Literature DB >> 28328013

Validation of surface-to-volume ratio measurements derived from oscillating gradient spin echo on a clinical scanner using anisotropic fiber phantoms.

Gregory Lemberskiy1,2, Steven H Baete1, Martijn A Cloos1, Dmitry S Novikov1, Els Fieremans1.   

Abstract

A diffusion measurement in the short-time surface-to-volume ratio (S/V) limit (Mitra et al., Phys Rev Lett. 1992;68:3555) can disentangle the free diffusion coefficient from geometric restrictions to diffusion. Biophysical parameters, such as the S/V of tissue membranes, can be used to estimate microscopic length scales non-invasively. However, due to gradient strength limitations on clinical MRI scanners, pulsed gradient spin echo (PGSE) measurements are impractical for probing the S/V limit. To achieve this limit on clinical systems, an oscillating gradient spin echo (OGSE) sequence was developed. Two phantoms containing 10 fiber bundles, each consisting of impermeable aligned fibers with different packing densities, were constructed to achieve a range of S/V values. The frequency-dependent diffusion coefficient, D(ω), was measured in each fiber bundle using OGSE with different gradient waveforms (cosine, stretched cosine, and trapezoidal), while D(t) was measured from PGSE and stimulated-echo measurements. The S/V values derived from the universal high-frequency behavior of D(ω) were compared against those derived from quantitative proton density measurements using single spin echo (SE) with varying echo times, and from magnetic resonance fingerprinting (MRF). S/V estimates derived from different OGSE waveforms were similar and demonstrated excellent correlation with both SE- and MRF-derived S/V measures (ρ  ≥  0.99). Furthermore, there was a smoother transition between OGSE frequency f and PGSE diffusion time when using teffS/V=9/64f, rather than the commonly used teff  = 1/(4f), validating the specific frequency/diffusion time conversion for this regime. Our well-characterized fiber phantom can be used for the calibration of OGSE and diffusion modeling techniques, as the S/V ratio can be measured independently using other MR modalities. Moreover, our calibration experiment offers an exciting perspective of mapping tissue S/V on clinical systems.
Copyright © 2017 John Wiley & Sons, Ltd.

Entities:  

Keywords:  OGSE diffusion; STEAM diffusion; anisotropic diffusion phantom; magnetic resonance fingerprinting; surface to volume ratio

Mesh:

Substances:

Year:  2017        PMID: 28328013      PMCID: PMC5501714          DOI: 10.1002/nbm.3708

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  46 in total

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Review 2.  Techniques and applications of skeletal muscle diffusion tensor imaging: A review.

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Authors:  Emine U Saritas; Patrick W Goodwill; Steven M Conolly
Journal:  Med Phys       Date:  2015-06       Impact factor: 4.071

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Authors:  J E Tanner
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7.  Surface-to-volume ratio mapping of tumor microstructure using oscillating gradient diffusion weighted imaging.

Authors:  Olivier Reynaud; Kerryanne Veronica Winters; Dung Minh Hoang; Youssef Zaim Wadghiri; Dmitry S Novikov; Sungheon Gene Kim
Journal:  Magn Reson Med       Date:  2015-07-24       Impact factor: 4.668

8.  In vivo investigation of restricted diffusion in the human brain with optimized oscillating diffusion gradient encoding.

Authors:  Anh T Van; Samantha J Holdsworth; Roland Bammer
Journal:  Magn Reson Med       Date:  2013-02-27       Impact factor: 4.668

9.  Exact analytical results for ADC with oscillating diffusion sensitizing gradients.

Authors:  A L Sukstanskii
Journal:  J Magn Reson       Date:  2013-06-29       Impact factor: 2.229

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Authors:  Dan Ma; Vikas Gulani; Nicole Seiberlich; Kecheng Liu; Jeffrey L Sunshine; Jeffrey L Duerk; Mark A Griswold
Journal:  Nature       Date:  2013-03-14       Impact factor: 49.962

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  3 in total

Review 1.  On modeling.

Authors:  Dmitry S Novikov; Valerij G Kiselev; Sune N Jespersen
Journal:  Magn Reson Med       Date:  2018-03-01       Impact factor: 4.668

Review 2.  Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook.

Authors:  Els Fieremans; Hong-Hsi Lee
Journal:  Neuroimage       Date:  2018-06-18       Impact factor: 6.556

Review 3.  Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation.

Authors:  Dmitry S Novikov; Els Fieremans; Sune N Jespersen; Valerij G Kiselev
Journal:  NMR Biomed       Date:  2018-10-15       Impact factor: 4.044

  3 in total

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