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Technical note: Temperature and concentration dependence of water diffusion in polyvinylpyrrolidone solutions

dc.contributor.authorAmouzandeh, Ghoncheh
dc.contributor.authorChenevert, Thomas L.
dc.contributor.authorSwanson, Scott D.
dc.contributor.authorRoss, Brian D.
dc.contributor.authorMalyarenko, Dariya I.
dc.date.accessioned2022-06-01T20:29:10Z
dc.date.available2023-06-01 16:29:07en
dc.date.available2022-06-01T20:29:10Z
dc.date.issued2022-05
dc.identifier.citationAmouzandeh, Ghoncheh; Chenevert, Thomas L.; Swanson, Scott D.; Ross, Brian D.; Malyarenko, Dariya I. (2022). "Technical note: Temperature and concentration dependence of water diffusion in polyvinylpyrrolidone solutions." Medical Physics 49(5): 3325-3332.
dc.identifier.issn0094-2405
dc.identifier.issn2473-4209
dc.identifier.urihttps://hdl.handle.net/2027.42/172814
dc.description.abstractObjectiveThe goal of this work is to provide temperature and concentration calibration of water diffusivity in polyvinylpyrrolidone (PVP) solutions used in phantoms to assess system bias and linearity in apparent diffusion coefficient (ADC) measurements.MethodADC measurements were performed for 40 kDa (K40) PVP of six concentrations (0%, 10%, 20%, 30%, 40%, and 50% by weight) at three temperatures (19.5°C, 22.5°C, and 26.4°C), with internal phantom temperature monitored by optical thermometer (±0.2°C). To achieve ADC measurement and fit accuracy of better than 0.5%, three orthogonal diffusion gradients were calibrated using known water diffusivity at 0°C and system gradient nonlinearity maps. Noise-floor fit bias was also controlled by limiting the maximum b-value used for ADC calculation of each sample. The ADC temperature dependence was modeled by Arrhenius functions of each PVP concentration. The concentration dependence was modeled by quadratic function for ADC normalized by the theoretical water diffusion values. Calibration coefficients were obtained from linear regression model fits.ResultsMeasured phantom ADC values increased with temperature and decreasing PVP concentration, [PVP]. The derived Arrhenius model parameters for [PVP] between 0% and 50%, are reported and can be used for K40 ADC temperature calibration with absolute ADC error within ±0.016 μm2/ms. Arrhenius model fit parameters normalized to water value scaled with [PVP] between 10% and 40%, and proportional change in activation energy increased faster than collision frequency. ADC normalization by water diffusivity, DW, from the Speedy–Angell relation accounted for the bulk of temperature dependence (±0.035 μm2/ms) and yielded quadratic calibration for ADCPVP/DW = (12.5 ± 0.7) ·10−5·[PVP]2 − (23.2 ± 0.3)·10−3·[PVP]+1, nearly independent of PVP molecular weight and temperature.ConclusionThe study provides ground-truth ADC values for K40 PVP solutions commonly used in diffusion phantoms for scanning at ambient room temperature. The described procedures and the reported calibration can be used for quality control and standardization of measured ADC values of PVP at different concentrations and temperatures.
dc.publisherWiley Periodicals, Inc.
dc.subject.otherPVP concentration
dc.subject.otherdiffusion phantom
dc.subject.otherADC calibration
dc.subject.othertemperature dependence
dc.subject.otherdiffusion MRI
dc.titleTechnical note: Temperature and concentration dependence of water diffusion in polyvinylpyrrolidone solutions
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172814/1/mp15556.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172814/2/mp15556-sup-0001-SuppMat.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/172814/3/mp15556_am.pdf
dc.identifier.doi10.1002/mp.15556
dc.identifier.sourceMedical Physics
dc.identifier.citedreferenceDietrich O, Raya JG, Reeder SB, Reiser MF, Schoenberg SO. Measurement of signal-to-noise ratios in MR images: influence of multichannel coils, parallel imaging, and reconstruction filters. J Magn Reson Imaging. 2007; 26 ( 2 ): 375 - 385.
dc.identifier.citedreferenceRahbar H, Zhang Z, Chenevert TL, et al. Utility of diffusion-weighted imaging to decrease unnecessary biopsies prompted by breast MRI: a trial of the ECOG-ACRIN Cancer Research Group (A6702). Clin Cancer Res. 2019; 25 ( 6 ): 1756 - 1765.
dc.identifier.citedreferencePadhani AR, Liu G, Mu-Koh D, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009; 11 ( 2 ): 102 - 125.
dc.identifier.citedreferenceShukla-Dave A, Obuchowski NA, Chenevert TL, et al. Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE-MRI derived biomarkers in multicenter oncology trials. J Magn Reson Imaging. 2019; 49 ( 7 ): e101 - e121.
dc.identifier.citedreferenceShenoy-Bhangle A, Baliyan V, Kordbacheh H, Guimaraes AR, Kambadakone A. Diffusion weighted magnetic resonance imaging of liver: principles, clinical applications and recent updates. World J Hepatol. 2017; 9 ( 26 ): 1081 - 1091.
dc.identifier.citedreferenceRaunig DL, Mcshane LM, Pennello G, et al. Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment. Stat Methods Med Res. 2015; 24 ( 1 ): 27 - 67.
dc.identifier.citedreferenceSullivan DC, Obuchowski NA, Kessler LG, et al. Metrology standards for quantitative imaging biomarkers. Radiology. 2015; 277 ( 3 ): 813 - 825.
dc.identifier.citedreferenceChenevert TL, Galbán CJ, Ivancevic MK, et al. Diffusion coefficient measurement using a temperature-controlled fluid for quality control in multicenter studies. J Magn Reson Imaging. 2011; 34 ( 4 ): 983 - 987.
dc.identifier.citedreferenceKeenan KE, Stupic KF, Russek SE, Mirowski E. MRI-visible liquid crystal thermometer. Magn Reson Med. 2020; 84 ( 3 ): 1552 - 1563.
dc.identifier.citedreferenceKeenan KE, Ainslie M, Barker AJ, et al. Quantitative magnetic resonance imaging phantoms: a review and the need for a system phantom. Magn Reson Med. 2018; 79 ( 1 ): 48 - 61.
dc.identifier.citedreferencePierpaoli C, Sarlls J, Nevo U, Basser PJ, Horkay F. Polyvinylpyrrolidone (PVP) water solutions as isotropic phantoms for diffusion MRI studies. In: Proceedings of the 17th International Society for Magnetic Resonance in Medicine (ISMRM); Honolulu, Hawaii, USA. ISMRM; 2009, p. 1414.
dc.identifier.citedreferencePalacios EM, Martin AJ, Boss MA, et al. Toward precision and reproducibility of diffusion tensor imaging: a multicenter diffusion phantom and traveling volunteer study. AJNR Am J Neuroradiol. 2017; 38 ( 3 ): 537 - 545.
dc.identifier.citedreferencePullens P, Bladt P, Sijbers J, Maas AIR, Parizel PM. Technical Note: a safe, cheap, and easy-to-use isotropic diffusion MRI phantom for clinical and multicenter studies. Med Phys. 2017; 44 ( 3 ): 1063 - 1070.
dc.identifier.citedreferenceWagner 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.
dc.identifier.citedreferenceNewitt DC, Tan ET, Wilmes LJ, et al. Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial. J Magn Reson Imaging. 2015; 42 ( 4 ): 908 - 919.
dc.identifier.citedreferenceMalyarenko D, Galbán CJ, Londy FJ, et al. Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom. J Magn Reson Imaging. 2013; 37 ( 5 ): 1238 - 1246.
dc.identifier.citedreferenceHolz M, Heil SR, Sacco A. Temperature-dependent self-diffusion coefficients of water and six selected molecular liquids for calibration in accurate H-1 NMR PFG measurements. Phys Chem Chem Phys. 2000; 2 ( 20 ): 4740 - 4742.
dc.identifier.citedreferenceMalyarenko DI, Ross BD, Chenevert TL. Analysis and correction of gradient nonlinearity bias in apparent diffusion coefficient measurements. Magn Reson Med. 2014; 71 ( 3 ): 1312 - 1323.
dc.identifier.citedreferenceTofts PS, Lloyd D, Clark CA, et al. Test liquids for quantitative MRI measurements of self-diffusion coefficient in vivo. Magn Reson Med. 2000; 43 ( 3 ): 368 - 374.
dc.identifier.citedreferenceKeenan KE, Peskin AP, Wilmes LJ, et al. Variability and bias assessment in breast ADC measurement across multiple systems. J Magn Reson Imaging. 2016; 44 ( 4 ): 846 - 855.
dc.identifier.citedreferenceMalyarenko DI, Swanson SD, Konar AS, et al. Multicenter repeatability study of a novel quantitative diffusion kurtosis imaging phantom. Tomography. 2019; 5 ( 1 ): 36 - 43.
dc.identifier.citedreferenceSpeedy RJ, Angell CA. Isothermal compressibility of supercooled water and evidence for a thermodynamic singularity at -45° C. J Chem Phys. 1976; 65 ( 3 ): 851 - 858.
dc.identifier.citedreferenceMills R. Self-diffusion in normal and heavy-water in range 1-45 °. J Phys Chem. 1973; 77 ( 5 ): 685 - 688.
dc.identifier.citedreferenceGladden JK, Dole M. Diffusion in supersaturated solutions.II. glucose solutions. J Am Chem Soc, 1953; 75 ( 16 ): 3900 - 3904.
dc.identifier.citedreferenceLaage D, Hynes JT. Do more strongly hydrogen-bonded water molecules reorient more slowly ? Chem Phys Lett, 2006; 433 ( 1-3 ): 80 - 85.
dc.identifier.citedreferenceRussek SE. NIST/NIBIB Medical Imaging Phantom Lending Library. http://doi.org/10.18434/mds2-2366 2021.
dc.identifier.citedreferenceBihan DLe. The ‘wet mind’:water and functional neuroimaging. Phys Med Biol. 2007; 52 ( 7 ): R57 - R90.
dc.identifier.citedreferenceBarkovich EJ, Shankar PR, Westphalen AC. A systematic review of the existing prostate imaging reporting and data system version 2 (PI-RADSv2) literature and subset meta-analysis of PI-RADSv2 categories stratified by gleason scores. AJR Am J Roentgenol. 2019; 212 ( 4 ): 847 - 854.
dc.identifier.citedreferencePartridge SC, Newitt DC, Chenevert TL, Rosen MA, Hylton NM. Diffusion-weighted MRI in multicenter trials of breast cancer. Radiology 2019; 291 ( 2 ): 546.
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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