Quantification of left atrial fibrosis by 3D late gadolinium-enhanced cardiac magnetic resonance imaging in patients with atrial fibrillation: impact of different analysis methods.

AIMS: Various methods and post-processing software packages have been developed to quantify left atrial (LA) fibrosis using 3D late gadolinium-enhancement cardiac magnetic resonance (LGE-CMR) images. Currently, it remains unclear how the results of these methods and software packages interrelate. METHODS AND RESULTS: Forty-seven atrial fibrillation (AF) patients underwent 3D-LGE-CMR imaging prior to their AF ablation. LA fibrotic burden was derived from the images using open-source CEMRG software and commercially available ADAS 3D-LA software. Both packages were used to calculate fibrosis based on the image intensity ratio (IIR)-method. Additionally, CEMRG was used to quantify LA fibrosis using three standard deviations (3SD) above the mean blood pool signal intensity. Intraclass correlation coefficients were calculated to compare LA fibrosis quantification methods and different post-processing software outputs. The percentage of LA fibrosis assessed using IIR threshold 1.2 was significantly different from the 3SD-method (29.80 ± 14.15% vs. 8.43 ± 5.42%; P < 0.001). Correlation between the IIR-and SD-method was good (r = 0.85, P < 0.001) although agreement was poor [intraclass correlation coefficient (ICC) = 0.19; P < 0.001]. One-third of the patients were allocated to a different fibrosis category dependent on the used quantification method. Fibrosis assessment using CEMRG and ADAS 3D-LA showed good agreement for the IIR-method (ICC = 0.93; P < 0.001). CONCLUSIONS: Both, the IIR1.2 and 3SD-method quantify atrial fibrotic burden based on atrial wall signal intensity differences. The discrepancy in the amount of LA fibrosis between these methods may have clinical implications when patients are classified according to their fibrotic burden. There was no difference in results between post-processing software packages to quantify LA fibrosis if an identical quantification method including the threshold was used.

Extent of Left Atrial Fibrosis Correlates with Descending Aorta Proximity at 3D Late Gadolinium Enhancement Cardiac MRI in Patients with Atrial Fibrillation.

Purpose: To determine whether the distance between the descending aorta and left atrial (LA) wall correlates with the amount of fibrosis quantified in the posterior left inferior pulmonary vein (LIPV) area of the LA in patients with atrial fibrillation (AF). Materials and Methods: In this retrospective study, patients with AF underwent cardiac MRI in sinus rhythm prior to a pulmonary vein isolation procedure (July 2018 to February 2020). The mean distance (distancemean) and shortest distance (distanceshort) between the descending aorta and the LA wall were measured on three-dimensional (3D) contrast-enhanced MR angiograms; distancemean was defined as the average of five measurements at different levels between the descending aorta and the LA wall. The extent of LA fibrosis, both global fibrosis and regional fibrosis within the LIPV area, was derived from postprocessed, 3D, late gadolinium-enhanced images. Associations between the extent of fibrosis and the proximity of the descending aorta were analyzed by using correlative and multivariable analyses. Results: A total of 47 (mean age, 60 years ± 8 [standard deviation]; 31 men) patients were included for analysis. The extent of fibrosis in the posterior LIPV area was correlated with the distancemean (r s = -0.48; P < .01) and distanceshort (r s = -0.49; P < .01). Patients with a short distance between the descending aorta and LA wall (defined as a distanceshort < 2 mm) had a higher percentage of fibrosis in the posterior LIPV area than patients with a distanceshort greater than 2 mm (38.7% ± 22.7 vs 21.2% ± 17.8; P < .01). Conclusion: The distance between the descending aorta and LA was correlated with the extent of quantified fibrosis within the posterior LIPV area.Keywords: MRI, Cardiac, Left Atrium Supplemental material is available for this article. © RSNA, 2022.