Validation of quantitative bound- and pore-water imaging in cortical bone.

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Title: Validation of quantitative bound- and pore-water imaging in cortical bone.
Authors: Manhard, Mary Kate1,2, Horch, R. Adam1,2, Harkins, Kevin D.2, Gochberg, Daniel F.2,3,4, Nyman, Jeffry S.1,5,6, Does, Mark D.1,2,3,7
Source: Magnetic Resonance in Medicine. Jun2014, Vol. 71 Issue 6, p2166-2171. 6p.
Abstract: Purpose To implement and validate a previously proposed ultra-short echo time method for measuring collagen-bound- and pore-water concentrations in bone based on their T2 differences. Methods Clinically compatible ultra-short echo time image sequences for quantitative T2-based bound and pore-water imaging in bone were implemented and validated on a 3T human scanner and a 4.7T small bore system. Bound- and pore-water images were generating using T2-selective adiabatic pulses. In both cases, the magnetization preparation was integrated into a three-dimensional ultra-short echo time acquisition, with 16 radial spokes acquired per preparation. Images were acquired from human cadaveric femoral mid-shafts from which isolated bone samples were subsequently extracted for nonimaging analysis using T2 spectroscopic measurements. Results A strong correlation was found between imaging-derived concentrations of bound and pore water and those determined from the isolated bone samples. Conclusions These studies demonstrate the translation of the previously developed approaches for distinguishing bound and pore water from human cortical bone using practical human MRI constraints of gradient performance and radiofrequency power deposition. Magn Reson Med 71:2166-2171, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Jun2014, Vol. 71 Issue 6, p2166-2171. 6p.
– Name: Abstract
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  Data: Purpose To implement and validate a previously proposed ultra-short echo time method for measuring collagen-bound- and pore-water concentrations in bone based on their T2 differences. Methods Clinically compatible ultra-short echo time image sequences for quantitative T2-based bound and pore-water imaging in bone were implemented and validated on a 3T human scanner and a 4.7T small bore system. Bound- and pore-water images were generating using T2-selective adiabatic pulses. In both cases, the magnetization preparation was integrated into a three-dimensional ultra-short echo time acquisition, with 16 radial spokes acquired per preparation. Images were acquired from human cadaveric femoral mid-shafts from which isolated bone samples were subsequently extracted for nonimaging analysis using T2 spectroscopic measurements. Results A strong correlation was found between imaging-derived concentrations of bound and pore water and those determined from the isolated bone samples. Conclusions These studies demonstrate the translation of the previously developed approaches for distinguishing bound and pore water from human cortical bone using practical human MRI constraints of gradient performance and radiofrequency power deposition. Magn Reson Med 71:2166-2171, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2014
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