MTF behavior of compressed sensing MR spectroscopic imaging

Heikal, Amr; Wachowicz, Keith; Fallone, B. G.

doi:10.1118/1.4800642

Cited by 6 publications

(14 citation statements)

References 27 publications

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“…In such cases, the reconstruction algorithm would need to be tailored to ensure a reliable representation of low‐concentration metabolites at higher accelerations, especially when the acquired MRSI data are SNR limited. Other areas of ongoing research involve determining the best pseudo‐random undersampling mask tailored to MRSI at each acceleration factor, and investigating the potential impact of CS reconstruction on the low spatial resolution in MRSI …”

Section: Doing More With Less Data: Fast Mrsi With Undersamplingmentioning

confidence: 99%

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Fast data acquisition techniques in magnetic resonance spectroscopic imaging

Shankar

Chang

et al. 2019

NMR in Biomedicine

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Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal‐to‐noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k‐space. Techniques such as fast/turbo‐spin echo MRSI, echo‐planar spectroscopic imaging, and non‐Cartesian MRSI effectively cover the full k‐space in a more efficient manner per TR. On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k‐space points and employ advanced reconstruction algorithms to recreate the spatial‐spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel‐wise comparisions) with the fully sampled data. The advantages and limitations of each state‐of‐the‐art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.

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Section: Doing More With Less Data: Fast Mrsi With Undersamplingmentioning

confidence: 99%

“…Other areas of ongoing research involve determining the best pseudo-random undersampling mask tailored to MRSI at each acceleration factor, 143 and investigating the potential impact of CS reconstruction on the low spatial resolution in MRSI. 144…”

Section: Figure 11mentioning

confidence: 99%

Fast data acquisition techniques in magnetic resonance spectroscopic imaging

Shankar

Chang

et al. 2019

NMR in Biomedicine

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“…From the artifact power analysis, it is clear that the 2D-CS method is relatively sensitive to the degree of undersampling of k-space. Heikal et al 25 have shown that undersampling in compressed sensing causes quantifiable loss in spatial frequency response (as described by its modulation transfer function) in reconstructed image. At low acceleration, the sampling pattern still has a significant amount of sampled data points in the high frequency regions (Fig.…”

Section: A Performance Dependence On Acceleration Factors-high Snrmentioning

confidence: 99%

Prior data assisted compressed sensing: A novel MR imaging strategy for real time tracking of lung tumors

et al. 2014

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The PDACS method can potentially improve the real time tracking of moving tumors by significantly increasing MRI's data acquisition speeds. In 3T images, the PDACS method does provide a benefit over the other two methods in terms of both the overall image quality and the ability to accurately and automatically contour the tumor shape. MRI's data acquisition may be accelerated using the simpler viewsharing strategy at the lower, 0.5T magnetic field, as the marginal benefit of the PDACS method may not justify its additional reconstruction times.

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“…Recently, a method has been introduced in the literature to quantify the MTF of MRSI scans and to provide a quantitative measure of the cost and benefit of CS-MRSI. 6 At first glance, the validity of MTF as a metric for linear systems would appear to be at odds with the nonlinearity of the CS reconstruction. However, previous work has shown that when the reconstruction weights are carefully chosen, a robustness of the spatial frequency response of the system with different noise levels can be established.…”

Section: Introductionmentioning

confidence: 99%