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Characterization of anisotropic T2W signals from human knee femoral cartilage: The magic angle effect on a spherical surface

dc.contributor.authorPang, Yuxi
dc.date.accessioned2021-07-01T20:12:43Z
dc.date.available2022-08-01 16:12:38en
dc.date.available2021-07-01T20:12:43Z
dc.date.issued2021-07
dc.identifier.citationPang, Yuxi (2021). "Characterization of anisotropic T2W signals from human knee femoral cartilage: The magic angle effect on a spherical surface." NMR in Biomedicine 34(7): n/a-n/a.
dc.identifier.issn0952-3480
dc.identifier.issn1099-1492
dc.identifier.urihttps://hdl.handle.net/2027.42/168330
dc.description.abstractThe aim of the current study was to propose a generalized magic angle effect (gMAE) function for characterizing anisotropic T2W signals of human knee femoral cartilage with a spherical surface in clinical studies. A gMAE model function f(α, ε) was formulated for an orientation‐dependent (ε) transverse T2 (i.e., 1/R2) relaxation in cartilage assuming an axially symmetric distribution (α) of collagen fibers. T2W sagittal images were acquired on an adult volunteer’s healthy knee at 3 T, and ROI‐based average signals S(ε) were extracted from angularly and radially segmented femoral cartilage. Compared with the standard MAE (sMAE) functions in the deep (DZ, α = 0°) and in the superficial (SZ, α = 90°) zones, a general form of R2 orientation‐dependent function f(α, ε) was fitted to S(ε), including an isotropic R2 contribution (internal reference [REF]). Goodness of fit was evaluated by root‐mean‐square deviations (RMSDs). An F‐test and a paired t‐test were respectively used to assess significant differences between the observed variances and means, with statistical significance set to p less than .05. As a symmetric orientation‐dependence function with a varying dynamic range, the proposed gMAE model outperformed the previous sMAE functions manifested by significantly reduced RMSDs in the DZ (0.239 ± 0.122 vs. 0.267 ± 0.097, p = .014) and in the SZ (0.183 ± 0.081 vs. 0.254 ± 0.085, p < .001). The fitted average angle α (38.5 ± 34.6° vs. 45.1 ± 30.1°, p < .43) and REF (5.092 ± 0.369 vs. 5.305 ± 0.440, p < .001) were smaller in the DZ than those in SZ, in good agreement with the reported collagen fibril microstructural configurations and the nonbound water contribution to R2 in articular cartilage. In conclusion, a general form of the magic angle effect function was proposed and demonstrated for better characterizing anisotropic T2W signals from human knee femoral cartilage at 3 T in clinical studies.A generalized magic angle effect (gMAE) function was formulated based on an axially symmetric collagen fibril distribution to better characterize anisotropic T2W signals of cartilage on a curved surface. Compared with the standard MAE models, the proposed function provided significantly improved fitting of segmented T2W signals from an adult healthy knee femoral cartilage at 3 T. The potential applications of the proposed model function could be extended to other highly organized biological tissues beyond human knee articular cartilage.
dc.publisherWiley Periodicals, Inc.
dc.publisherThe Royal Society of Chemistry
dc.subject.otherhuman knee femoral cartilage
dc.subject.otherspherical surface
dc.subject.otherresidual dipolar interaction
dc.subject.otherorientation‐dependent transverse relaxation
dc.subject.otheranisotropic T2‐weighted imaging
dc.subject.othermagic angle effect
dc.titleCharacterization of anisotropic T2W signals from human knee femoral cartilage: The magic angle effect on a spherical surface
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelElectrical Engineering
dc.subject.hlbsecondlevelPhysics
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168330/1/nbm4535.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/168330/2/nbm4535_am.pdf
dc.identifier.doi10.1002/nbm.4535
dc.identifier.sourceNMR in Biomedicine
dc.identifier.citedreferenceGeerts‐Ossevoort L, Weerdt Ed, Duijndam A, et al. Compressed SENSE. Speed done right. Every time. https://philipsproductcontent.blob.core.windows.net/assets/20180109/619119731f2a42c4acd4a863008a46c7.pdf. 2018; Accessed September 20, 2019.
dc.identifier.citedreferenceBella J. Collagen structure: new tricks from a very old dog. Biochem J. 2016; 473 ( 8 ): 1001 ‐ 1025. https://doi.org/10.1042/bj20151169
dc.identifier.citedreferenceWoessner DE. Nuclear magnetic‐relaxation and structure in aqueous heterogenous systems. Mol Phys. 1977; 34 ( 4 ): 899 ‐ 920.
dc.identifier.citedreferenceJeffery AK, Blunn GW, Archer CW, Bentley G. Three‐dimensional collagen architecture in bovine articular cartilage. J Bone Joint Surg. British volume. 1991; 73‐B ( 5 ): 795 ‐ 801. https://doi.org/10.1302/0301‐620x.73b5.1894669
dc.identifier.citedreferenceZheng S, Xia Y, Badar F. Further studies on the anisotropic distribution of collagen in articular cartilage by μMRI. Magn Reson Med. 2011; 65 ( 3 ): 656 ‐ 663.
dc.identifier.citedreferenceGarnov N, Gründer W, Thörmer G, et al. In vivo MRI analysis of depth‐dependent ultrastructure in human knee cartilage at 7 T. NMR Biomed. 2013; 26 ( 11 ): 1412 ‐ 1419. https://doi.org/10.1002/nbm.2968
dc.identifier.citedreferenceMlynárik V, Degrassi A, Toffanin R, Vittur F, Cova M, Pozzi‐Mucelli RS. Investigation of laminar appearance of articular cartilage by means of magnetic resonance microscopy. Magn Reson Imaging. 1996; 14 ( 4 ): 435 ‐ 442. https://doi.org/10.1016/0730‐725x(96)00025‐2
dc.identifier.citedreferenceXia Y. Relaxation anisotropy in cartilage by NMR microscopy (muMRI) at 14‐microm resolution. Magn Reson Med. 1998; 39 ( 6 ): 941 ‐ 949.
dc.identifier.citedreferenceGrunder W. MRI assessment of cartilage ultrastructure. NMR Biomed. 2006; 19 ( 7 ): 855 ‐ 876.
dc.identifier.citedreferenceBenninghoff A. Form und Bau der gelenkknorpel in ihren Beziehungen zur funktion‐Erste Mitteilung: Die modellierenden und formerhaltenden Faktoren des Knorpelreliefs. Zeitsh f Anatomie. 1925; 76: 43 ‐ 63.
dc.identifier.citedreferenceHennel JW, Klinowski J. Magic‐angle spinning: a historical perspective. In: Klinowski J, ed. New Techniques in Solid‐State NMR. Berlin, Heidelberg, Germany: Springer; 2005; 1 ‐ 14.
dc.identifier.citedreferenceMomot KI, Pope JM, Wellard RM. Anisotropy of spin relaxation of water protons in cartilage and tendon. NMR Biomed. 2010; 23 ( 3 ): 313 ‐ 324. https://doi.org/10.1002/nbm.1466
dc.identifier.citedreferenceYushkevich PA, Piven J, Hazlett HC, et al. User‐guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. Neuroimage. 2006; 31 ( 3 ): 1116 ‐ 1128. https://doi.org/10.1016/j.neuroimage.2006.01.015
dc.identifier.citedreferenceMarkwardt CB. Non‐linear least‐squares fitting in IDL with MPFIT. In: Bohlender D, Dowler P, Durand D, eds. Proceedings Astronomical Data Analysis Software and Systems XVIII, Quebec, Canada, ASP Conference Series, volume 411. San Francisco, CA: Astronomical Society of the Pacific; 2009: 251 ‐ 254.
dc.identifier.citedreferenceAhearn TS, Staff RT, Redpath TW, Semple SIK. The use of the Levenberg–Marquardt curve‐fitting algorithm in pharmacokinetic modelling of DCE‐MRI data. Phys Med Biol. 2005; 50 ( 9 ): N85 ‐ N92.
dc.identifier.citedreferenceShapiro E, Borthakur A, Kaufman J, Leigh J, Reddy R. Water distribution patterns inside bovine articular cartilage as visualized by1H magnetic resonance imaging. Osteoarthr Cartil. 2001; 9 ( 6 ): 533 ‐ 538.
dc.identifier.citedreferenceBerberat JE, Nissi MJ, Jurvelin JS, Nieminen MT. Assessment of interstitial water content of articular cartilage with T1 relaxation. Magn Reson Imaging. 2009; 27 ( 5 ): 727 ‐ 732. https://doi.org/10.1016/j.mri.2008.09.005
dc.identifier.citedreferenceXia Y. MRI of articular cartilage at microscopic resolution. Bone Joint Res. 2013; 2 ( 1 ): 9 ‐ 17. https://doi.org/10.1302/2046‐3758.21.2000135
dc.identifier.citedreferenceXia Y, Moody JB, Alhadlaq H. Orientational dependence of T2 relaxation in articular cartilage: A microscopic MRI (microMRI) study. Magn Reson Med. 2002; 48 ( 3 ): 460 ‐ 469. https://doi.org/10.1002/mrm.10216
dc.identifier.citedreferenceMlynárik V. Magic angle effect in articular cartilage. Am J Roentgenol. 2002; 178 ( 5 ): 1287 ‐ 1288. https://doi.org/10.2214/ajr.178.5.1781287
dc.identifier.citedreferenceGoodwin DW, Dunn JF. MR imaging and T2 mapping of femoral cartilage. Am J Roentgenol. 2002; 178 ( 6 ): 1568 ‐ 1569.
dc.identifier.citedreferenceNozaki T, Kaneko Y, Hon JY, et al. T1rho mapping of entire femoral cartilage using depth‐and angle‐dependent analysis. Eur Radiol. 2016; 26 ( 6 ): 1952 ‐ 1962.
dc.identifier.citedreferenceHenkelman RM, Stanisz GJ, Kim JK, Bronskill MJ. Anisotropy of NMR properties of tissues. Magn Reson Med. 1994; 32 ( 5 ): 592 ‐ 601.
dc.identifier.citedreferencePang Y. Anisotropic transverse relaxation in the human brain white matter induced by restricted rotational diffusion. In: Proceedings of the 29th Virtual Annual Meeting of ISMRM, 2021; abstract: 1711.
dc.identifier.citedreferenceWang N, Mirando AJ, Cofer G, Qi Y, Hilton MJ, Johnson GA. Characterization complex collagen fiber architecture in knee joint using high‐resolution diffusion imaging. Magn Reson Med. 2020; 84 ( 2 ): 908 ‐ 919. https://doi.org/10.1002/mrm.28181
dc.identifier.citedreferenceWei H, Gibbs E, Zhao P, et al. Susceptibility tensor imaging and tractography of collagen fibrils in the articular cartilage. Magn Reson Med. 2017; 78 ( 5 ): 1683 ‐ 1690.
dc.identifier.citedreferenceMlynarik V, Szomolanyi P, Toffanin R, Vittur F, Trattnig S. Transverse relaxation mechanisms in articular cartilage. J Magn Reson. 2004; 169 ( 2 ): 300 ‐ 307.
dc.identifier.citedreferenceBydder M, Rahal A, Fullerton GD, Bydder GM. The magic angle effect: A source of artifact, determinant of image contrast, and technique for imaging. J Magn Reson Imaging. 2007; 25 ( 2 ): 290 ‐ 300. https://doi.org/10.1002/jmri.20850
dc.identifier.citedreferenceFullerton GD. The magic angle effect in NMR and MRI of cartilage. In: Xia Y, Momot KI, eds. Biophysics and Biochemistry of Cartilage by NMR and MRI. Cambridge, UK: The Royal Society of Chemistry; 2016: 109 ‐ 144. https://doi.org/10.1039/9781782623663‐00109
dc.identifier.citedreferenceXia Y. Magic‐angle effect in magnetic resonance imaging of articular cartilage: a review. Invest Radiol. 2000; 35 ( 10 ): 602 ‐ 621.
dc.identifier.citedreferenceHanninen N, Rautiainen J, Rieppo L, Saarakkala S, Nissi MJ. Orientation anisotropy of quantitative MRI relaxation parameters in ordered tissue. Sci Rep. 2017; 7 ( 1 ): 1 ‐ 11.
dc.identifier.citedreferencePang Y. An order parameter without magic angle effect (OPTIMA) derived from R1ρ dispersion in ordered tissue. Magn Reson Med. 2020; 83 ( 5 ): 1783 ‐ 1795.
dc.identifier.citedreferenceFullerton GD, Rahal A. Collagen structure: The molecular source of the tendon magic angle effect. J Magn Reson Imaging. 2007; 25 ( 2 ): 345 ‐ 361. https://doi.org/10.1002/jmri.20808
dc.identifier.citedreferenceTourell MC, Momot KI. Molecular Dynamics of a Hydrated Collagen Peptide: Insights into Rotational Motion and Residence Times of Single‐Water Bridges in Collagen. J Phys Chem B. 2016; 120 ( 49 ): 12432 ‐ 12443. https://doi.org/10.1021/acs.jpcb.6b08499
dc.identifier.citedreferenceErickson SJ, Prost RW, Timins ME. The "magic angle" effect: background physics and clinical relevance.. Radiology. 1993; 188 ( 1 ): 23 ‐ 25. https://doi.org/10.1148/radiology.188.1.7685531
dc.identifier.citedreferenceBerendsen HJC. Nuclear magnetic resonance study of collagen hydration. J Chem Phys. 1962; 36 ( 12 ): 3297 ‐ 3305.
dc.identifier.citedreferenceTotland C, Nerdal W. Experimental Determination of Water Molecular Orientation near a Silica Surface Using NMR Spectroscopy. J Phys Chem C. 2016; 120 ( 9 ): 5052 ‐ 5058. https://doi.org/10.1021/acs.jpcc.6b00466
dc.identifier.citedreferenceFung B. Orientation of water in striated frog muscle. Science. 1975; 190 ( 4216 ): 800 ‐ 802.
dc.identifier.citedreferencePeto S, Gillis P, Henri VP. Structure and dynamics of water in tendon from NMR relaxation measurements. Biophys J. 1990; 57 ( 1 ): 71 ‐ 84. https://doi.org/10.1016/s0006‐3495(90)82508‐x
dc.identifier.citedreferenceLenk R, Bonzon M, Greppin H. Dynamically oriented biological water as studied by NMR. Chem Phy Lett. 1980; 76 ( 1 ): 175 ‐ 177.
dc.identifier.citedreferenceLink TM, Neumann J, Li X. Prestructural cartilage assessment using MRI. J Magn Reson Imaging. 2017; 45 ( 4 ): 949 ‐ 965. https://doi.org/10.1002/jmri.25554
dc.identifier.citedreferenceRoemer FW, Kijowski R, Guermazi A. Editorial: from theory to practice ‐ the challenges of compositional MRI in osteoarthritis research. Osteoarthr Cartil. 2017; 25 ( 12 ): 1923 ‐ 1925.
dc.identifier.citedreferenceLink TM, Li X. Establishing compositional MRI of cartilage as a biomarker for clinical practice. Osteoarthr Cartil. 2018; 26 ( 9 ): 1137 ‐ 1139.
dc.identifier.citedreferencePang Y, Palmieri‐Smith RM, Malyarenko DI, Swanson SD, Chenevert TL. A unique anisotropic R2 of collagen degeneration (ARCADE) mapping as an efficient alternative to composite relaxation metric (R2 ‐R1 rho) in human knee cartilage study. Magn Reson Med. 2019; 81 ( 6 ): 3763 ‐ 3774.
dc.identifier.citedreferenceMonk AP, Choji K, O’Connor JJ, Goodfellow† JW, Murray DW. The shape of the distal femur. Bone Joint J. 2014; 96‐B ( 12 ): 1623 ‐ 1630. https://doi.org/10.1302/0301‐620x.96b12.33964
dc.identifier.citedreferenceMorales Martinez A, Caliva F, Flament I, et al. Learning osteoarthritis imaging biomarkers from bone surface spherical encoding. Magn Reson Med. 2020; 84 ( 4 ): 2190 ‐ 2203. https://doi.org/10.1002/mrm.28251
dc.identifier.citedreferenceKaneko Y, Nozaki T, Yu H, et al. Normal T2 map profile of the entire femoral cartilage using an angle/layer‐dependent approach. J Magn Reson Imaging. 2015; 42 ( 6 ): 1507 ‐ 1516. https://doi.org/10.1002/jmri.24936
dc.identifier.citedreferenceMosher TJ, Smith H, Dardzinski BJ, Schmithorst VJ, Smith MB. MR imaging and T2 mapping of femoral cartilage: in vivo determination of the magic angle effect. Am J Roentgenol. 2001; 177 ( 3 ): 665 ‐ 669. https://doi.org/10.2214/ajr.177.3.1770665
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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