Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

Zhang, Tao; Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y.; Alley, Marcus T.; Lustig, Michael; Pauly, John M.; Vasanawala, Shreyas S.

doi:10.1007/s00247-015-3384-y

Cited by 13 publications

(4 citation statements)

References 41 publications

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“…The 4D flow MRI technique we used combined spiral‐like view ordering with golden‐angle permutation and soft gating to compensate for respiratory and cardiac motion without the use of external tracking devices. This technique has previously been evaluated in pediatric populations, 23,27 however it has not been previously applied to adults which offer unique challenges in MRI, for example due to larger average patient size placing surface coils further from the vasculature of interest. Acceleration allowed acquisition of high resolution volumetric 4D flow data over the entire abdomen in 10 minutes.…”

Section: Discussionmentioning

confidence: 99%

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Brunsing

Brown

Almahoud

et al. 2021

Magnetic Resonance Imaging

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Background Non‐invasive assessment of the hemodynamic changes of cirrhosis might help guide management of patients with liver disease but are currently limited. Purpose To determine whether free‐breathing 4D flow MRI can be used to quantify the hemodynamic effects of cirrhosis and introduce hydraulic circuit indexes of severity. Study Type Retrospective. Population Forty‐seven patients including 26 with cirrhosis. Field Strength/Sequence 3 T/free‐breathing 4D flow MRI with soft gating and golden‐angle view ordering. Assessment Measurements of the supra‐celiac abdominal aorta, supra‐renal abdominal aorta (SRA), celiac trunk (CeT), superior mesenteric artery (SMA), splenic artery (SpA), common hepatic artery (CHA), portal vein (PV), and supra‐renal inferior vena cava (IVC) were made by two radiologists. Measures of hepatic vascular resistance (hepatic arterial relative resistance [HARR]; portal resistive index [PRI]) were proposed and calculated. Statistical Analysis Bland–Altman, Pearson's correlation, Tukey's multiple comparison, and Cohen's kappa. P < 0.05 was considered significant. Results Forty‐four of 47 studies yielded adequate image quality for flow quantification (94%). Arterial structures showed high inter‐reader concordance (range; ρ = 0.948–0.987) and the IVC (ρ = 0.972), with moderate concordance in the PV (ρ = 0.866). Conservation of mass analysis showed concordance between large vessels (SRA vs. IVC; ρ = 0.806), small vessels (celiac vs. CHA + SpA; ρ = 0.939), and across capillary beds (CeT + SMA vs. PV; ρ = 0.862). Splanchnic flow was increased in patients with portosystemic shunting (PSS) relative to control patients and patients with cirrhosis without PSS (P < 0.05, difference range 0.11–0.68 liter/m). HARR was elevated and PRI was decreased in patients with PSS (3.55 and 1.49, respectively) compared to both the control (2.11/3.18) and non‐PSS (2.11/2.35) cohorts. Data Conclusion 4D flow MRI with self‐navigation was technically feasible, showing promise in quantifying the hemodynamic effects of cirrhosis. Proposed quantitative metrics of hepatic vascular resistance correlated with PSS. Level of Evidence 3 Technical Efficacy Stage 2

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Section: Discussionmentioning

confidence: 99%

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Brunsing

Brown

Almahoud

et al. 2021

Magnetic Resonance Imaging

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“…Abdominal MR angiography poses the twin challenges of rapid contrast dynamics and a need for very large field of view coverage. Thus significant efforts to use sparse reconstruction techniques for acceleration in the abdomen are underway, both in adults and children 110 .…”

Section: Clinical Applications Of Sparse Reconstruction Techniquesmentioning

confidence: 99%

Sparse Reconstruction Techniques in Magnetic Resonance Imaging

Yang

Kretzler

Sudarski

et al. 2016

Investigative Radiology

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The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in Magnetic Resonance Imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be employed to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MR imaging, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold-standards, are discussed.

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“…Numerous researchers [48,50,49,45,18] have been conducting MR imaging experiments where one dimension is sampled exhaustively and the others are sampled at random, and in some cases uniformly at random exactly as discussed here; see for example [29].…”

Section: Stylized Application To Mr Imagingmentioning

confidence: 99%

Sparsity/undersampling tradeoffs in anisotropic undersampling, with applications in MR imaging/spectroscopy

Monajemi

Donoho

2018

Information and Inference: A Journal of the IMA

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We study anisotropic undersampling schemes like those used in multi-dimensional NMR spectroscopy and MR imaging, which sample exhaustively in certain time dimensions and randomly in others.Our analysis shows that anisotropic undersampling schemes are equivalent to certain block-diagonal measurement systems. We develop novel exact formulas for the sparsity/undersampling tradeoffs in such measurement systems, assuming uniform sparsity fractions in each column. Our formulas predict finite-N phase transition behavior differing substantially from the well-known asymptotic phase transitions for classical Gaussian undersampling. Extensive empirical work shows that our formulas accurately describe observed finite-N behavior, while the usual formulas based on universality are substantially inaccurate at the moderate N involved in realistic applications.We also vary the anisotropy, keeping the total number of samples fixed, and for each variation we determine the precise sparsity/undersampling tradeoff (phase transition). We show that, other things being equal, the ability to recover a sparse object decreases with an increasing number of exhaustively sampled dimensions. keywords: Sparse Recovery, Compressed Sensing, Block Diagonal Measurement Matrix. 1 * asy (δ), then, with overwhelming probability, convex optimization will fail.Exact expressions for the boundary * asy (δ) separating success from failure were derived in [6,11] assuming the measurement matrix is Gaussian and the problem size N is large. In [12,14] those same expressions were experimentally observed to also describe accurately many non-Gaussian random measurement schemes. Thorough mathematical analysis now fully supports all these findings across very large classes of random matrices [2,40]. We would also like to thank the Stanford Research Computing Center for providing computational resources and support that were essential to these research results. Thanks also to the anonymous referees for many thoughtful comments.

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Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

Cited by 13 publications

References 41 publications

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Quantification of the Hemodynamic Changes of Cirrhosis with Free‐Breathing Self‐Navigated MRI

Sparse Reconstruction Techniques in Magnetic Resonance Imaging

Sparsity/undersampling tradeoffs in anisotropic undersampling, with applications in MR imaging/spectroscopy

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