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

Wu, Dan; Liu, Dapeng; Hsu, Yi Cheng; Li, Haotian; Sun, Yi; Qin, Qin; Zhang, Yi

doi:10.1002/mrm.28401

Cited by 16 publications

(26 citation statements)

References 71 publications

(118 reference statements)

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“…All scans were performed with a 3.0-T MRI scanner (Skyra, Siemens Healthcare) with maximum gradient of 45 mT/m and maximum slew rate of 200 mT/m/msec, with the participant in the supine position and using an external pelvic phased-array coil. An in-house OGSE diffusion MRI sequence (25) was implemented with trapezoid-cosine gradients and echo-planar imaging acquisition. OGSE data were acquired at oscillating frequencies of 33 Hz (effective diffusion time = 7.5 msec, two cycles, b = 300 and 600 sec/mm 2 ) and 17 Hz (effective diffusion time = 15 msec, one cycle, b = 400, 800, and 1200 sec/mm 2 ), and pulsed gradient spin-echo at diffusion duration and separation of 10 and 30 msec, respectively (effective diffusion time = 26.7 msec, b = 400, 800, and 1200 sec/mm 2 ).…”

Section: Image Acquisitionmentioning

confidence: 99%

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer

Jiang

et al. 2022

Radiology

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GENITOURINARY IMAGING P rostate cancer (PCa) is the fourth most commonly diagnosed cancer and ranked eighth among the leading causes of cancer-related deaths worldwide (1). The aggressiveness of PCa is indicated by the Gleason score (GS), which is important for guiding management and predicting clinical outcome (2). Previous studies have demonstrated that GS is closely associated with pathologic characteristics in PCa. For instance, the proliferation of epithelial cells and tumor cells and reduced stroma and lumen volumes are hallmarks of high-risk PCa (3).Multiparametric MRI, especially diffusion MRI, plays an indispensable role, given its high sensitivity for PCa detection (4,5). The diffusion MRI-derived apparent diffusion coefficient (ADC) is traditionally considered to reflect the cellularity of tumors based on empirical observations (3). However, ADC is only an overall measure of the water diffusivity that is determined by multiple microstructural features, such as the intra-and extracellular space, cell size, permeability, and intrinsic diffusivity. More specific imaging markers for characterizing specific tumor microstructure are urgently needed for precise description of the pathologic characteristics of PCa.Progress in multidimensional diffusion MRI has enhanced our capacity to probe tissue microstructure by using different diffusion weightings (q-space) and varying diffusion times (t-space) (6), opening new avenues in PCa research (7-10). Particularly, the recent development of time-dependent diffusion MRI has demonstrated unique advantages in depicting cellular microstructures by characterizing the diffusion time dependence of restricted water diffusion and relating the diffusion time dependence to specific microstructural parameters (11,12). Background: Recently developed time-dependent diffusion MRI has potential in characterizing cellular tissue microstructures; however, its value in imaging prostate cancer (PCa) remains unknown. Purpose: To investigate the feasibility of time-dependent diffusion MRI-based microstructural mapping for noninvasively characterizing cellular properties of PCa and for discriminating between clinically significant PCa and clinically insignificant disease. Materials and Methods:Men with a clinical suspicion of PCa were enrolled prospectively between October 2019 and August 2020. Time-dependent diffusion MRI data were acquired with pulsed and oscillating gradient diffusion MRI sequences at an equivalent diffusion time of 7.5-30 msec on a 3.0-T scanner. Time-dependent diffusion MRI-based microstructural parameters, including cell diameter, intracellular volume fraction, cellularity, and diffusivities, were estimated with a two-compartment model. These were compared for different International Society of Urological Pathology grade groups (GGs), and their performance in discriminating clinically significant PCa (GG .1) from clinically insignificant disease (benign and GG 1) was determined with a linear discriminant analysis. The fitted microstructural parameters were validate...

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Section: Image Acquisitionmentioning

confidence: 99%

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer

Jiang

et al. 2022

Radiology

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“…This improvement, however, adds a marginal flow sensitivity, which has not been fully investigated. In the direction of readout efficiency, a diffusion‐prepared 3D gradient spin‐echo sequence for oscillating diffusion gradients has been proposed to reduce overall scan time and improve the SNR 15 . Another potential avenue for readout‐based sensitivity improvements would be to use spiral trajectories; to date, EPI is the only single‐shot readout trajectory that has been used with OGSE.…”

Section: Introductionmentioning

confidence: 99%

“…In the direction of readout efficiency, a diffusion‐prepared 3D gradient spin‐echo sequence for oscillating diffusion gradients has been proposed to reduce overall scan time and improve the SNR. 15 Another potential avenue for readout‐based sensitivity improvements would be to use spiral trajectories; to date, EPI is the only single‐shot readout trajectory that has been used with OGSE. Compared with EPI, spiral readouts can provide a considerable SNR advantage because spirals have shorter TEs and better readout efficiency, among other favorable effects.…”

Section: Introductionmentioning

confidence: 99%

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

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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.

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“…First, stabilizer (or crusher) gradients were introduced to the diffusion prepared sequences to spoil the phase before the tip up pulse in the diffusion preparation and restore it after each excitation in the SSFP acquisition, in order to maintain the correct signal magnitude. 37,54,66 One can then directly use the magnitude-only analysis or correct the phase errors separately. The main drawback of this approach is the signal loss due to repeated crusher gradients in each acquisition window, resulting in low SNR of the entire diffusion weighted signal.…”

Section: Discussionmentioning

confidence: 99%

“…Diffusion‐weighted scans can be highly sensitive to phase errors, such as those resulting from eddy current and physiological motions (cardiac pulsation). In this study, three MRF readout designs (gray section of Figure 1A) were implemented to investigate the robustness of the resulting maps to measurement errors: (1) conventional FISP‐based MRF readouts, 52 (2) FLASH‐based MRF readouts with RF and gradient spoiling, as well as phase stabilizers that are commonly used in the diffusion‐prepared sequences 37,53–56 . The phase stabilizers (4pi dephasing) were implemented before the −90 degrees tip‐up pulse of each diffusion preparation module and after each RF pulse of the MRF readout within diffusion acquisition segments.…”

Section: Methodsmentioning

confidence: 99%

MR Fingerprinting with b‐Tensor Encoding for Simultaneous Quantification of Relaxation and Diffusion in a Single Scan

Afzali

Mueller

Sakaie

et al. 2022

Magnetic Resonance in Med

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Although both relaxation and diffusion imaging are sensitive to tissue microstructure, studies have reported limited sensitivity and robustness of using relaxation or conventional diffusion alone to characterize tissue microstructure. Recently, it has been shown that tensor-valued diffusion encoding and joint relaxation-diffusion quantification enable more reliable quantification of compartment-specific microstructural properties. However, scan times to acquire such data can be prohibitive. Here, we aim to simultaneously quantify relaxation and diffusion using MR fingerprinting (MRF) and b-tensor encoding in a clinically feasible time. Methods:We developed multidimensional MRF scans (mdMRF) with linear and spherical b-tensor encoding (LTE and STE) to simultaneously quantify T1, T2, and ADC maps from a single scan. The image quality, accuracy, and scan efficiency were compared between the mdMRF using LTE and STE. Moreover, we investigated the robustness of different sequence designs to signal errors and their impact on the maps.Results: T1 and T2 maps derived from the mdMRF scans have consistently high image quality, while ADC maps are sensitive to different sequence designs. Notably, the fast imaging steady state precession (FISP)-based mdMRF scan with peripheral pulse gating provides the best ADC maps that are free of image distortion and shading artifacts. Conclusion:We demonstrated the feasibility of quantifying T1, T2, and ADC maps simultaneously from a single mdMRF scan in around 24 s/slice.The map quality and quantitative values are consistent with the reference scans.

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

Cited by 16 publications

References 71 publications

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer

Time-Dependent Diffusion MRI for Quantitative Microstructural Mapping of Prostate Cancer

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

MR Fingerprinting with b‐Tensor Encoding for Simultaneous Quantification of Relaxation and Diffusion in a Single Scan

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