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Background Mapping the longitudinal relaxation time (T1) is a promising quantitative tool for the detection of myocardial pathologies either in mouse or human. T1 maps are usually obtained in 2D in order to reduce the total scan time. However, to diagnose myocardial infarction it might be useful to obtain the T1 maps in three dimensions (3D) which require a long acquisition time. In this project a new 3D T1 mapping method based on Look-Locker protocol using continuous radio frequency (RF) excitation and spiral gradient shape has been developed. This method allowed to obtain 3D maps with high spatial (200 x 200 x 300 μm) & temporal resolution (

Background Characterization of carotid artery morphology and plaque composition requires multiple measurements with different contrast-weightings, which are limited by long scan time, image misregistration, and expertise-dependency in image interpretation. Recently, a new method,3D Multicontrast ATherosclerosis CHaracterization (MATCH) has been developed to overcome the above drawbacks by acquiring multi-contrast weighted images in one scan [1] This study was conducted to determine the accuracy of MATCH in the characterization of plaque morphology and composition in patients.

Background Cardiac and respiratory motion artifacts are major challenges to whole-heart coronary MRA. The conventional motion suppression strategies often involve prospective gating based on motion surrogates, e.g. ECG and navigator, which complicates scan setup and prolongs scan time significantly. To address these limitations, an ECG and navigator-free 4D whole-heart coronary MRA technique was recently proposed, providing both cardiac function and coronary artery assessment from a single measurement [1]. In this work, we evaluate the 4D technique by comparing it against conventional cine and coronary MRA protocols.

Background Although using more coils may improve parallel imaging performance, it produces a burden on the amount of calibration data required for autocalibrating methods. This work investigates the use of principal component analysis (PCA) to project the original set of coils onto a smaller set of virtual coils to reduce calibration scan time for through-time radial GRAPPA [Seiberlich, et al. Magn Reson Med. 2011; 65(2):492-505].

Background A typical CMR exam includes cine, tagging, first-pass, and delayed-hyper-enhancement (DHE) imaging. The DHE image is usually acquired at a single timeframe. Nevertheless, obtaining cine DHE images would provide both viability and functional information in single set of images without misregistration problems for better image interpretation. However, repeated breath-hold scans are required to obtain cine DHE images, which increases scan-time with varying level of tissue enhancement with time. In this work, we propose a new technique for generating cine DHE images based on the acquired DHE image and motion field derived from the corresponding tagged images. Methods A mid-diastolic short-axis DHE image and the corresponding set of tagged images were acquired on 3T-MRI scanner. The corresponding cine images were acquired for reference. Image analysis has two steps: 1) apply the Lucas-Kanade optical-flow algorithm to the tagged images to extract the motion field of the myocardium through the cardiac cycle; 2) apply the measured motion field to the known (acquired) DHE image to generate the unknown DHE images. The infarcted regions were identified in the DHE images using the full-width at halfmaximum method. Radial thickening was measured from both cine and DHE images to evaluate the generated images. Infarction transmurality, circumferential strain, and radial thickening were measured from the DHE, tagged, and cine images, respectively, and the relationships between the generated parameters were studied using regression and correlation analyses. Results Figure 1 shows tagged and DHE images. Figure 2 shows transmurality and strain at different segments. Peak infarction transmurality (circumferential strain) were 91% (0%) and 0% (-14%) in the infarcted and lateral regions, respectively. Myocardial thickening, calculated from the DHE images, showed good correlation with the results from the gold-standard cine images (r = 0.72). Further, there was an excellent agreement between ED and ES infarction transmurality calculated from the DHE images (r = 0.998). Infarction transmurality showed good correlation with strain (r = 0.81; y = 0.19x+11.27). Conclusions The developed technique generates composite images that show both viability and functional information in one set of images, which is important for prognostic evaluation of the patient’s condition, e.g. determining candidates for revascularization. The generated images could be also useful for differentiating between gadolinium recess in the muscle and myocardial scar, usually conducted by comparing cine and DHE images side-by-side. Future work includes further improvement of the optical-flow algorithm to minimize error propagation with time, and implementing the algorithm on large number of patients with different degrees of infarction.

Methods Cohorts and Acquisition: 41 volunteers (HV, 25 ± 5 y.), 14 STEMI (63 ± 7 y.), 12 DCM (54 ± 17 y.), and 5 DCM+LBBB (47 ± 8 y.) patients were investigated. Acquisition parameters were: Philips Achieva 3 T, 32 channel cardiac coil, velocity encoded (Tissue Phase Mapping, TPM) segmented black-blood gradient echo with VENC = 30 cm/s, TR/TE = 6.1/4.6 ms, FOV adapted to patient size, resolution = 2x8 mm, 3 k-lines/segment, SENSE = 2, phase interval = 30 ms, and nominal scan time = 5:51 min:sec for 3 short axis slices. Parameters (see [1]): a) velocity-based: Standard Deviation of Times to Peak [SD(TTP)], Asynchrony Correlation Coefficient [ACC], Temporal Uniformity of Velocity [TUV], and Velocity Ranges (difference: maximum-minimum velocity). b) strain-based: Base Apex Rotation Correlation [BARC], Temporal Uniformity of Strain [TUS], Standard Deviation of Onset/Peak Time [SD(T)], Coefficient of Variation [CV], Difference between Septal and Lateral Peak Circumferential Strain [DiffSLpeakCS], Onset/Peak Of Shortening Delay [Delay], Regional Variance of Strain [RVS], and Regional Variance Vector of Strain [RVVPS]. Analysis: The significance of resulting differences between the different groups was assessed via non-parametric Kruskal-WallisTest.

Background Through-Time non-Cartesian GRAPPA, a novel parallel imaging method for non-Cartesian trajectories, has recently been shown to provide real-time, free-breathing cardiac images with temporal resolutions of less than 35 ms per frame [Seiberlich N, et al. MRM 2011 Dec;66 (6):1682-8]. The drawback to this method is the need for several fully-sampled datasets for calibration stemming from the non-Cartesian nature of the data, which leads to a longer overall scan time. By acquiring interleaved spiral datasets and combining them to form fully-sampled datasets for the generation of the GRAPPA weights, as in TGRAPPA [Breuer FA, et al. MRM 2005 Apr;53(4):9815.], there is no need for additional calibration data. However, this interleaved calibration method poses the risk of increased artifacts if the temporal footprint of the calibration data is too long. The goal of this study is to test the extent to which self-calibrating through-time spiral GRAPPA can be used for real-time free-breathing CMR.

Background Pulmonary arterial hypertension (PAH) is characterized by progressive increase in pulmonary vascular resistance (PVR), leading to right ventricular (RV) failure [1]. PVR is calculated using right heart catheterization (RHC), from the trans-pulmonary pressure gradient (ΔP) and pulmonary flow (QPA). Doppler echocardiography can estimate PVR from the ratio of peak tricuspid regurgitation velocity (TRV) to main pulmonary artery velocity time-integral (MPA flow) [2]. MRI is increasingly used to assess right ventricular (RV) function in PAH. Determining PVR from MRI could enable a more complete characterization of RV and PA interactions in PAH. The purpose of this study was to non-invasively estimate PVR from TRV/QPA using a 4D flow-sensitive MRI sequence in humans [3]. Methods Six PAH patients referred for right heart catheterization (RHC) and six healthy volunteers were scanned according to an IRB-approved protocol. In patients, RHC was performed clinically within 1 week of the MRI in patients with PAH. PVRRHC was calculated as follows: PVR=ΔP/QPA. 4D flow MRI (Phase Contrast with Vastly undersampled Isotropic Projection Reconstruction - PC VIPR) was performed on 3T clinical scanners (GE Healthcare, Waukesha, WI) after the administration of gadolinium-based contrast agents. PC VIPR parameters: FOV=32 x 32 x 22 cm, isotropic 1.3 mm spatial resolution, TR/TE = 6.3/2.1 ms, Venc=150 cm/s, scan time: ~10 min using respiratory and retrospective ECG gating. Post-processing was done using Ensight (CEI, Apex, NC) and MatLab (The Mathworks, Natick, MA) to measure peak TRV and QPA. Statistical analysis included regression analysis to evaluate the correlation between TRV/QPA and PVRRHC. Ar egression equation was derived to calculate PVRMRI. Differences between PVRMRI and PVRRHC were assessed using Bland-Altman analysis. TRV/QPA ratios in healthy controls were compared to those in PAH patients using Student t-test. Results Average (± standard deviation) PVRRHC was 7.15 ± 3.56 UW. The Pearson correlation coefficient between TRV/QPA and PVRRHC was 0.94. The equation derived from linear regression was PVRMRI = 0.69*PVRRHC 2.84 UW. Using this equation, the average (± standard deviation) PVRMRI was 7.15 ± 3.35 (p=0.99). The mean difference between PVRMRI and PVRRHC was 0 with positive and negative levels of agreement of 2.4 and -2.4, respectively. Differences in TRV/QPA in healthy controls and PAH patients were statistically significant (p=0.0003).

Summary To investigate the performance of a novel algorithm for correcting respiratory-induced heart motion for wholeheart coronary MRI. Background A right hemi-diaphragm (RHD) respiratory navigator is commonly used to suppress the respiratory motion of the heart in coronary MRI [1]. Typically, a small 5mm end expiratory gating window (GW) is used to gate data. While this technique successfully suppresses respiratory motion, it prolongs scan time due to navigator efficacies of only 30-50%. Increasing the GW to 15mm would increase the navigator efficiency. In this study, we present a novel respiratory motion correction algorithm which allows increasing the GW to 15mm. Methods Whole-heart coronary MRI with isotropic 1.3mm 3 resolution was acquired using partial Fourier and a navigator with 15mm GW on a 1.5T Philips CMR scanner from 10 healthy subjects (4 males; 29 ± 13 yr). The navigator RHD positions were used to sort the acquired k-space segments into 15 separate 1mm bins (based on their displacement). To compensate for the respiratory motion of the heart, all k-space segments acquired in each bin were assigned a 3D translation parameter. The 3D translation parameter was estimated using an iterative gradient descent optimization algorithm to correct the kspace segments such that the sharpness of the image, reconstructed using the corrected k-space segments, is maximized. The variance of the gradient of the image was used as the measure for the image sharpness [2]. For comparison, another whole-heart coronary MRI dataset was acquired using the same sequence and a navigator with a 5mm GW.

Background Evaluation of cardiac function is clinically performed using multi-slice breath-hold (BH) acquisition, in which patient breathes for a period of 40-60 seconds between a BH of 10-12 seconds. This results in suboptimal data acquisition efficiency. In this study, we propose to take advantage of the time between multiple BHs to acquire additional free-breathing (FB) data that can be used in the reconstruction of undersampled BH acquisition without increasing the total scan time.

Background Parallel imaging can reduce scan time with typical reduction factors of ~2, often not sufficient to reduce scan time to breath hold duration. Spatiotemporal parallel imaging such as k-t-GRAPPA allows for a significantly higher speed-up in data acquisition, but previous studies mostly acquired full k-space data while removing data retrospectively. Here, aortic flow scans were acquired during breath-hold using kt-GRAPPA based reconstruction [1,2] and compared to conventional protocols using GRAPPA and navigator respiration gating.

Background and objective The Modified Look-Locker Inversion-Recovery (MOLLI) sequence (Messroghli, et al, JMRI, 2007) was optimized for myocardial T1 mapping on 1.5T. However, little data exists on T1 mapping at 3T. The standard MOLLI sequence uses three inversion-recovery blocks to acquire 11 images over 17 heartbeats (HB). The long breath hold could limit its clinical application in patients with cardiorespiratory compromise. A new 11 HB MOLLI protocol with two inversion-recovery blocks was introduced recently, which reduces scan time by 35%. This aim of this study is to verify both 17 HB and 11 HB MOLLI sequences at 3T.