in the design of diffusion-weighted magnetic resonance imaging (DWMRI) phantoms to mimic biological tissue properties, including diffusion. This review thus provides an overview of the preparations of the various DW-MRI phantoms available in relation to the limitations and strengths of materials/solutions used to fill them. The narrative review conducted from relevant databases shows that synthesizing all relevant compounds from individual liquids, gels, and solutions based on their identified strengths could contribute to the development of a novel multifunctional DW-MRI phantom. The proposed multifunctional material at varied concentrations, when filled into a multi-compartment Perspex container of cylindrical or spherical geometry, could serve as a standard DW-MRI phantom. The standard multifunctional phantom could potentially provide DW-MRI quality control test parameters in one study session.
Rocznik
Strony
169--179
Opis fizyczny
Bibliogr. 39 poz., tab.
Twórcy
  • Department of Medical Imaging, University for Development Studies, Ghana
  • Department of Medical Imaging, University for Development Studies, Ghana
  • Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Ghana
  • Medical Physics, University of Ghana, Ghana
  • Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Ghana
autor
  • Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Ghana
  • Radiological and Medical Sciences Research Institute, Ghana Atomic Energy Commission, Ghana
  • Medical Physics, University of Ghana, Ghana
Bibliografia
  • 1. Drake-Pérez M, Boto J, Fitsiori A, Lovblad K, Vargas MI. Clinical applications of diffusion weighted imaging in neuroradiology. Insights into Imaging. 2018;9(4):535-47. https://doi.org/10.1007/s13244-018-0624-3
  • 2. Laubach HJ, Jakob PM, Loevblad KO, et al. A phantom for diffusion‐weighted imaging of acute stroke. Journal of Magnetic Resonance Imaging. 1998;8(6):1349-1354. https://doi.org/10.1002/jmri.1880080627
  • 3. Bammer R. Basic principles of diffusion-weighted imaging. European Journal of Radiology. 2003;45(3):169-84. https://doi.org/10.1016/S0720-048X(02)00303-0
  • 4. Tang L, Zhou XJ. Diffusion MRI of cancer: From low to high b‐values. Journal of Magnetic Resonance Imaging. 2019;49(1):23-40. https://doi.org/10.1002/jmri.26293
  • 5. Rosenkrantz AB, Padhani AR, Chenevert TL, et al. Body diffusion kurtosis imaging: basic principles, applications, and considerations for clinical practice. Journal of Magnetic Resonance Imaging. 2015;42(5):1190-202. https://doi.org/10.1002/jmri.24985
  • 6. Granata V, Fusco R, Setola SV, et al. Diffusion kurtosis imaging and conventional diffusion weighted imaging to assess electrochemotherapy response in locally advanced pancreatic cancer. Radiology and Oncology. 2019;53(1):15-24. https://doi.org/10.2478/raon-2019-0004
  • 7. Bennett KM, Schmainda KM, Bennett R, Rowe DB, Lu H, Hyde JS. Characterization of continuously distributed cortical water diffusion rates with a stretched‐exponential model. Magnetic Resonance in Medicine. 2003;50(4):727-34. https://doi.org/10.1002/mrm.10581
  • 8. Posnansky OP, Shah NJ. On the problem of diffusivity in heterogeneous biological materials with random structure. Journal of Biological Physics. 2008;34(6):551-567. https://doi.org/10.1007/s10867-008-9119-7
  • 9. Cooper RL, Chang DB, Young AC, Martin CJ, Ancker-Johnson B. Restricted diffusion in biophysical systems: experiment. Biophysical Journal. 1974;14(3):161-177. https://doi.org/10.1016/S0006-3495(74)85904-7
  • 10. Malyarenko DI, Pang Y, Amouzandeh G, Chenevert TL. Numerical DWI phantoms to optimize accuracy and precision of quantitative parametric maps for non-Gaussian diffusion. Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 113130W. 2020. https://doi.org/10.1117/12.2549412
  • 11. Kato H, Kuroda M, Yoshimura K, et al. Composition of MRI phantom equivalent to human tissues. Medical Physics. 2005;32(10):3199-3208. https://doi.org/10.1118/1.2047807
  • 12. de Souza EM, Costa ET, Castellano G. Phantoms for diffusion-weighted imaging and diffusion tensor imaging quality control: a review and new perspectives. Research on Biomedical Engineering. 2017;33(2):156-165. https://doi.org/10.1590/2446-4740.07816
  • 13. Kıvrak AS, Paksoy Y, Erol C, et al. Comparison of apparent diffusion coefficient values among different MRI platforms: a multicenter phantom study. Diagn Interv Radiol. 2013;19(6):433-437. https://doi.org/10.5152/dir.2013.13034
  • 14. Hubbard PL, Zhou FL, Eichhorn SJ, Parker GJ. Biomimetic phantom for the validation of diffusion magnetic resonance imaging. Magnetic Resonance in Medicine. 2015;73(1):299-305. https://doi.org/10.1002/mrm.25107
  • 15. Kalaitzakis G, Boursianis T, Gourzoulidis G, et al. Apparent diffusion coefficient measurements on a novel diffusion weighted MRI phantom utilizing EPI and HASTE sequences. Physica Medica. 2020;73:179-189. https://doi.org/10.1016/j.ejmp.2020.04.024
  • 16. Groch MW, Urbon JA, Erwin WD, Al-Doohan S. An MRI tissue equivalent lesion phantom using a novel polysaccharide material. Magnetic Resonance Imaging. 1991;9(3):417-421. https://doi.org/10.1016/0730-725X(91)90430-T
  • 17. Mazzara GP, Briggs RW, Wu Z, Steinbach BG. Use of a modified polysaccharide gel in developing a realistic breast phantom for MRI. Magnetic Resonance Imaging. 1996;14(6):639-648. https://doi.org/10.1016/0730-725X(96)00054-9
  • 18. Vassiliou VS, Heng EL, Gatehouse PD, et al. Magnetic resonance imaging phantoms for quality-control of myocardial T1 and ECV mapping: specific formulation, long-term stability and variation with heart rate and temperature. Journal of Cardiovascular Magnetic Resonance. 2016;18(1):1-12. https://doi.org/10.1186/s12968-016-0275-9
  • 19. Lavdas I, Behan KC, Papadaki A, McRobbie DW, Aboagye EO. A phantom for diffusion-weighted MRI (DW-MRI). Journal of Magnetic Resonance Imaging, 2013;38(1):173-179. https://doi.org/10.1002/jmri.23950
  • 20. Captur G, Gatehouse P, Keenan KE, et al. A medical device-grade T1 and ECV phantom for global T1 mapping quality assurance - the T1 Mapping and ECV Standardization in cardiovascular magnetic resonance (T1MES) program. Journal of Cardiovascular Magnetic Resonance. 2016;18(1):1-20. https://doi.org/10.1186/s12968-016-0280-z
  • 21. Kim JH, Kim JH, Lee SH., Park J, Lee SK. Fabrication of a spherical inclusion phantom for validation of magnetic resonance-based magnetic susceptibility imaging. PLOS One. 2019;14(8):e0220639. https://doi.org/10.1371/journal.pone.0220639
  • 22. Hara M, Kuroda M, Ohmura Y, et al. A new phantom and empirical formula for apparent diffusion coefficient measurement by a 3 Tesla magnetic resonance imaging scanner. Oncology Letters. 2014;8(2):819-824. https://doi.org/10.3892/ol.2014.2187
  • 23. Gatidis S, Schmidt H, Martirosian P, Schwenzer NF. Development of an MRI phantom for diffusion‐weighted imaging with independent adjustment of apparent diffusion coefficient values and T2 relaxation times. Magnetic Resonance in Medicine. 2014;72(2):459-463. https://doi.org/10.1002/mrm.24944
  • 24. Le Bihan D, Iima M. Diffusion magnetic resonance imaging: what water tells us about biological tissues. PLOS Biology. 2015;13(7):e1002203. https://doi.org/10.1371/journal.pbio.1002246
  • 25. Khasawneh A, Kuroda M, Yoshimura Y, et al. Development of a novel phantom using polyethylene glycol for the visualization of restricted diffusion in diffusion kurtosis imaging and apparent diffusion coefficient subtraction method. Biomedical Reports. 2020;13:52. https://doi.org/10.3892/br.2020.1359
  • 26. Hariri A, Palma-Chavez J, Wear KA, Pfefer TJ, Jokerst JV, Vogt WC. Polyacrylamide hydrogel phantoms for performance evaluation of multispectral photoacoustic imaging systems. Photoacoustics. 2021;22:100245. https://doi.org/10.1016/j.pacs.2021.100245
  • 27. Stringer R. Electrophoresis overview. Encyclopedia of Analytical Science (Second Edition), Elsevier 2005, Pages 356-363, https://doi.org/10.1016/B0-12-369397-7/00120-5
  • 28. Fieremans E, Lee HH. Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook. Neuroimage. 2018;182:39-61. https://doi.org/10.1016/j.neuroimage.2018.06.046
  • 29. Yoshida T, Urikura A, Shirata K, Nakaya Y, Terashima S, Hosokawa Y. Image quality assessment of single-shot turbo spin echo diffusion-weighted imaging with parallel imaging technique: a phantom study. The British Journal of Radiology. 2016;89(1065):20160512. https://doi.org/10.1259/bjr.20160512
  • 30. Komlosh ME, Benjamini D, Barnett AS, et al. Anisotropic phantom to calibrate high-q diffusion MRI methods. Journal of Magnetic Resonance. 2017;275:19-28. https://doi.org/10.1016/j.jmr.2016.11.017
  • 31. Kamphuis ME, Greuter MJ, Slart RH, Slump CH. Quantitative imaging: systematic review of perfusion/flow phantoms. European Radiology Experimental. 2020;4(1):1-13. https://doi.org/10.1186/s41747-019-0133-2
  • 32. Al-Mulla M, McGee A, Kenny P, Rainford L. Quality Assurance Phantom Testing of an Echo-Planar Diffusion-Weighted Sequence on a 3T Scanner. Adv Res Foot Ankle: ARFA-110. 2019;11
  • 33. Shurche S, Riahialam N. Diffusion Phantom Assessment in 3 Tesla MRI Scanner. Frontiers in Biomedical Technologies. 2016;3(1-2):34-40
  • 34. Hellerbach A, Schuster V, Jansen A, Sommer J. MRI phantoms–are there alternatives to agar? PloS One. 2013;8(8):e70343. https://doi.org/10.1371/journal.pone.0070343
  • 35. Sato E, Fukuzawa K, Takashima H, et al. Evaluation of a Polyethylene Glycol Phantom for Measuring Apparent Diffusion Coefficients Using Three 3.0 T MRI Systems. Applied Magnetic Resonance. 2021;52(5):619-31. https://doi.org/10.1007/s00723-021-01336-z
  • 36. Matsuya R, Kuroda M, Matsumoto Y, et al. A new phantom using polyethylene glycol as an apparent diffusion coefficient standard for MR imaging. International Journal of Oncology. 2009;35(4):893-900. https://doi.org/10.3892/ijo_00000404
  • 37. Boursianis T, Kalaitzakis G, Pappas E, Karantanas AH, Maris TG. MRI diffusion phantoms: ADC and relaxometric measurement comparisons between polyacrylamide and agarose gels. European Journal of Radiology. 2021;139:109696. https://doi.org/10.1016/j.ejrad.2021.109696
  • 38. Wagner F, Laun FB, Kuder TA, et al. Temperature and concentration calibration of aqueous polyvinylpyrrolidone (PVP) solutions for isotropic diffusion MRI phantoms. PloS One. 2017;12(6):e0179276. https://doi.org/10.1371/journal.pone.0179276
  • 39. Pierpaoli C, Sarlls J, Nevo U, Basser PJ, Horkay F. Polyvinylpyrrolidone (PVP) water solutions as isotropic phantoms for diffusion MRI studies. Proc Intl Soc Magn Reson Med. 2009;17:1414
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-11cdbe0b-a91a-4d32-833c-a0c95e63e1d3
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