Optimization of undersampling parameters for <scp>3D</scp> intracranial compressed sensing <scp>MR</scp> angiography at 7 T

Buck, Matthijs H. S.; Jezzard, Peter; Hess, Aaron T.

doi:10.1002/mrm.29236

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…Maximum intensity projection (MIP) images were generated from the source images of the TOF MRA. As previous work reported that the vessel‐masked structural similarity index measure (SSIM) well correlates with visual assessment by radiologists when evaluating the reconstructions from retrospectively undersampled TOF MRA dataset, 13 , 34 we adopted the vessel‐masked SSIM in addition to a standard SSIM in this study to assess the accuracy of the reconstruction from retrospectively undersampling. Additionally, CBR, SSIM, and vessel‐masked SSIM metrics were compared between different accelerated sampling schemes using a two‐tailed paired t test with Bonferroni correction, and adjusted P values less than 0.05 were considered statistically significant ( N = 6).…”

Section: Methodsmentioning

confidence: 99%

Highly accelerated intracranial time‐of‐flight magnetic resonance angiography using wave‐encoding

Buck

et al. 2023

Magnetic Resonance in Med

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To develop an accelerated 3D intracranial time-of-flight (TOF) magnetic resonance angiography (MRA) sequence with wave-encoding (referred to as 3D wave-TOF) and to evaluate two variants: wave-controlled aliasing in parallel imaging (CAIPI) and compressed-sensing wave (CS-wave).Methods: A wave-TOF sequence was implemented on a 3 T clinical scanner. Wave-encoded and Cartesian k-space datasets from six healthy volunteers were retrospectively and prospectively undersampled with 2D-CAIPI sampling and variable-density Poisson disk sampling. 2D-CAIPI, wave-CAIPI, standard CS, and CS-wave schemes were compared at various acceleration factors. Flow-related artifacts in wave-TOF were investigated, and a set of practicable wave parameters was developed. Quantitative analysis of wave-TOF and traditional Cartesian TOF MRA was performed by comparing the contrast-to-background ratio between the vessel and background tissue in source images, and the structural similarity index measure (SSIM) between the maximum intensity projection images from accelerated acquisitions and their respective fully sampled references.Results: Flow-related artifacts caused by the wave-encoding gradients in wave-TOF were eliminated by properly chosen parameters. Images from wave-CAIPI and CS-wave acquisitions had a higher SNR and better-preserved contrast than traditional parallel imaging (PI) and CS methods. Maximum intensity projection images from wave-CAIPI and CS-wave acquisitions had a cleaner background, with vessels that were better depicted. Quantitative analyses indicated that wave-CAIPI had the highest contrast-to-background ratio, SSIM, and vessel-masked SSIM among the sampling schemes studied, followed by the CS-wave acquisition. Conclusion: 3D wave-TOF improves the capability of accelerated MRA and provides better image quality at higher acceleration factors compared to traditional PI-or CS-accelerated TOF, suggesting the potential use of wave-TOF in cerebrovascular disease. K E Y W O R D S 3D time-of-flight, compressed sensing, CS-wave, MR angiography, wave-CAIPI This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Methodsmentioning

confidence: 99%

Highly accelerated intracranial time‐of‐flight magnetic resonance angiography using wave‐encoding

Buck

et al. 2023

Magnetic Resonance in Med

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“…An acceleration factor larger than seven has been achieved on 7 T TOF‐MRA, 36 enabling a 0.3 mm isotropic acquisition covering the whole LSAs in less than 8 minutes 36 . The image quality may be further improved by the appropriate choice of under‐sampling parameters 41 …”

Section: Time‐of‐flight Mr Angiographymentioning

confidence: 99%

“…36 The image quality may be further improved by the appropriate choice of undersampling parameters. 41 TOF-MRA is mainly used to analyze the anatomical structures of cerebral arteries. The diameters and degree of stenosis can be measured on TOF-MRA.…”

Section: Time-of-flight Mr Angiographymentioning

confidence: 99%

Visualizing Cerebral Small Vessel Degeneration During Aging and Diseases Using Magnetic Resonance Imaging

Huang

Chen

Liu

et al. 2023

Magnetic Resonance Imaging

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Cerebral small vessel disease is a major contributor to brain disorders in older adults. It is associated with a much higher risk of stroke and dementia. Due to a lack of clinical and fluid biomarkers, diagnosing and grading small vessel disease are highly dependent on magnetic resonance imaging. In the past, researchers mostly used brain parenchymal imaging markers to represent small vessel damage, but the relationships between these surrogate markers and small vessel pathologies are complex. Recent progress in high‐resolution magnetic resonance imaging methods, including time‐of‐flight MR angiography, phase‐contrast MR angiography, black blood vessel wall imaging, susceptibility‐weighted imaging, and contrast‐enhanced methods, allow for direct visualization of cerebral small vessel structures. They could be powerful tools for understanding aging‐related small vessel degeneration and improving disease diagnosis and treatment. This article will review progress in these imaging techniques and their application in aging and disease studies. Some challenges and future directions are also discussed.Evidence Level4.Technical Efficacy3.

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“…CS was first introduced for 1 H MRI, but CS validity has also been investigated with non‐proton MRI such as helium‐3, 11 fluorine‐19, 12 carbon‐13, 13 sodium‐23, 14 and xenon‐129 15,16 . Although these studies showed good agreement between fully and undersampled images, the quality of images reconstructed by CS depends strongly on multiple factors and has several drawbacks: (1) sparse transformations can be insufficient for representing complex image components and result in artifacts, particularly in medical imaging; (2) CS employs iterative procedures, which are costly and often result in oversmoothed images; (3) hyperparameters such as updating rates, weighting factors, and so on must be selected manually, which takes time and can differ depending on the patient and anatomy being assessed 17 . To our knowledge, there is no conclusive information about the effect of suboptimal sampling patterns for CS HP 129 Xe lung MRI 18 .…”

Section: Introductionmentioning

confidence: 99%

Sampling pattern discrepancy in the application of compressed sensing hyperpolarized xenon‐129 lung MRI

Tavakkoli,

Svenningsen,

Friedlander

et al. 2024

NMR in Biomedicine

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Although hyperpolarized (HP) 129Xe ventilation MRI can be carried out within a breath hold, it is still challenging for many sick patients. Compressed sensing (CS) is a viable alternative to accelerate this approach. However, undersampled images with identical sampling ratios differ from one another. Twenty subjects (n = 10 healthy and n = 10 patients with asthma) were scanned using a GE MR750 3 T scanner, acquiring fully sampled 2D multi‐slice HP 129Xe lung ventilation images (10 s breath hold, 128 × 80 (FE × PE—frequency encoding × phase encoding) and 16 slices). Using fully sampled data, 500 variable‐density Cartesian random undersampling patterns were generated, each at eight different sampling ratios from 10% to 80%. The parallel imaging and compressed sensing (PICS) command from BART was employed to reconstruct undersampled data. The signal to noise ratio (SNR), structural similarity index measurement (SSIM) and sidelobe to peak ratio of each were subsequently compared. There was a high degree of variation in both SNR and SSIM results from each of the 500 masks of each sampling rate. As the undersampling increases, there is more variation in the quantifying metrics, for both healthy and asthmatic individuals. Our study shows that random undersampling poses a significant challenge when applied at sampling ratios less than 60%, despite fulfilling CS's incoherency criteria. Such low sampling ratios will result in a large variety of undersampling patterns. Therefore, skipped segments of k‐space cannot be allowed to happen randomly at low sampling rates. By optimizing the sampling pattern, CS will reach its full potential and be able to be applied to a highly undersampled 129Xe lung dataset.

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Optimization of undersampling parameters for 3D intracranial compressed sensing MR angiography at 7 T

Cited by 6 publications

References 33 publications

Highly accelerated intracranial time‐of‐flight magnetic resonance angiography using wave‐encoding

Highly accelerated intracranial time‐of‐flight magnetic resonance angiography using wave‐encoding

Visualizing Cerebral Small Vessel Degeneration During Aging and Diseases Using Magnetic Resonance Imaging

Sampling pattern discrepancy in the application of compressed sensing hyperpolarized xenon‐129 lung MRI

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