Advanced 3D analysis of fibrotic ring-like pattern in non-ischemic cardiomyopathy predicts major arrhythmic events

Abstract

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by the National Institute for Health Research Biomedical Research Centre at Guy’s and St. Thomas’ Trust and King’s College, the Centre of Excellence in Medical Engineering funded by the Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC; WT088641/Z/09/Z). M.J.B. is supported by a Medical Research Council New Investigator Grant (MR/N011007/1) and British Heart Foundation (Project grant PG/18/74/34077). This work was supported by EPSRC 2018/19 DTP - EP/R513064/1 grant. This work was supported by a National Heart and Lung Institute Foundation grant awarded to Professor Sanjay Prasad and Dr Richard Jones. This work was supported by a National Heart and Lung Institute Foundation grant awarded to SKP, DJH, REJ, UT and BPH. Additionally, the study was supported by an Intermediate Clinical Research Fellowship awarded to BPH (FS/ICRF/21/26019). Background The presence of ring-like patterns of mid-wall fibrosis identified on late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) is associated with an increased risk of major arrhythmic events (MAE) in non-ischemic cardiomyopathy (NICM). Analysis of tissue bordering core fibrosis and healthy myocardium (Gray Zone [GZ]) has been suggested as an important pro-arrhythmic substrate in this population. Purpose To investigate refined anatomical definitions of the fibrotic ring pattern, including the importance of GZ inclusion in the association with MAE in NICM. Methods LGE CMR data from 292 NICM patients were analysed to delineate both core and GZ fibrosis. Fibrosis quantification masks for each 2D image slice were used, along with AHA 17-segment maps, to identify fibrotic ring patterns: defined by fibrosis extending by 3 or more continuous AHA-segments for any individually-contiguous fibrotic component within each slice (Fig 1A). Ring patterns were assessed separately for core fibrosis and core + GZ, as well as individually in basal, mid-basal and mid-apical regions. In separate analysis, LGE contours were aligned, interpolated, and used to generate 3D computational volumetric models (Fig 1B). Individually-connected scar components were extracted and the 3D circumferential angular variation (3DCAV) of each separate fibrotic structure quantified as a continuous variable (Fig 1C). Association of the presence of ring patterns and 3DCAV with a composite MAE were investigated. Results Of 292 patients, 67(23%) had core fibrotic ring patterns (54 basal, 28 mid-cavity level, 6 apical). Over a median(IQR) of 6(4) years, 16(24%) patients experienced MAE. On univariate Cox analysis, ring pattern core fibrosis was a strong predictor of MAE (Hazard ratio [HR] 2.2, 95% confidence interval [CI] 1.13-4.31, p=0.021). Apical-basal region analysis showed that basal ring pattern was associated with MAE (HR 2.25, 95%CI, 1.13-4.51, p=0.022). Multivariate Cox analysis including raised NYHA Class and severely reduced LVEF, overall ring (HR 2.14, 95%CI, 1.05-4.33, p=0.035) and basal ring pattern (HR 2.9, 95%CI 1.39-6.02, P=0.004) continued to show independent association with the MAE. Analysis of the full 3D geometry of the individual scar components also showed that our novel 3DCAV metric was associated with the MAE on both univariate (HR 1.31, 95%CI 1.08-1.59, P=0.007) and multivariate (HR 1.3, 95%CI, 1.06-1.60, P=0.013). Analysis of core ring patterns outperformed analysis of core+GZ patterns in all cases. Conclusions Our study confirms that ring-like patterns of fibrosis in NICM are strongly associated with MAE in NICM, with patterns predominantly at the basal regions conferring enhanced risk relative to mid-basal and mid-apical regions. Inclusion of GZ quantification in ring-pattern analysis did not enhance risk prediction. Our novel 3D analysis of circumferential fibrosis patterns may provide a more robust quantitative metric for stratification.