Oscillating diffusion‐encoding with a high gradient‐amplitude and high slew‐rate head‐only gradient for human brain imaging

Tan, Ek Tsoon; Shih, Robert Y.; Mitra, Jhimli; Sprenger, Tim; Hua, Yaping; Bhushan, Chitresh; Bernstein, Matt A.; McNab, Jennifer A.; DeMarco, J. Kevin; Ho, Vincent B.; Foo, Thomas K.F.

doi:10.1002/mrm.28180

Cited by 23 publications

(46 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Linear trends of the diffusivities and FA were also reported in the only other OGSE study of the in vivo human brain using a high‐performance gradient system, 13 and general positive trends of these parameters were observed in several other in vivo human OGSE studies using standard gradient strengths 4,5,23 . Moreover, the b ‐value employed in this work surpasses those used previously by a factor of at least 2, permitting diffusion tensor computation with less bias by microcirculatory flow 22,25 …”

Section: Resultssupporting

confidence: 71%

“…For this reason, probing frequencies on human MRI systems have only recently reached 100 Hz with cosine-based (as opposed to sine-based) waveforms. 13 Furthermore, resolution of the entire accessible spectral range requires probing of frequencies as low as 20-30 Hz. To keep the sequence duration comparable to the range of T 2 values within the brain, these low-frequency OGSE scans must use single-period pulses.…”

Section: Introductionmentioning

confidence: 99%

“…The main limitation of OGSE is the rapid decrease of the b ‐value (ie the integral of k 2 ( t )), and, therefore, of the sensitivity of the experiment with increasing oscillation frequency; at constant amplitude and duration of the OGSE pulses, the b ‐value is roughly proportional to ω −2 . For this reason, probing frequencies on human MRI systems have only recently reached 100 Hz with cosine‐based (as opposed to sine‐based) waveforms 13 . Furthermore, resolution of the entire accessible spectral range requires probing of frequencies as low as 20‐30 Hz.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Improved gradient waveforms for oscillating gradient spin‐echo (OGSE) diffusion tensor imaging

2020

View full text Add to dashboard Cite

The dependence of the diffusion tensor on frequency is of great interest in studies of tissue microstructure because it reveals restrictions to the Brownian motion of water molecules caused by cell membranes. Oscillating gradient spin‐echo (OGSE) sequences can sample this dependence with gradient shapes for which the power spectrum of the zeroth moment is focused at a target frequency. In order to maintain the total spectral power (ie the b‐value), oscillating gradient amplitudes must grow with the frequency squared. For this reason, OGSE applications on clinical MRI scanners are limited to low frequencies, for which it is difficult to obtain a narrow frequency bandwidth of the gradient moment in a useful echo time. In particular, the commonly used pair of single‐period trapezoidal‐cosine pulses separated by a half‐period produces significant side lobes away from the target frequency. To mitigate this effect, improved OGSE waveforms are proposed, which reduce the gap between the two gradient pulses to the minimum duration required for the refocusing RF pulse. Additionally, a slight deviation from the periodicity of the waveforms is proposed in order to permit using the maximum slew rate of the gradient system for all lobes of trapezoidal waveforms while maintaining advantageous spectral properties, which is not the case for the currently used OGSE sequences. Numerical calculations validate these changes, showing that both modifications significantly narrow the gradient moment power spectrum and increase the contribution of its main lobe to the b‐value, thus improving the specificity of the measurement. The utility of the new shapes is demonstrated by diffusion tensor measurements of human white matter in vivo over the range of 30‐75 Hz with a b‐value of nearly 1000 s/mm2, using a high‐performance gradient insert. However, the improvement should increase the sampling precision of OGSE experiments for all gradient systems.

show abstract

Section: Resultssupporting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improved gradient waveforms for oscillating gradient spin‐echo (OGSE) diffusion tensor imaging

2020

View full text Add to dashboard Cite

show abstract

“…In addition, despite the improvement in scan time and SNR, the attainable oscillating frequency is still limited to approximately 50 Hz with a moderate b-value. Advances in hardware, such as the Connectome scanner 71 and headonly gradient coil, 35 together with the improvement in pulse sequences 72,73 and gradient optimization techniques 74 that reduce the peripheral nerve stimulation, would make timedependent diffusion dMRI ready for clinical studies.…”

Section: Discussionmentioning

confidence: 99%

“…This leads to a limited capacity to access shorter diffusion times, [24][25][26][27] as the effective diffusion time is approximately 1/4f. 8 Nevertheless, recent studies have investigated the feasibility and utility of OG-dMRI on clinical systems, [24][25][26][27][28][29][30][31][32][33][34][35] given the limited oscillating frequencies and b-values. For example, Xu et al 32 demonstrated that on a 3T clinical scanner, cell size could be accurately estimated in breast cancer with a simplified PG-dMRI and OG-dMRI protocol and an advanced biophysical model.…”

Section: Introductionmentioning

confidence: 99%

Diffusion‐prepared 3D gradient spin‐echo sequence for improved oscillating gradient diffusion MRI

Liu

Hsu

et al. 2020

Magnetic Resonance in Med

View full text Add to dashboard Cite

Oscillating gradient (OG) enables the access of short diffusion times for time-dependent diffusion MRI (dMRI); however, it poses several technical challenges for clinical use. This study proposes a 3D oscillating gradient-prepared gradient spin-echo (OGprep-GRASE) sequence to improve SNR and shorten acquisition time for OG dMRI on clinical scanners. Methods: The 3D OGprep-GRASE sequence consisted of global saturation, diffusion encoding, fat saturation, and GRASE readout modules. Multiplexed sensitivityencoding reconstruction was used to correct the phase errors between multiple shots. We compared the scan time and SNR of the proposed sequence and the conventional 2D-EPI sequence for OG dMRI at 30-90-mm slice coverage. We also examined the time-dependent diffusivity changes with OG dMRI acquired at frequencies of 50 Hz and 25 Hz and pulsed-gradient dMRI at diffusion times of 30 ms and 60 ms. Results: The OGprep-GRASE sequence reduced the scan time by a factor of 1.38, and increased the SNR by 1.74-2.27 times compared with 2D EPI for relatively thick slice coverage (60-90 mm). The SNR gain led to improved diffusion-tensor reconstruction in the multishot protocols. Image distortion in 2D-EPI images was also reduced in GRASE images. Diffusivity measurements from the pulsed-gradient dMRI and OG dMRI showed clear diffusion-time dependency in the white matter and gray matter of the human brain, using both the GRASE and EPI sequences. Conclusion: The 3D OGprep-GRASE sequence improved scan time and SNR and reduced image distortion compared with the 2D multislice acquisition for OG dMRI on a 3T clinical system, which may facilitate the clinical translation of timedependent dMRI.

show abstract

Evaluating diffusion dispersion across an extended range of b‐values and frequencies: Exploiting gap‐filled OGSE shapes, strong gradients, and spiral readouts

Michael

Hennel

Pruessmann

2022

Magnetic Resonance in Med

View full text Add to dashboard Cite

To address the long echo times and relatively weak diffusion sensitization that typically limit oscillating gradient spin-echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap-filled oscillating gradient shapes providing stronger diffusion encoding, and a high-performance gradient system is developed here and utilized to investigate the tradeoff between b-value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow-compensated variants are devised for experimental comparison.Methods: Using DTI sequences, OGSE acquisitions were performed on three volunteers at b-values of 300, 500, and 1000 s/mm 2 and frequencies up to 125, 100, and 75 Hz, respectively; scans were performed for gap-filled oscillating gradient shapes with and without flow sensitivity. Pulsed gradient spin-echo DTI acquisitions were also performed at each b-value. Upon reconstruction, mean diffusivity (MD) maps and maps of the diffusion dispersion rate were computed. Results:The power law diffusion dispersion model was found to fit best to MD measurements acquired at b = 1000 s/mm 2 despite the associated reduction of the spectral range; this observation was consistent with Monte Carlo simulations.Furthermore, diffusion dispersion rates without flow sensitivity were slightly higher than flow-sensitive measurements. Conclusion:The presented OGSE implementation provided an improved depiction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b-values rather than higher frequencies within the regimes employed in this study.

show abstract

Oscillating diffusion‐encoding with a high gradient‐amplitude and high slew‐rate head‐only gradient for human brain imaging

Cited by 23 publications

References 40 publications

Improved gradient waveforms for oscillating gradient spin‐echo (OGSE) diffusion tensor imaging

Improved gradient waveforms for oscillating gradient spin‐echo (OGSE) diffusion tensor imaging

Diffusion‐prepared 3D gradient spin‐echo sequence for improved oscillating gradient diffusion MRI

Evaluating diffusion dispersion across an extended range of b‐values and frequencies: Exploiting gap‐filled OGSE shapes, strong gradients, and spiral readouts

Contact Info

Product

Resources

About