Computational modeling identifies embolic stroke of undetermined source patients with potential arrhythmic substrate
- Department of Bioengineering, University of Washington, United States
- Division of Cardiology, University of Washington, United States
- Department of Neurology, University of Washington, United States
- School of Biomedical Engineering and Imaging Sciences, King’s College London, United Kingdom
- Department of Cardiology, Klinikum Coburg, Germany
- Department of Epidemiology, University of Washington, United States
- Center for Cardiovascular Biology, University of Washington, United States
- Institute for Stem Cell and Regenerative Medicine, University of Washington, United States
Figures
Figure 1 with 1 supplement
Model generation.
(A) Reconstruction of LA geometry with anatomical features labeled (RIPV/RSPV/LIPV/LSPV, right/left inferior/superior pulmonary veins; LAA, LA appendage). The LA is modeled as a bilayer comprising nested endocardial and epicardial shells linked in both fibrotic and non-fibrotic regions by 1D linear elements. (B) LA fiber orientations for the endocardium and epicardium, mapped from human atlas geometry as described in Materials and methods. (C) AFib trigger sites as pacing sites (posterior/anterior LIPV, LSPV, RSPV, RIPV, LAA base, mitral valve annulus, and posterior wall). (D) Regions of the LA generated as described in methods: (Andrade et al., 2014) atrial floor, (Israel et al., 2017) anterior wall and LAA, (Brachmann et al., 2016) posterior wall, (Tandon et al., 2019) left PVs, and (Zahid et al., 2016a) right PVs.
Figure 1—figure supplement 1
LA subdivision scheme.
(A) Alpha coordinate from universal atrial coordinate (UAC) system mapped on to a representative LA model. (B) Beta coordinate from UAC mapped on to a representative LA model. (C) 2D representation of UAC with pulmonary vein locations labeled. Dashed lines represent edges of the five atrial regions. (D) Segmented LA mapped onto a 3D mesh with numbered regions corresponding to regions in (C). (E) Final division scheme after edge expansion of the LPVs and RPVs to generate regions 3 and 4, respectively.
Figure 2
Summary of patient-derived model fibrosis with respect to RD inducibility.
(A) Histogram of AFib (22/45) and ESUS (24/45) inducible patients. Inducibility was not significantly different by χ2 test. (B) Patients with ESUS and AFib arranged by percentage of LA fibrosis. Dotted lines indicate the quartiles of fibrosis observed for all 90 patient-derived models. Circles are indicative of stable reentry observed in the model from at least one pacing site after in silico pacing protocol. Triangles indicate no RDs after pacing from all 15 pacing sites independently. Cases that lacked RDs despite high fibrosis (inset I) or were inducible despite low fibrosis (inset II) are highlighted.
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Figure 2—source data 1
Spreadsheet including source data underlying Figure 2.
ESUS and AFib patient ID numbers; inducibility status (i.e., whether RD-sustained arrhythmia was observed in the corresponding patient-specific LA model); and LA volumetric fibrosis burden (%) extracted directly from clinical report.
- https://cdn.elifesciences.org/articles/64213/elife-64213-fig2-data1-v2.xlsx
Figure 3
Summary of RD characteristics between ESUS and AFib models.
(A) Boxplot of fibrosis percentage in ESUS and AFib models where reentry was induced (ESUS: N = 24, IQR = 10.6; AFib: N = 22, IQR = 5) and where reentry was not induced (ESUS: N = 21, IQR = 5; AFib N = 23, IQR = 3.5). Across ESUS and AFib models, fibrosis burden for RD-inducible and RD non-inducible models was significantly different (p<0.0001). (B) Boxplot of number of unique reentrant morphologies elicited by all 15 pacing sites (p=0.83). (C) Correlation plot of fibrosis vs. number of RDs (R = 0.63, p<0.0001). (D) Boxplot of the number of pacing sites which induced reentry (p=0.79). (E) Correlation plot of fibrosis vs. number of pacing sites that induced reentry (R = 0.62, p<0.0001). (F) Boxplot depicting percentage of tissue with significantly depolarized tissue (>95th percentile) between ESUS and AFib models after reaching steady state. p=0.32; CI: [–0.007, 0.019].
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Figure 3—source data 1
Spreadsheet including source data underlying Figure 3.
For each LA model used in the study: number of pacing sites that induced RD-sustained arrhythmia; number of unique RD locations; percentage of tissue significantly depolarized in quiescent state, as presented in Figure 3F.
- https://cdn.elifesciences.org/articles/64213/elife-64213-fig3-data1-v2.xlsx
Figure 4
Maps of fibrotic tissue distribution (left) and activation time (right) for ESUS and AFib models in which pacing succeeded (rows 1–2) or failed (row 3) to induce RD-driven arrhythmia.
Black arrows indicate directions of wavefront propagation in RDs. Double lines indicate sites of conduction block. Black-shaded regions in activation maps indicate locations where activation did not occur during the analysis interval. (A) ESUS model with 6.9% fibrosis and reentry inferior to LIPV. (B) ESUS model with 10.0% fibrosis and reentry on the atrial floor. (C) ESUS model with 16% fibrosis with wavefront termination through fibrosis on posterior wall. (D) AFib model with 9.9% fibrosis and reentry observed adjacent to RIPV on posterior wall. (E) AFib model with 13.7% fibrosis and reentry observed on the anterior wall. (F) AFib model with 11.6% fibrosis with wavefront collision on posterior wall.
Figure 5
Summary of IdS and RD localization characteristics.
(A) Region-wise IdS for both ESUS and AFib LA models. (B) Heat map of the regions in which triggers are most likely to induce arrhythmias depicted as representative ESUS and AFib models. (C) Histogram of RDs across all AFib and ESUS models binned by localization to specific LA regions. (D) Heat map of regions in which RDs are most likely to localize depicted as representative ESUS and AFib models.
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Figure 5—source data 1
Spreadsheet including source data underlying Figure 5.
For each episode of RD-sustained arrhythmia induced in each patient-specific LA model, the location of the pacing associated pacing site and the LA region in which the RD ultimately anchored are provided.
- https://cdn.elifesciences.org/articles/64213/elife-64213-fig5-data1-v2.xlsx
Figure 6
Summary of the region-by-region extent of tissue with a spatial fibrosis pattern (as characterized by local density and entropy) associated with RD localization (i.e., pro-RD tissue).
(A) Maps of pro-RD tissue for representative AFib and ESUS cases, including boundaries between regions. (B) Region-wise extent of pro-RD tissue in inducible AFib and ESUS models, depicted as boxplots (**p<0.01, Wilcoxon rank-sum test; CI: [–0.149, –0.021]).
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Figure 6—source data 1
Spreadsheet including source data underlying Figure 6.
For each LA model used in the study, proportion of pro-RD tissue (as calculated by previously established machine learning-based analysis of fibrosis spatial pattern) in each LA region.
- https://cdn.elifesciences.org/articles/64213/elife-64213-fig6-data1-v2.xlsx
Tables
Table 1
Patient characteristics in ESUS and AFib groups.
| ESUS (N = 45) | AFib (N = 45) | p value | |
|---|---|---|---|
| Age, years | 60 ± 16 | 62 ± 12 | 0.504 |
| Female, % | 44.0% | 32.8% | 0.275 |
| BMI, kg/m2 | 27.6 ± 4.3 | 29.5 ± 5.9 | 0.08 |
| CHA2DVASc score | 2.0 | 1.9 | 0.345 |
| CHF, n | 14.3% | 18.4% | 0.599 |
| Hypertension, n | 68.5% | 61.2% | 0.468 |
| Diabetes mellitus, n | 20.4% | 12.2% | 0.292 |
| CAD, n | 18.4% | 18.4% | 1.000 |
| Smoking, n | 32% | 28% | 0.679 |
| LA fibrosis, % | 13.6 ± 6.2% | 14.2 ± 4.5% | 0.91 |
| LA surface area, cm2 | 109 ± 26 | 134 ± 40 | 0.0007 |
| LA volume index, mL/m2 | 60 ± 29 | 57 ± 26 | 0.607 |
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Computational modeling identifies embolic stroke of undetermined source patients with potential arrhythmic substrate
eLife 10:e64213.
https://doi.org/10.7554/eLife.64213
