An Augmented Lagrangian Based Compressed Sensing Reconstruction for Non-Cartesian Magnetic Resonance Imaging without Gridding and Regridding at Every Iteration

Background: Non-Cartesian trajectories are used in a variety of fast imaging applications, due to the incoherent image domain artifacts they create when undersampled. While the gridding technique is commonly utilized for reconstruction, the incoherent artifacts may be further removed using compressed sensing (CS). CS reconstruction is typically done using conjugate-gradient (CG) type algorithms, which require gridding and regridding to be performed at every iteration. This leads to a large computational overhead that hinders its applicability. Methods: We sought to develop an alternative method for CS reconstruction that only requires two gridding and one regridding operation in total, irrespective of the number of iterations. This proposed technique is evaluated on phantom images and whole-heart coronary MRI acquired using 3D radial trajectories, and compared to conventional CS reconstruction using CG algorithms in terms of quantitative vessel sharpness, vessel length, computation time, and convergence rate. Results: Both CS reconstructions result in similar vessel length (P = 0.30) and vessel sharpness (P = 0.62). The per-iteration complexity of the proposed technique is approximately 3-fold lower than the conventional CS reconstruction (17.55 vs. 52.48 seconds in C++). Furthermore, for in-vivo datasets, the convergence rate of the proposed technique is faster (60±13 vs. 455±320 iterations) leading to a ∼23-fold reduction in reconstruction time. Conclusions: The proposed reconstruction provides images of similar quality to the conventional CS technique in terms of removing artifacts, but at a much lower computational complexity

Impact of diastolic dysfunction severity on global left ventricular volumetric filling - assessment by automated segmentation of routine cine cardiovascular magnetic resonance

<p>Abstract</p> <p>Objectives</p> <p>To examine relationships between severity of echocardiography (echo) -evidenced diastolic dysfunction (DD) and volumetric filling by automated processing of routine cine cardiovascular magnetic resonance (CMR).</p> <p>Background</p> <p>Cine-CMR provides high-resolution assessment of left ventricular (LV) chamber volumes. Automated segmentation (LV-METRIC) yields LV filling curves by segmenting all short-axis images across all temporal phases. This study used cine-CMR to assess filling changes that occur with progressive DD.</p> <p>Methods</p> <p>115 post-MI patients underwent CMR and echo within 1 day. LV-METRIC yielded multiple diastolic indices - E:A ratio, peak filling rate (PFR), time to peak filling rate (TPFR), and diastolic volume recovery (DVR₈₀- proportion of diastole required to recover 80% stroke volume). Echo was the reference for DD.</p> <p>Results</p> <p>LV-METRIC successfully generated LV filling curves in all patients. CMR indices were reproducible (≤ 1% inter-reader differences) and required minimal processing time (175 ± 34 images/exam, 2:09 ± 0:51 minutes). CMR E:A ratio decreased with grade 1 and increased with grades 2-3 DD. Diastolic filling intervals, measured by DVR₈₀or TPFR, prolonged with grade 1 and shortened with grade 3 DD, paralleling echo deceleration time (p < 0.001). PFR by CMR increased with DD grade, similar to E/e' (p < 0.001). Prolonged DVR₈₀identified 71% of patients with echo-evidenced grade 1 but no patients with grade 3 DD, and stroke-volume adjusted PFR identified 67% with grade 3 but none with grade 1 DD (matched specificity = 83%). The combination of DVR₈₀and PFR identified 53% of patients with grade 2 DD. Prolonged DVR₈₀was associated with grade 1 (OR 2.79, CI 1.65-4.05, p = 0.001) with a similar trend for grade 2 (OR 1.35, CI 0.98-1.74, p = 0.06), whereas high PFR was associated with grade 3 (OR 1.14, CI 1.02-1.25, p = 0.02) DD.</p> <p>Conclusions</p> <p>Automated cine-CMR segmentation can discern LV filling changes that occur with increasing severity of echo-evidenced DD. Impaired relaxation is associated with prolonged filling intervals whereas restrictive filling is characterized by increased filling rates.</p

Improved Wall And Lumen Image Acquistion And Processing For Cardiac And Peripheral Magnetic Resonance

Magnetic Resonance Imaging (MRI) is regularly used for routine diagnostics in clinical medicine today. It is a versatile imaging modality that can be tailored to provide anatomical and functional information for clinicians to assess a vast range of diseases without surgical or invasive interventions. Over the last several decades, over thousands of clinical MRI techniques have been developed for the advancement of medicine. Post-processing of routinely acquired MR image or data is one area where such innovation happens. Specifically, these methods use dedicated methods or algorithms to extract clinically relevant parameters that can aid in the diagnostics of diseases. In cardiac MRI, processing of cinematic images of left ventricular motion throughout the cardiac cycle was considered to be challenging, as it required the manual segmentation of the left ventricular blood volume and myocardium from over 200 images - from 8-10 slices over 20-28 temporal frames. In this case, an automated segmentation algorithm of the LV allow s rapid generation of volumetric filling curves, which can be further analyzed to assess the presence or absence of diastolic dysfunction. Another example of MR technology development happens in pulse sequence design, where novel acquisition methods are programmed to allow imaging tailored to a specific anatomy, such as the arterial vessel wall in the peripheral arteries. Vessel walls are difficult to visualize using standard MRI approaches, and novel pulse sequence components have been explored to provide a black-blood effect, which provides improved contrast between the vessel wall and the darkened blood signal. Finally, technology development on the MRI scanner to enable real-time feedback during data acquisition is a challenging, yet an exciting area of research with tremendous potential applications in the clinical arena. One such example is in coronary artery imaging, which faces the challenges of acquiring high-quality images of the moving heart. In this work, a 2D fat image snapshot - called a navigator - is developed to directly monitor the epicardial fat surrounding the coronary arteries at every heartbeat, and is incorporated into a real-time interactive software that allows rapid setup and efficient motion extraction on a standard clinical scanner

Whole heart coronary imaging with flexible acquisition window and trigger delay.

Coronary magnetic resonance imaging (MRI) requires a correctly timed trigger delay derived from a scout cine scan to synchronize k-space acquisition with the quiescent period of the cardiac cycle. However, heart rate changes between breath-held cine and free-breathing coronary imaging may result in inaccurate timing errors. Additionally, the determined trigger delay may not reflect the period of minimal motion for both left and right coronary arteries or different segments. In this work, we present a whole-heart coronary imaging approach that allows flexible selection of the trigger delay timings by performing k-space sampling over an enlarged acquisition window. Our approach addresses coronary motion in an interactive manner by allowing the operator to determine the temporal window with minimal cardiac motion for each artery region. An electrocardiogram-gated, k-space segmented 3D radial stack-of-stars sequence that employs a custom rotation angle is developed. An interactive reconstruction and visualization platform is then employed to determine the subset of the enlarged acquisition window for minimal coronary motion. Coronary MRI was acquired on eight healthy subjects (5 male, mean age = 37 ± 18 years), where an enlarged acquisition window of 166-220 ms was set 50 ms prior to the scout-derived trigger delay. Coronary visualization and sharpness scores were compared between the standard 120 ms window set at the trigger delay, and those reconstructed using a manually adjusted window. The proposed method using manual adjustment was able to recover delineation of five mid and distal right coronary artery regions that were otherwise not visible from the standard window, and the sharpness scores improved in all coronary regions using the proposed method. This paper demonstrates the feasibility of a whole-heart coronary imaging approach that allows interactive selection of any subset of the enlarged acquisition window for a tailored reconstruction for each branch region