BackgroundCardiovascular magnetic resonance (CMR) myocardial native T1 mapping allows assessment of interstitial diffuse fibrosis. In this technique, the global and regional T1 are measured manually by drawing region of interest in motion-corrected T1 maps. The manual analysis contributes to an already lengthy CMR analysis workflow and impacts measurements reproducibility. In this study, we propose an automated method for combined myocardium segmentation, alignment, and T1 calculation for myocardial T1 mapping.MethodsA deep fully convolutional neural network (FCN) was used for myocardium segmentation in T1 weighted images. The segmented myocardium was then resampled on a polar grid, whose origin is located at the center-of-mass of the segmented myocardium. Myocardium T1 maps were reconstructed from the resampled T1 weighted images using curve fitting. The FCN was trained and tested using manually segmented images for 210 patients (5 slices, 11 inversion times per patient). An additional image dataset for 455 patients (5 slices and 11 inversion times per patient), analyzed by an expert reader using a semi-automatic tool, was used to validate the automatically calculated global and regional T1 values. Bland-Altman analysis, Pearson correlation coefficient, r, and the Dice similarity coefficient (DSC) were used to evaluate the performance of the FCN-based analysis on per-patient and per-slice basis. Inter-observer variability was assessed using intraclass correlation coefficient (ICC) of the T1 values calculated by the FCN-based automatic method and two readers.ResultsThe FCN achieved fast segmentation (< 0.3 s/image) with high DSC (0.85 ± 0.07). The automatically and manually calculated T1 values (1091 ± 59 ms and 1089 ± 59 ms, respectively) were highly correlated in per-patient (r = 0.82; slope = 1.01; p < 0.0001) and per-slice (r = 0.72; slope = 1.01; p < 0.0001) analyses. Bland-Altman analysis showed good agreement between the automated and manual measurements with 95% of measurements within the limits-of-agreement in both per-patient and per-slice analyses. The intraclass correllation of the T1 calculations by the automatic method vs reader 1 and reader 2 was respectively 0.86/0.56 and 0.74/0.49 in the per-patient/per-slice analyses, which were comparable to that between two expert readers (=0.72/0.58 in per-patient/per-slice analyses).ConclusionThe proposed FCN-based image processing platform allows fast and automatic analysis of myocardial native T1 mapping images mitigating the burden and observer-related variability of manual analysis.Electronic supplementary materialThe online version of this article (10.1186/s12968-018-0516-1) contains supplementary material, which is available to authorized users.

Background Optimal healing of the myocardium following myocardial infarction (MI) requires a suitable degree of inflammation and its timely resolution, together with a well-orchestrated deposition and degradation of extracellular matrix (ECM) proteins. Methods and Results MI and SHAM-operated animals were imaged at 3,7,14 and 21 days with 3T magnetic resonance imaging (MRI) using a 19F/1H surface coil. Mice were injected with 19F-perfluorocarbon (PFC) nanoparticles to study inflammatory cell recruitment, and with a gadolinium-based elastin-binding contrast agent (Gd-ESMA) to evaluate elastin content. 19F MRI signal co-localized with infarction areas, as confirmed by late-gadolinium enhancement, and was highest 7days post-MI, correlating with macrophage content (MAC-3 immunohistochemistry) (ρ=0.89,P<0.0001). 19F quantification with in vivo (MRI) and ex vivo nuclear magnetic resonance (NMR) spectroscopy correlated linearly (ρ=0.58,P=0.020). T1 mapping after Gd-ESMA injection showed increased relaxation rate (R1) in the infarcted regions and was significantly higher at 21days compared with 7days post-MI (R1[s-1]:21days=2.8 [IQR,2.69-3.30] vs 7days=2.3 [IQR,2.12-2.5], P<0.05), which agreed with an increased tropoelastin content (ρ=0.89, P<0.0001). The predictive value of each contrast agent for beneficial remodeling was evaluated in a longitudinal proof-of-principle study. Neither R1 nor 19F at day 7 were significant predictors for beneficial remodeling (P=0.68;P=0.062). However, the combination of both measurements (R1<2.34Hz and 0.55≤19F≤1.85) resulted in an odds ratio of 30.0 (CI95%:1.41-638.15;P=0.029) for favorable post-MI remodeling. Conclusions Multinuclear 1H/19F MRI allows the simultaneous assessment of inflammation and elastin remodeling in a murine MI model. The interplay of these biological processes affects cardiac outcome and may have potential for improved diagnosis and personalized treatment.

BackgroundRecent studies demonstrated a strong association between atrial fibrillation (AF) and epicardial fat around the left atrium (LA). We sought to assess whether epicardial fat volume around the LA is associated with AF, and to determine the additive value of LA‐epicardial fat measurements to LA structural remodeling for identifying patients with AF using 3‐dimensional multi‐echo Dixon fat–water separated cardiovascular magnetic resonance.Methods and ResultsA total of 105 subjects were studied: 53 patients with a history of AF and 52 age‐matched patients with other cardiovascular diseases but no history of AF. The 3‐dimensional multi‐echo Dixon fat‐water separated sequence was performed for LA‐epicardial fat measurements. AF patients had significantly greater LA‐epicardial fat (28.9±12.3 and 14.2±7.3 mL for AF and non‐AF, respectively; P<0.001) and LA volume (110.8±38.2 and 89.7±30.3 mL for AF and non‐AF, respectively; P=0.002). LA‐epicardial fat adjusted for LA volume was still higher in patients with AF compared with those without AF (P<0.001). LA‐epicardial fat and hypertension were independently associated with the risk of AF (odds ratio, 1.17; 95% confidence interval, 1.10%–1.25%, P<0.001, and odds ratio, 3.29; 95% confidence interval, 1.17%–9.27%, P=0.03, respectively). In multivariable logistic regression analysis adjusted for body surface area, LA‐epicardial fat remained significant and an increase per mL was associated with a 42% increase in the odds of AF presence (odds ratio, 1.42; 95% confidence interval, 1.23%–1.62%, P<0.001). Combined assessment of LA‐epicardial fat and LA volume provided greater discriminatory performance for detecting AF than LA volume alone (c‐statistic=0.88 and 0.74, respectively, DeLong test; P<0.001).ConclusionsCardiovascular magnetic resonance 3‐dimensional Dixon‐based LA‐epicardial fat volume is significantly increased in AF patients. LA‐epicardial fat measured by 3‐dimensional Dixon provides greater performance for detecting AF beyond LA structural remodeling.