Recurrence and non-improvement of European Heart Rhythm Association symptom scores after atrial fibrillation ablation: the role of left atrial fractal dimension
Introduction
Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting millions of individuals worldwide, with a high clinical prevalence and significant disease burden (1,2). Compared with antiarrhythmic drugs, radiofrequency ablation is a commonly used treatment that can restore sinus rhythm and improve symptoms in certain patients with AF. However, its efficacy in preventing recurrence varies, and it may not significantly reduce cardiovascular mortality in all patient populations (3,4). The recurrence of postoperative AF and potential complications of ablation warrant careful patient selection to avoid unnecessary surgical risks and additional financial burdens. The European Heart Rhythm Association (EHRA) symptom score is a widely used clinical tool to assess the severity of AF-related symptoms, ranging from class I (no symptoms) to class IV (severe symptoms affecting daily activity), which allows for grading of patients with AF (5). In patients with AF, preoperative prediction of non-improvement in EHRA symptom scores may help identify patients who are less likely to experience significant symptom relief following ablation, guiding more personalized treatment decisions.
Previous studies have reported that greater left atrial (LA) wall thickness, increased diameter, larger volume and volume index, as well as more spherical LA morphology and box surface ratio, are associated with a higher risk of late AF recurrence following ablation (6-9). This suggests that, in addition to LA size, LA morphology can also indicate poor LA remodeling associated with recurrence after ablation.
To quantitatively describe the morphology of the LA, a mathematical method called fractal analysis was introduced. Fractal dimensions (FD) acquired based on fractal analysis can be applied to quantify shape complexity and boundary irregularity, capturing early morphologic changes that might precede volumetric alterations (10,11). We hypothesized that LA-FD could serve as a novel biomarker to quantify adverse structural remodeling and be correlated with poor outcomes in patients with AF. Therefore, we quantified LA morphological heterogeneity using FD from cardiac computed tomography angiography (CTA) images, with the aim of investigating the relationship between LA-FD, AF recurrence, and changes in EHRA symptom scores after recurrence. Understanding these relationships could help guide personalized treatment strategies for patients undergoing ablation. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2049/rc).
Methods
Study population
This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study protocol was approved by the Institutional Review Board of Lanzhou University Second Hospital (ethical board approval number: 2023A-702). The informed consent was exempted for all individual patients because of the retrospective nature of the study.
We queried the information management system of Lanzhou University Second Hospital to identify 535 patients who underwent their first radiofrequency ablation procedure for paroxysmal or persistent AF and had CTA performed within three days before the procedure from October 2019 to September 2022. We routinely followed up our patients consecutively after ablation. We excluded patients based on the following criteria: age <18 years (n=2); follow-up time of less than 1 year (n=3); incomplete clinical and imaging data (n=1); with stent placement, bypass, or pacemaker (n=5); underwent valve replacement, left atrial appendage blocker, and other cardiac surgeries (n=7); previous history of myocardial infarction (n=2); diagnosis of valvular, dilated, or hypertrophic heart disease (n=2); and poor cardiac CTA image quality (n=1). Finally, 512 eligible patients were included in the study. Figure 1 shows the patient enrollment process.

Cardiac CTA examination
After patients were admitted to the Lanzhou University Second Hospital, routine contrast-enhanced cardiac CTA was performed using three different computed tomography (CT) machines with a similar scanning protocol: Revolution 256-row CT (GE HealthCare, Waukesha, WI, USA), iCT 256 (Brilliance iCT256, Philips Healthcare, Netherlands), and dual-source Force CT (Somatom Force, Siemens Healthcare, Forchheim, Germany). Table S1 provides more detailed information on the specific acquisition parameters used.
Radiofrequency ablation and postoperative follow-up
All enrolled patients with AF underwent ablation based on circumferential pulmonary vein isolation. The four pulmonary veins were isolated and observed for 30 min to verify the bidirectional block between the left atrium and pulmonary veins. The patients were monitored using a 12-lead electrocardiogram and 24-hour ambulatory electrocardiogram every 3 months during the first year of the postoperative period and every 6 months thereafter at follow-up visits. When patients were not followed up as planned, they were followed up by telephone. The follow-up end point was AF recurrence or termination by December 2023. AF recurrence was defined as the detection of any atrial tachyarrhythmia (including atrial tachycardia, atrial flutter, and AF) lasting >30 seconds after a 3-month postoperative blanking period.
According to the European Society of Cardiology guidelines (5), cardiologists routinely evaluate the EHRA symptom scores preoperatively. In addition, patients with AF recurrence were assessed for changes in EHRA symptoms compared with the preoperative period. The EHRA symptoms that remained unchanged/worsened were considered the non-improvement group, and the EHRA symptoms that improved were considered the improvement group.
LA-FD measurement
The FD is measured by the box-counting method with the formula (12):
First, the maximal level of the LA was determined on cardiac-enhanced CTA images by two radiologists with 10 years of experience in cardiovascular diagnosis (readers 1 and 2), neither of whom was aware of the patient’s follow-up. Second, three-dimensional (3D) Slicer (version 5.2.0; USA) was used by reader 1 to outline three regions of interest (ROIs) along the outer edge of the LA, including the maximal level of the LA and its adjacent upper and lower layers. Furthermore, reader 2 checked the ROIs sketched by reader 1, and if there were ambiguities, they were negotiated and manually modified. Finally, Python 3.11 (https://www.python.org) was applied by reader 1 to calculate the FD of the three ROIs mentioned above. The average was taken to get the final FD. Figure 2 shows a schematic diagram of the LA-FD measurements. The diameter, circumference, and square of the LA were measured three times at the maximal level using the Advanced Workstation 4.7 (GE Healthcare Waukesha, WI, USA) workstation by reader 1. The final result was determined by averaging the three measurements.

Statistical analysis
Statistical analyses were conducted with SPSS 26.0 (IBM Corp., Armonk, NY, USA). The frequencies (percentages) were utilized to express categorical variables. Continuous variables were shown as mean ± standard deviation or median (interquartile range). Continuous variables were dichotomized according to mean values, and the Kaplan-Meier method was used to construct non-recurrence and EHRA symptom improvement survival curves. The log-rank test was used to detect the difference between the survival distributions of the two curves. Survival analyses were performed using Cox proportional risk models to determine the risk ratios of single and multifactorial predictors of AF recurrence and EHRA symptom score improvement. A P value of <0.05 was considered statistically significant.
Results
Study population
Among 512 total patients, 349 (68.2%) patients had paroxysmal AF, 163 (31.8%) patients had persistent AF, 341 (66.6%) were males, 171 (33.4%) were females, and the median age was 59 [interquartile range (IQR), 52–67] years. During a median follow-up time of 29 (IQR, 18–37) months, 146 (28.5%) patients had a recurrence. In addition, the median LA-FD of the patients was 1.2087 (1.0766, 1.3227). Table 1 shows the baseline characteristics of the study population.
Table 1
Parameters | Value |
---|---|
Age (years) | 59.00 (52.00, 67.00) |
Gender | |
Female | 171 (33.4) |
Male | 341 (66.6) |
BMI (kg/m2) | 24.57 (22.49, 26.71) |
Current smoking | 133 (26.0) |
Drinking | 84 (16.4) |
Hypertension | 238 (46.5) |
Hyperglycaemia | 159 (31.1) |
Hyperlipidemia | 286 (55.9) |
Urea (mmol/L) | 6.31 (5.30, 7.70) |
CREA (μmol/L) | 74.00 (64.00, 84.08) |
Urea/CREA | 0.09 (0.07, 0.11) |
UA (μmol/L) | 342.50 (283.00, 398.00) |
COPD | 180 (35.2) |
TIA/stroke/embolism | 154 (30.1) |
Type of AF | |
Paroxysmal | 349 (68.2) |
Persistent | 163 (31.8) |
CHA2DS2-VaSc score | 2.00 (1.00, 3.00) |
EHRA classification | |
EHRA 1 | 36 (7.0) |
EHRA 2a | 181 (35.4) |
EHRA 2b | 208 (40.6) |
EHRA 3 | 87 (17.0) |
WBC (109/L) | 6.15 (5.24, 7.40) |
NE (109/L) | 3.80 (3.08, 4.86) |
LY (109/L) | 1.64 (1.28, 2.02) |
MO (109/L) | 0.42 (0.35, 0.54) |
PLT (109/L) | 179.50 (138.25, 219.75) |
NLR | 2.32 (1.74, 3.18) |
PLR | 107.33 (84.63, 136.90) |
LMR | 3.76 (2.91, 4.83) |
SII | 402.87 (289.75, 600.04) |
CAD | 206 (40.2) |
LA diameter (mm) | 37.45 (33.20, 42.00) |
LA circumference (mm) | 284.55 (253.80, 312.93) |
LA square (mm2) | 2,729.00 (2,179.48, 3,351.55) |
LA-FD | 1.2087 (1.0766, 1.3227) |
AF recurrence | 146 (28.5) |
Follow-up time (months) | 29.00 (18.00, 37.00) |
Data are presented as median (IQR) or n (%). AF, atrial fibrillation; BMI, body mass index; CREA, creatinine; COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease; EHRA, European Heart Rhythm Association; FD, fractal dimension; IQR, interquartile range; LY, lymphocyte count; LMR, lymphocyte-to-monocyte ratio; LA, left atrium; MO, monocyte count; NE, neutrophil count; NLR, neutrophil-to-lymphocyte ratio; PLT, platelet count; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index [(neutrophil count × platelet count)/lymphocyte count]; TIA, transient ischemic attack; UA, uric acid; WBC, white blood cell count.
Cox regression analysis for AF recurrence
In the univariate analysis, LA-FD [hazard ratio (HR) =18.205, 95% confidence interval (CI): 8.599–38.544, P<0.001] was a significant predictor of recurrence after ablation in all patients with AF, similar to current smoking (HR =1.731, 95% CI: 1.132–2.647, P=0.011) and the type of AF (HR =0.576, 95% CI: 0.415–0.798, P=0.001). Recurrence of AF was not predicted by any other clinical parameters such as age or sex (P>0.05, Table 2). When meaningful univariate values were included in the multivariate analysis (P<0.05), the LA-FD retained its predictive value for AF recurrence (HR =16.056, 95% CI: 7.493, 34.406, P<0.001; Table 2). Kaplan-Meier survival curves revealed a lower incidence of AF recurrence in patients with a small LA-FD (<1.208) than in those with a large LA-FD (>1.208) (Figure 3A).
Table 2
Parameters | Univariate Cox regression | Multivariate Cox regression | |||
---|---|---|---|---|---|
HR (95% CI) | P value | HR (95% CI) | P value | ||
Age (years) | 1.000 (0.985, 1.015) | 0.967 | |||
Gender (male) | 1.210 (0.863, 1.698) | 0.269 | |||
BMI (kg/m2) | 1.009 (0.967, 1.053) | 0.680 | |||
Current smoking | 1.731 (1.132, 2.647) | 0.011 | 0.620 (0.405, 0.949) | 0.028 | |
Drinking | 1.320 (0.815, 2.138) | 0.260 | |||
Hypertension | 1.022 (0.738, 1.415) | 0.897 | |||
Hyperglycaemia | 0.777 (0.550, 1.098) | 0.152 | |||
Hyperlipidemia | 0.915 (0.659, 1.270) | 0.595 | |||
Urea (mmol/L) | 0.977 (0.903, 1.057) | 0.562 | |||
CREA (μmol/L) | 1.002 (0.996, 1.008) | 0.511 | |||
Urea/CREA | 0.733 (0.144, 3.732) | 0.709 | |||
UA (μmol/L) | 0.999 (0.997, 1.001) | 0.320 | |||
COPD | 0.942 (0.672, 1.321) | 0.730 | |||
TIA/stroke/embolism | 0.747 (0.529, 1.056) | 0.098 | |||
Type of AF | 0.576 (0.415, 0.798) | 0.001 | 0.609 (0.439, 0.844) | 0.003 | |
CHA2DS2-VaSc score | 1.078 (0.970, 1.199) | 0.162 | |||
EHRA classification | |||||
EHRA 1 | 0.731 (0.426, 1.254) | 0.255 | |||
EHRA 2a | 1.024 (0.762, 1.377) | 0.873 | |||
EHRA 2b | 1.222 (0.922, 1.621) | 0.163 | |||
EHRA 3 | 0 (Ref) | ||||
WBC (109/L) | 0.970 (0.896, 1.051) | 0.458 | |||
NE (109/L) | 0.968 (0.888, 1.056) | 0.467 | |||
LY (109/L) | 0.934 (0.704, 1.241) | 0.639 | |||
MO (109/L) | 1.163 (0.488, 2.772) | 0.734 | |||
PLT (109/L) | 1.000 (0.997, 1.003) | 0.995 | |||
NLR | 0.984 (0.924, 1.049) | 0.626 | |||
PLR | 1.000 (0.998, 1.002) | 0.809 | |||
LMR | 0.964 (0.872, 1.065) | 0.467 | |||
SII | 1.000 (1.000, 1.000) | 0.597 | |||
CAD | 1.201 (0.858, 1.680) | 0.285 | |||
LA diameter (mm) | 1.004 (0.981, 1.027) | 0.753 | |||
LA circumference (mm) | 0.998 (0.995, 1.002) | 0.364 | |||
LA square (mm2) | 1.000 (1.000, 1.000) | 0.753 | |||
LA-FD | 18.205 (8.599, 38.544) | <0.001 | 16.056 (7.493, 34.406) | <0.001 |
AF, atrial fibrillation; BMI, body mass index; CI, confidence interval; CREA, creatinine; COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease; EHRA, European Heart Rhythm Association; FD, fractal dimension; HR, hazard ratio; LY, lymphocyte count; LMR, lymphocyte-to-monocyte ratio; LA, left atrium; MO, monocyte count; NE, neutrophil count; NLR, neutrophil-to-lymphocyte ratio; PLT, platelet count; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index [(neutrophil count × platelet count)/lymphocyte count]; TIA, transient ischemic attack; UA, uric acid; WBC, white blood cell count.

Cox regression analysis for AF recurrence in patients with paroxysmal AF
In univariate Cox regression analysis, gender (HR =1.595, 95% CI: 1.022–2.490, P=0.040), current smoking (HR =2.213, 95% CI: 1.197–4.089, P=0.011), uric acid level (HR =0.997, 95% CI: 0.995–1.000, P=0.041), and LA-FD (HR =24.310, 95% CI: 9.740–60.671, P<0.001) were predictors of recurrence in patients with paroxysmal AF; other clinical indicators did not predict recurrence in patients with paroxysmal AF (P>0.05), as shown in Table 3. The indicators with P<0.05 in the univariate analysis were included in the multivariate Cox regression analysis, and the results showed that LA-FD (HR 21.750, 95% CI: 8.533–55.444, P<0.001) was a predictor of recurrence in patients with paroxysmal AF (Table 3). The Kaplan-Meier survival curves showed a low incidence of AF recurrence in patients with paroxysmal AF who had a small LA-FD (<1.208) (Figure 3B).
Table 3
Parameters | Univariate Cox regression | Multivariate Cox regression | |||
---|---|---|---|---|---|
HR (95% CI) | P value | HR (95% CI) | P value | ||
Age (years) | 1.004 (0.984, 1.025) | 0.679 | |||
Gender (male) | 1.595 (1.022, 2.490) | 0.040 | 0.806 (0.490, 1.326) | 0.396 | |
BMI (kg/m2) | 0.975 (0.914, 1.039) | 0.432 | |||
Current smoking | 2.213 (1.197, 4.089) | 0.011 | 1.601 (0.818, 3.134) | 0.169 | |
Drinking | 1.892 (0.823, 4.350) | 0.133 | |||
Hypertension | 1.086 (0.696, 1.697) | 0.715 | |||
Hyperglycaemia | 0.772 (0.484, 1.233) | 0.279 | |||
Hyperlipidemia | 0.845 (0.541, 1.320) | 0.459 | |||
Urea (mmol/L) | 0.974 (0.873, 1.085) | 0.629 | |||
CREA (μmol/L) | 1.002 (0.993, 1.011) | 0.656 | |||
Urea/CREA | 0.739 (0.128, 4.267) | 0.735 | |||
UA (μmol/L) | 0.997 (0.995, 1.000) | 0.041 | 0.998 (0.996, 1.001) | 0.185 | |
COPD | 0.977 (0.618, 1.547) | 0.923 | |||
TIA/stroke/embolism | 0.972 (0.592, 1.594) | 0.909 | |||
CHA2DS2-VaSc score | 1.070 (0.930, 1.231) | 0.343 | |||
EHRA classification | |||||
EHRA 1 | 0.634 (0.295, 1.363) | 0.243 | |||
EHRA 2a | 1.112 (0.741, 1.669) | 0.607 | |||
EHRA 2b | 1.231 (0.835, 1.813) | 0.294 | |||
EHRA 3 | 0 (Ref) | ||||
WBC (109/L) | 0.981 (0.885, 1.088) | 0.718 | |||
NE (109/L) | 0.975 (0.872, 1.090) | 0.657 | |||
LY (109/L) | 1.103 (0.752, 1.618) | 0.616 | |||
MO (109/L) | 0.679 (0.199, 2.316) | 0.536 | |||
PLT (109/L) | 1.000 (0.997, 1.004) | 0.764 | |||
NLR | 0.962 (0.874, 1.057) | 0.418 | |||
PLR | 0.999 (0.996, 1.002) | 0.691 | |||
LMR | 1.079 (0.953, 1.222) | 0.232 | |||
SII | 1.000 (1.000, 1.000) | 0.573 | |||
CAD | 1.340 (0.840, 2.137) | 0.219 | |||
LA diameter (mm) | 0.998 (0.966, 1.030) | 0.883 | |||
LA circumference (mm) | 0.998 (0.992, 1.003) | 0.342 | |||
LA square (mm2) | 1.000 (1.000, 1.000) | 0.332 | |||
LA-FD | 24.310 (9.740, 60.671) | <0.001 | 21.750 (8.533, 55.444) | <0.001 |
AF, atrial fibrillation; BMI, body mass index; CI, confidence interval; CREA, creatinine; COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease; EHRA, European Heart Rhythm Association; FD, fractal dimension; HR, hazard ratio; LY, lymphocyte count; LMR, lymphocyte-to-monocyte ratio; LA, left atrium; MO, monocyte count; NE, neutrophil count; NLR, neutrophil-to-lymphocyte ratio; PLT, platelet count; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index [(neutrophil count × platelet count)/lymphocyte count]; TIA, transient ischemic attack; UA, uric acid; WBC, white blood cell count.
Cox regression analysis for AF recurrence in patients with persistent AF
Based on univariate analysis, only transient cerebral ischemic attacks/stroke/embolism (HR =0.550, 95% CI: 0.335–0.903, P=0.018) and LA-FD (HR =8.454, 95% CI: 2.316–30.864, P=0.001) were found to be predictors of recurrence in patients with persistent AF among the baseline characteristics of the patients. In addition, based on multivariate analysis, LA-FD (HR =7.291, 95% CI: 1.977–26.896, P=0.003) maintained its predictive value for the recurrence of persistent AF. The results are summarized in Table 4. Kaplan-Meier survival curves indicated a higher rate of AF recurrence in patients with persistent AF who had a larger LA-FD (>1.208) (Figure 3C).
Table 4
Parameters | Univariate Cox regression | Multivariate Cox regression | |||
---|---|---|---|---|---|
HR (95% CI) | P value | HR (95% CI) | P value | ||
Age (years) | 0.990 (0.968, 1.013) | 0.389 | |||
Gender (male) | 0.895 (0.520, 1.541) | 0.689 | |||
BMI (kg/m2) | 1.030 (0.971, 1.092) | 0.322 | |||
Current smoking | 1.294 (0.716, 2.338) | 0.393 | |||
Drinking | 1.163 (0.633, 2.137) | 0.626 | |||
Hypertension | 1.085 (0.666, 1.767) | 0.744 | |||
Hyperglycaemia | 0.756 (0.451, 1.268) | 0.290 | |||
Hyperlipidemia | 0.986 (0.603, 1.612) | 0.954 | |||
Urea (mmol/L) | 0.947 (0.837, 1.070) | 0.379 | |||
CREA (μmol/L) | 1.001 (0.992, 1.010) | 0.848 | |||
Urea/CREA | 0.171 (0.000, 1,209.035) | 0.696 | |||
UA (μmol/L) | 1.000 (0.998, 1.002) | 0.997 | |||
COPD | 1.010 (0.612, 1.666) | 0.969 | |||
TIA/stroke/embolism | 0.550 (0.335, 0.903) | 0.018 | 0.597 (0.363, 0.982) | 0.042 | |
CHA2DS2-VaSc score | 1.036 (0.873, 1.230) | 0.683 | |||
EHRA classification | |||||
EHRA 1 | 1.120 (0.365, 3.441) | 0.843 | |||
EHRA 2a | 1.102 (0.552, 2.203) | 0.782 | |||
EHRA 2b | 1.439 (0.741, 2.793) | 0.282 | |||
EHRA 3 | 0 (Ref) | ||||
WBC (109/L) | 0.954 (0.840, 1.083) | 0.464 | |||
NE (109/L) | 0.963 (0.839, 1.105) | 0.588 | |||
LY (109/L) | 0.785 (0.523, 1.179) | 0.243 | |||
MO (109/L) | 1.797 (0.450, 7.183) | 0.407 | |||
PLT (109/L) | 1.000 (0.996,1.004) | 0.980 | |||
NLR | 1.012 (0.920, 1.114) | 0.800 | |||
PLR | 1.002 (0.997, 1.007) | 0.521 | |||
LMR | 0.867 (0.742, 1.013) | 0.073 | |||
SII | 1.000 (1.000, 1.001) | 0.632 | |||
CAD | 1.176 (0.718, 1.926) | 0.520 | |||
LA diameter (mm) | 0.991 (0.955, 1.027) | 0.609 | |||
LA circumference (mm) | 0.996 (0.990, 1.002) | 0.198 | |||
LA square (mm2) | 1.000 (1.000, 1.000) | 0.498 | |||
LA-FD | 8.454 (2.316, 30.864) | 0.001 | 7.291 (1.977, 26.896) | 0.003 |
AF, atrial fibrillation; BMI, body mass index; CI, confidence interval; CREA, creatinine; COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease; EHRA, European Heart Rhythm Association; FD, fractal dimension; HR, hazard ratio; LY, lymphocyte count; LMR, lymphocyte-to-monocyte ratio; LA, left atrium; MO, monocyte count; NE, neutrophil count; NLR, neutrophil-to-lymphocyte ratio; PLT, platelet count; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index [(neutrophil count × platelet count)/lymphocyte count; TIA, transient ischemic attack; UA, uric acid; WBC, white blood cell count.
Cox regression analysis for EHRA symptom score non-improvement
Among 146 patients with recurrent AF, median age was 59.53±0.88 years, 93 (63.7%) were males and 53 (36.3%) were females, 81 (55.5%) were patients with paroxysmal AF and 65 (44.5%) were patients with persistent AF. Compared to the preoperative EHRA symptom scores, 48 (32.9%) patients showed improvement and 98 (67.1%) showed no improvement.
The results of univariate Cox regression analysis showed that in addition to hyperlipidemia (HR =0.629, 95% CI: 0.416–0.952, P=0.028), lymphocyte count (HR =1.484, 95% CI: 1.097–2.007, P=0.010), platelet count (HR =1.003, 95% CI: 1.001–1.006, P=0.013), and neutrophil-to-lymphocyte ratio (HR =0.910, 95% CI: 0.836–0.990, P=0.029), LA-FD (HR =7.555, 95% CI: 2.347–24.323, P=0.001) was also a predictor of non-improvement in EHRA symptom scores. Other clinical characteristics such as sex and age did not predict non-improvement in EHRA symptom scores (Table 5). The findings of the multivariate Cox regression analysis suggested that LA-FD (HR =10.500, 95% CI: 3.086–35.728, P<0.001) was an independent predictor of non-improvement in EHRA symptom scores (Table 5). Kaplan-Meier survival curves suggested a lower incidence of EHRA symptom score improvement in patients with a larger LA-FD (>1.208) than in those with a smaller LA-FD (<1.208) (Figure 3D).
Table 5
Parameters | Univariate Cox regression | Multivariate Cox regression | |||
---|---|---|---|---|---|
HR (95% CI) | P value | HR (95% CI) | P value | ||
Age (years) | 0.984 (0.967, 1.001) | 0.065 | |||
Gender (male) | 1.334 (0.875, 2.034) | 0.180 | |||
BMI (kg/m2) | 0.990 (0.932, 1.051) | 0.747 | |||
Current smoking | 0.781 (0.467, 1.308) | 0.348 | |||
Drinking | 0.879 (0.479, 1.613) | 0.677 | |||
Hypertension | 1.234 (0.824, 1.847) | 0.308 | |||
Hyperglycaemia | 1.013 (0.662, 1.550) | 0.953 | |||
Hyperlipidemia | 0.629 (0.416, 0.952) | 0.028 | 0.707 (0.456, 1.095) | 0.121 | |
Urea (mmol/L) | 0.960 (0.871, 1.059) | 0.414 | |||
CREA (μmol/L) | 1.002 (0.996, 1.008) | 0.560 | |||
Urea/CREA | 0.250 (0.000, 293.268) | 0.701 | |||
UA (μmol/L) | 0.998 (0.997, 1.000) | 0.132 | |||
COPD | 1.240 (0.822, 1.871) | 0.305 | |||
TIA/stroke/embolism | 1.066 (0.687, 1.654) | 0.775 | |||
Type of AF | 0.980 (0.649, 1.481) | 0.924 | |||
CHA2DS2-VaSc score | 0.911 (0.799, 1.038) | 0.163 | |||
EHRA classification | |||||
EHRA 1 | 0.820 (0.307, 2.190) | 0.692 | |||
EHRA 2a | 1.306 (0.705, 2.416) | 0.396 | |||
EHRA 2b | 1.051 (0.568, 1.943) | 0.875 | |||
EHRA 3 | 0 (Ref) | ||||
WBC (109/L) | 1.003 (0.918, 1.095) | 0.954 | |||
NE (109/L) | 0.966 (0.875, 1.068) | 0.503 | |||
LY (109/L) | 1.484 (1.097, 2.007) | 0.010 | 1.095 (0.706, 1.697) | 0.686 | |
MO (109/L) | 1.227 (0.441, 3.416) | 0.695 | |||
PLT (109/L) | 1.003 (1.001, 1.006) | 0.013 | 1.002 (0.999, 1.005) | 0.126 | |
NLR | 0.910 (0.836, 0.990) | 0.029 | 0.918 (0.828, 1.019) | 0.107 | |
PLR | 0.999 (0.995, 1.002) | 0.382 | |||
LMR | 1.107 (0.988, 1.240) | 0.080 | |||
SII | 1.000 (0.999, 1.000) | 0.279 | |||
CAD | 1.408 (0.922, 2.150) | 0.113 | |||
LA diameter (mm) | 0.995 (0.964, 1.027) | 0.746 | |||
LA circumference (mm) | 0.997 (0.993, 1.002) | 0.224 | |||
LA square (mm2) | 1.000 (1.000, 1.000) | 0.287 | |||
LA-FD | 7.555 (2.347, 24.323) | 0.001 | 10.500 (3.086, 35.728) | <0.001 |
AF, atrial fibrillation; BMI, body mass index; CI, confidence interval; CREA, creatinine; COPD, chronic obstructive pulmonary disease; CAD, coronary artery disease; EHRA, European Heart Rhythm Association; FD, fractal dimension; HR, hazard ratio; LY, lymphocyte count; LMR, lymphocyte-to-monocyte ratio; LA, left atrium; MO, monocyte count; NE, neutrophil count; NLR, neutrophil-to-lymphocyte ratio; PLT, platelet count; PLR, platelet-to-lymphocyte ratio; SII, systemic immune-inflammation index [(neutrophil count × platelet count)/lymphocyte count; TIA, transient ischemic attack; UA, uric acid; WBC, white blood cell count.
Discussion
The aim of the present study was to investigate the relationship between LA-FD and recurrence after ablation for AF and to determine whether the EHRA symptom score improves after treatment. The FD can be used as a quantitative marker to characterize LA morphology and has been used to assess several cardiovascular diseases (13,14). The main finding of the present study was that LA-FD was an independent predictor of recurrence and non-improvement in EHRA symptom scores after AF ablation. In addition, patients with a larger LA-FD (>1.208) had a higher incidence of recurrent AF and no improvement in the EHRA symptom scores than those with a smaller LA-FD (<1.208).
The LA is recognized as an indicator of adverse cardiovascular outcomes, particularly the occurrence, progression, and prognosis of AF (15-17). LA remodeling is a crucial factor that contributes to recurrence after AF ablation (7,18). LA remodeling includes neural, electrical, and structural remodeling, and its structural remodeling is characterized by changes in LA size parameters detectable by imaging (19,20). A retrospective study found that the ratio of the larger box lesion surface area to the total LA surface area was protective against recurrence after persistent AF ablation (21). Wang et al. (22) showed that both larger and smaller LA diameters and an ellipsoidal model/body surface area were associated with a higher risk of AF recurrence one year after radiofrequency ablation. Chollet et al. (23) found that an LA volume index ≥42 mL/m2 was an independent predictor of recurrence 1 year after pulmonary vein isolation in patients with AF. A meta-analysis suggested that a larger LA volume/volume index increases the risk of AF recurrence after radiofrequency ablation (24). Thus, LA remodeling is an established cause of recurrence after AF ablation and can be clinically monitored by imaging.
Currently, LA remodeling is characterized by its morphological features (25,26). Shi et al. (25) demonstrated that the LA sphericity index was an independent predictor of AF recurrence following radiofrequency ablation. Nedios et al. (26) reported a higher LA asymmetry index after ablation in patients with AF recurrence than in those without recurrence. A study of two cohorts showed that fractal LA measurements on CT images were related to AF recurrence after ablation (27). In addition, Bisbal et al. (7) determined that LA sphericity quantified using a 3D model of the LA chamber is one of the strongest predictors of recurrence after AF ablation. In the current study, we found that FD, as a quantitative characterization of LA morphologic heterogeneity, was significantly correlated with AF ablation outcomes, and that a high FD predicted a higher rate of postprocedural recurrence. This may be explained by the fact that a larger FD indicates poor structural remodeling of the LA, which promotes electrical remodeling and creates a favorable environment for the development of AF.
Another important aspect confirmed in this study is that LA-FD was also associated with no improvement in EHRA symptom scores. This was predictable because patients with non-improvement in EHRA symptom scores usually have a poorer clinical prognosis, which may be closely related to adverse LA remodeling (15,28). Moreover, we observed that AF type was a clinically valid predictor of AF recurrence after ablation, which is consistent with previous studies (29,30). Interestingly, we stratified patients with AF and showed that a high LA-FD was associated with a higher rate of postoperative AF recurrence, both in patients with paroxysmal and those with persistent AF. Therefore, FD can be used as an indicator for the preoperative evaluation of AF ablation in the clinic, thereby helping to select the patients who will have the optimum benefit from the procedure.
Recent artificial intelligence (AI)-enabled LA volumetry techniques have demonstrated high predictive accuracy for AF and stroke (31-33). However, our findings suggest that FD analysis captures finer morphological details that are not reflected in volume-based assessments. While AI volumetry offers rapid and automated analysis, FD provides unique insights into atrial morphology, offering potential for early detection of atrial remodeling and fibrosis. Integrating FD with AI volumetry could provide a more comprehensive evaluation of atrial remodeling, aiding in personalized risk stratification.
Previous studies have shown that AF is more prevalent in males than females, which could account for the higher proportion of male patients in this study cohort (34,35). The lack of significant gender differences in AF recurrence and symptom improvement may also be explained by the fact that structural remodeling in the left atrium, such as changes in LA morphology and size, may affect both male and female patients similarly. Nonetheless, gender-related factors such as hormonal differences and comorbidities could still play a role in long-term outcomes, and further studies with larger cohorts and longer follow-up periods are warranted to investigate these potential differences in greater depth.
This study had some limitations. First, this was designed as a single-center retrospective study, and some patients with incomplete information or those lost to follow-up were excluded, which may have led to selection bias. In contrast, follow-up was prospective and meaningful. Second, the morphological heterogeneity of the LA, except for quantification by FD, should be explored to determine the correlation between additional morphological indicators and AF recurrence. Finally, in addition to AF recurrence, the prognostic value of LA-FD may be applied to other cardiac conditions, warranting further exploration.
Conclusions
In conclusion, a larger LA-FD (>1.208) on cardiac CTA images is an indication of adverse LA remodeling and an independent predictor of recurrence and non-improvement in the EHRA symptom score after ablation for AF.
Acknowledgments
The abstract of this manuscript has been accepted for presentation as an oral paper presentation at the 110th Scientific Assembly and Annual Meeting of the Radiological Society of North America (Session Number: T7-SSCA06).
Footnote
Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-2049/rc
Funding: This work was supported by
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2049/coif). W.R. reports that he is an Employee of GE Healthcare, the manufacturer of the CT scanner used in this study. J.Z. reports that this work was supported by the National Natural Science Foundation of China (grant No. 82371914), and Medical Innovation and Development Project of Lanzhou University (No. lzuyxcx-2022-139). The other authors have no conflicts of interest to declare.
Ethical Statement:
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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