PurposeDynamic contrast enhanced MRI of the heart typically acquires 2–4 short-axis (SA) slices to detect and characterize coronary artery disease. This acquisition scheme is limited by incomplete coverage of the left ventricle. We studied the feasibility of using radial simultaneous multi-slice (SMS) technique to achieve SA, 2-chamber and/or 4-chamber long-axis (2CH LA and/or 4CH LA) coverage with and without electrocardiography (ECG) gating using a motion-robust reconstruction framework.Methods12 subjects were scanned at rest and/or stress, free breathing, with or without ECG gating. Multiple sets of radial SMS k-space were acquired within each cardiac cycle, and each SMS set sampled 3 parallel slices that were either SA, 2CH LA, or 4CH LA slices. The radial data was interpolated onto Cartesian space using an SMS GRAPPA operator gridding method. Self-gating and respiratory states binning of the data were done. The binning information as well as a pixel tracking spatiotemporal constrained reconstruction method were applied to obtain motion-robust image reconstructions. Reconstructions with and without the pixel tracking method were compared for signal-to-noise ratio and contrast-to-noise ratio.ResultsFull coverage of the heart (at least 3 SA and 3 LA slices) during the first pass of contrast at every heartbeat was achieved by using the radial SMS acquisition. The proposed pixel tracking reconstruction improves the average SNR and CNR by 21% and 30% respectively, and reduces temporal blurring for both gated and ungated acquisitions.ConclusionAcquiring simultaneous multi-slice SA, 2CH LA and/or 4CH LA myocardial perfusion images in every heartbeat is feasible in both gated and ungated acquisitions. This can add confidence when detecting and characterizing coronary artery disease by revealing ischemia in different views, and by providing apical coverage that is improved relative to SA slices alone. The proposed pixel tracking framework improves the reconstruction while adding little computational cost.

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Background Using the spin‐lattice relaxation time (T1) as a biomarker, the myocardium can be quantitatively characterized using cardiac T1 mapping. The modified Look–Locker inversion (MOLLI) recovery sequences have become the standard clinical method for cardiac T1 mapping. However, the MOLLI sequences require an 11‐heartbeat breath‐hold that can be difficult for subjects, particularly during exercise or pharmacologically induced stress. Although shorter cardiac T1 mapping sequences have been proposed, these methods suffer from reduced precision. As such, there is an unmet need for accelerated cardiac T1 mapping. Purpose To accelerate cardiac T1 mapping MOLLI sequences by using neural networks to estimate T1 maps using a reduced number of T1‐weighted images and their corresponding inversion times. Materials and Methods In this retrospective study, 911 pre‐contrast T1 mapping datasets from 202 subjects (128 males, 56 ± 15 years; 74 females, 54 ± 17 years) and 574 T1 mapping post‐contrast datasets from 193 subjects (122 males, 57 ± 15 years; 71 females, 54 ± 17 years) were acquired using the MOLLI‐5(3)3 sequence and the MOLLI‐4(1)3(1)2 sequence, respectively. All acquisition protocols used similar scan parameters: TR=2.2ms$TR\; = \;2.2\;{\rm{ms}}$, TE=1.12ms$TE\; = \;1.12\;{\rm{ms}}$, and FA=35∘$FA\; = \;35^\circ $, gadoteridol (ProHance, Bracco Diagnostics) dose ∼0.075mmol/kg$\sim 0.075\;\;{\rm{mmol/kg}}$. A bidirectional multilayered long short‐term memory (LSTM) network with fully connected output and cyclic model‐based loss was used to estimate T1 maps from the first three T1‐weighted images and their corresponding inversion times for pre‐ and post‐contrast T1 mapping. The performance of the proposed architecture was compared to the three‐parameter T1 recovery model using the same reduction of the number of T1‐weighted images and inversion times. Reference T1 maps were generated from the scanner using the full MOLLI sequences and the three‐parameter T1 recovery model. Correlation and Bland–Altman plots were used to evaluate network performance in which each point represents averaged regions of interest in the myocardium corresponding to the standard American Heart Association 16‐segment model. The precision of the network was examined using consecutively repeated scans. Stress and rest pre‐contrast MOLLI studies as well as various disease test cases, including amyloidosis, hypertrophic cardiomyopathy, and sarcoidosis were also examined. Paired t‐tests were used to determine statistical significance with p<0.05$p < 0.05$. Results Our proposed network demonstrated similar T1 estimations to the standard MOLLI sequences (pre‐contrast: 1260±94ms$1260 \pm 94\;{\rm{ms}}$ vs. 1254±91ms$1254 \pm 91\;{\rm{ms}}$ with p=0.13$p\; = \;0.13$; post‐contrast: 484±92ms$484 \pm 92\;{\rm{ms}}$ vs. 493±91ms$493 \pm 91\;{\rm{ms}}$ with p=0.07$p\; = \;0.07$). The precision of standard MOLLI sequences was well preserved with the proposed network architecture (24±28ms$24 \pm 28\;\;{\rm{ms}}$ vs. 18±13ms$18 \pm 13\;{\rm{ms}}...

fibrillation (AF) is the most common sustained arrhythmia in adults in the United States (1). Catheter ablation is superior to antiarrhythmic drugs for rhythm control treatment of AF, but success rates to date are still modest: approximately 70% for paroxysmal AF and 60% or lower for persistent AF (2). Identifying accurate predictors for AF recurrence based on clinical (eg, AF duration) and imaging metrics (eg, left atrial [LA] size or left ventricular function) has proven difficult. A more promising candidate for predicting AF recurrence following catheter ablation is LA fibrosis because atrial fibrosis has been shown to play a crucial role in the development of the arrhythmogenic substrate for AF and may be a marker for more extensive disease less amenable to pulmonary vein isolation (3,4). Although LA fibrosis as assessed with three-dimensional (3D) LA late gadolinium enhancement (LGE) MRI ( 5) has shown promise for predicting AF recurrence following catheter ablation (6-8), the "Utah" classification (9) has not been independently reproduced by the field, most likely the result of several major gaps in technology: (a) inadequate spatial resolution (1.5 mm 3 1.5 mm 3 2.5 to 5 mm) (5,6,8,10,11), (b) lengthy imaging time (approximately 10-15 minutes) (12), and (c) unreliable image analysis techniques for quantification for LA fibrosis in the thin (1-2 mm) LA wall. These gaps prevent widespread adoption of LA fibrosis quantification.We sought to address the four limitations (spatial resolution, imaging time, reliance on external navigator gating, and reliance on 3 T) of standard 3D LA LGE MRI by synergistically combining the following advanced techniques: (a) balanced steady-state free precession (SSFP) readout (higher signal-to-noise ratio [SNR] than gradient echo), (b) stack-of-stars k-space sampling (higher incoherence than Cartesian k-space sampling), and (c) self-navigation

Background Esophageal thermal injury (ETI) is a byproduct of atrial fibrillation (AF) ablation using thermal sources. The most severe form of ETI is represented by atrioesophageal fistula, which has a high mortality rate. Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows identification of ETI. Hence, we sought to evaluate the utility of LGE‐MRI as a method to identify ETI across the entire spectrum of severity. Methods and Results All AF radiofrequency ablations performed at the University of Utah between January 2009 and December 2017 were reviewed. Patients with LGE‐MRI within 24 hours following AF ablation as well as patients who had esophagogastroduodenoscopy in addition to LGE‐MRI were identified. An additional patient with atrioesophageal fistula who had AF ablation at a different institution and had MRI and esophagogastroduodenoscopy at the University of Utah was identified. A total of 1269 AF radiofrequency ablations were identified. ETI severity was classified on the basis of esophageal LGE pattern (none, 60.9%; mild, 27.5%; moderate, 9.9%; severe, 1.7%). ETI resolved in most patients who underwent repeat LGE‐MRI at 3 months. All patients with esophagogastroduodenoscopy‐confirmed ETI had moderate‐to‐severe LGE 24 hours after ablation MRI. Moderate‐to‐severe LGE had 100% sensitivity and 58.1% specificity in detecting ETI, and a negative predictive value of 100%. Atrioesophageal fistula was visualized by both computed tomography and LGE‐MRI in one patient. Conclusions LGE‐MRI is useful in detecting and characterizing ETI across the entire severity spectrum. LGE‐MRI exhibits an extremely high sensitivity and negative predictive value in screening for ETI after AF ablation.