Assessing measurement consistency of a diffusion tensor imaging (DTI) quality control (QC) anisotropy phantom

Avants BB, Cook PA, Ungar L, Gee JC, Grossman M (2010) Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis. Neuroimage 50(3):1004–1016. https://doi.org/10.1016/j.neuroimage.2010.01.041

Article  PubMed  Google Scholar 

Faria AV, Zhang J, Oishi K, Li X, Jiang H, Akhter K, Hermoye L, Lee SK, Hoon A, Stashinko E, Miller MI (2010) Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection. Neuroimage 52(2):415–428. https://doi.org/10.1016/j.neuroimage.2010.04.238

Article  PubMed  Google Scholar 

Ciccarelli O, Catani M, Johansen-Berg H, Clark C, Thompson A (2008) Diffusion-based tractography in neurological disorders: concepts, applications, and future developments. Lancet Neurol 7(8):715–727. https://doi.org/10.1016/S1474-4422(08)70163-7

Article  PubMed  Google Scholar 

Yu CS, Li KC, Xuan Y, Ji XM, Qin W (2005) Diffusion tensor tractography in patients with cerebral tumors: a helpful technique for neurosurgical planning and postoperative assessment. Eur J Radiol 56(2):197–204. https://doi.org/10.1016/j.ejrad.2005.04.010

Article  PubMed  Google Scholar 

Soni N, Mehrotra A, Behari S, Kumar S, Gupta N (2017) Diffusion-tensor imaging and tractography application in pre-operative planning of intra-axial brain lesions. Cureus. https://doi.org/10.7759/cureus.1739

Article  PubMed  PubMed Central  Google Scholar 

Asken BM, DeKosky ST, Clugston JR, Jaffee MS, Bauer RM (2018) Diffusion tensor imaging (DTI) findings in adult civilian, military, and sport-related mild traumatic brain injury (mTBI): a systematic critical review. Brain Imaging Behav 12:585–612. https://doi.org/10.1007/s11682-017-9708-9

Article  PubMed  Google Scholar 

Sasaki M, Yamada K, Watanabe Y, Matsui M, Ida M, Fujiwara S, Shibata E (2008) Variability in absolute apparent diffusion coefficient values across different platforms may be substantial: a multivendor, multi-institutional comparison study. Radiology 249(2):624–630. https://doi.org/10.1148/radiol.2492071681

Article  PubMed  Google Scholar 

Keenan KE, Ainslie M, Barker AJ, Boss MA, Cecil KM, Charles C, Chenevert TL, Clarke L, Evelhoch JL, Finn P, Gembris D (2018) Quantitative magnetic resonance imaging phantoms: a review and the need for a system phantom. Magn Reson Med 79(1):48–61. https://doi.org/10.1002/mrm.26982

Article  PubMed  Google Scholar 

Tong Q, He H, Gong T, Li C, Liang P, Qian T, Sun Y, Ding Q, Li K, Zhong J (2020) Multicenter dataset of multi-shell diffusion MRI in healthy traveling adults with identical settings. Sci Data 7(1):157. https://doi.org/10.1038/s41597-020-0493-8

Article  PubMed  PubMed Central  Google Scholar 

Lauzon CB, Asman AJ, Esparza ML, Burns SS, Fan Q, Gao Y, Anderson AW, Davis N, Cutting LE, Landman BA (2013) Simultaneous analysis and quality assurance for diffusion tensor imaging. PLoS ONE 8(4):e61737. https://doi.org/10.1371/journal.pone.0061737

Article  CAS  PubMed  PubMed Central  Google Scholar 

Palmeri ML, Milkowski A, Barr R, Carson P, Couade M, Chen J, Chen S, Dhyani M, Ehman R, Garra B, Gee A (2021) Radiological society of North America/quantitative imaging biomarker alliance shear wave speed bias quantification in elastic and viscoelastic phantoms. J Ultrasound Med 40(3):569–581. https://doi.org/10.1002/jum.15609

Article  PubMed  PubMed Central  Google Scholar 

Clarke LP, Croft BS, Nordstrom R, Zhang H, Kelloff G, Tatum J (2009) Quantitative imaging for evaluation of response to cancer therapy. Transl Oncology. 2(4):195

Google Scholar 

Belli G, Busoni S, Ciccarone A, Coniglio A, Esposito M, Giannelli M, Mazzoni LN, Nocetti L, Sghedoni R, Tarducci R, Zatelli G (2016) Quality assurance multicenter comparison of different MR scanners for quantitative diffusion-weighted imaging. J Magn Reson Imaging 43(1):213–219. https://doi.org/10.1002/jmri.24956

Article  PubMed  Google Scholar 

Fedeli L, Belli G, Ciccarone A, Coniglio A, Esposito M, Giannelli M, Mazzoni LN, Nocetti L, Sghedoni R, Tarducci R, Altabella L (2018) Dependence of apparent diffusion coefficient measurement on diffusion gradient direction and spatial position–A quality assurance intercomparison study of forty-four scanners for quantitative diffusion-weighted imaging. Physica Med 1(55):135–141. https://doi.org/10.1016/j.ejmp.2018.09.007

Article  Google Scholar 

Fritz V, Eisele S, Martirosian P, Machann J, Schick F (2024) A straightforward procedure to build a non-toxic relaxometry phantom with desired T1 and T2 times at 3T. Magn Reson Mater Phys, Biol Med 11:1–9. https://doi.org/10.1007/s10334-024-01166-7

Article  CAS  Google Scholar 

Souza EM, Costa ET, Castellano G (2017) Phantoms for diffusion-weighted imaging and diffusion tensor imaging quality control: a review and new perspectives. Res Biomed Eng 33:156–165. https://doi.org/10.1590/2446-4740.07816

Article  Google Scholar 

Fortin JP, Parker D, Tunç B, Watanabe T, Elliott MA, Ruparel K, Roalf DR, Satterthwaite TD, Gur RC, Gur RE, Schultz RT (2017) Harmonization of multi-site diffusion tensor imaging data. Neuroimage 1(161):149–170. https://doi.org/10.1016/j.neuroimage.2017.08.047

Article  Google Scholar 

Verma R, Swanson RL, Parker D, Ismail AA, Shinohara RT, Alappatt JA, Doshi J, Davatzikos C, Gallaway M, Duda D, Chen HI (2019) Neuroimaging findings in US government personnel with possible exposure to directional phenomena in Havana. Cuba Jama. 322(4):336–47. https://doi.org/10.1001/jama.2019.9269

Article  PubMed  Google Scholar 

Karayumak SC, Bouix S, Ning L, James A, Crow T, Shenton M, Kubicki M, Rathi Y (2019) Retrospective harmonization of multi-site diffusion MRI data acquired with different acquisition parameters. Neuroimage 1(184):180–200. https://doi.org/10.1016/j.neuroimage.2018.08.073

Article  Google Scholar 

Pohl KM, Sullivan EV, Rohlfing T, Chu W, Kwon D, Nichols BN, Zhang Y, Brown SA, Tapert SF, Cummins K, Thompson WK (2016) Harmonizing DTI measurements across scanners to examine the development of white matter microstructure in 803 adolescents of the NCANDA study. Neuroimage 15(130):194–213. https://doi.org/10.1016/j.neuroimage.2016.01.061

Article  Google Scholar 

Tax CM, Grussu F, Kaden E, Ning L, Rudrapatna U, Evans CJ, St-Jean S, Leemans A, Koppers S, Merhof D, Ghosh A (2019) Cross-scanner and cross-protocol diffusion MRI data harmonisation: a benchmark database and evaluation of algorithms. Neuroimage 15(195):285–299. https://doi.org/10.1016/j.neuroimage.2019.01.077

Article  Google Scholar 

National Electrical Manufacturers Association. Determination of signal-to-noise ratio (SNR) in diagnostic magnetic resonance imaging. NEMA Standards Publication MS 1–1991. R2014. https://www.nema.org/docs/default-source/standards-document-library/ms1-2008-r2014-watermarked.pdf?sfvrsn=2101f7b9_2

International Electrotechnical Commission. Magnetic Resonance Equipment for Medical Imaging: Determination of Essential Image Quality Parameters. International Electrotechnical Commission; 2018. https://webstore.iec.ch/en/publication/61163

Gunter JL, Bernstein MA, Borowski BJ, Ward CP, Britson PJ, Felmlee JP, Schuff N, Weiner M, Jack CR (2009) Measurement of MRI scanner performance with the ADNI phantom. Med Phys. https://doi.org/10.1118/1.3116776

Article  PubMed  PubMed Central  Google Scholar 

National Electrical Manufacturers Association. Determination of image uniformity in diagnostic magnetic resonance images. NEMA Standards Publication MS 1–2005. R2020. https://www.nema.org/standards/view/determination-of-image-uniformity-in-diagnostic-magnetic-resonance-images

Friedman L, Glover GH (2006) Report on a multicenter fMRI quality assurance protocol. J Magn Reson Imaging 23(6):827–839. https://doi.org/10.1002/jmri.20583

Article  PubMed  Google Scholar 

Xu D, Maier JK, King KF, Collick BD, Wu G, Peters RD, Hinks RS (2013) Prospective and retrospective high order eddy current mitigation for diffusion weighted echo planar imaging. Magn Reson Med 70(5):1293–1305. https://doi.org/10.1002/mrm.24589

Article  PubMed  Google Scholar 

Ginsburger K, Poupon F, Beaujoin J, Estournet D, Matuschke F, Mangin JF, Axer M, Poupon C (2018) Improving the realism of white matter numerical phantoms: a step toward a better understanding of the influence of structural disorders in diffusion MRI. Front Phys 6:12. https://doi.org/10.3389/fphy.2018.00012

Article  Google Scholar 

Henkelman RM (1985) Measurement of signal intensities in the presence of noise in MR images. Med Phys 12(2):232–233. https://doi.org/10.1118/1.595711

Article  CAS  PubMed  Google Scholar 

Murphy BW, Carson PL, Ellis JH, Zhang YT, Hyde RJ, Chenevert TL (1993) Signal-to-noise measures for magnetic resonance imagers. Magn Reson Imaging 11(3):425–428. https://doi.org/10.1016/0730-725X(93)90076-P

Article  CAS  PubMed  Google Scholar 

Kellman P, McVeigh ER (2005) Image reconstruction in SNR units: a general method for SNR measurement. Magn Reson Med 54(6):1439–1447. https://doi.org/10.1002/mrm.20713

Article  PubMed  PubMed Central  Google Scholar 

Dietrich O, Raya JG, Reeder SB, Reiser MF, Schoenberg SO (2007) Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging: Off J Int Soc Magn Reson Med 26(2):375–385. https://doi.org/10.1002/jmri.20969

Article  Google Scholar 

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