Author's summary
Atrial fibrillation (AF) is uncommon in the young but increasingly diagnosed, often without comorbidities. From 80 young and old AF patients, we compared atrial metabolism using 18F-fluorodeoxyglucose (FDG) positron emission tomography. While atrial FDG uptake did not differ by age, we noted an age-transcending contributory role of right atrium (RA) on AF progression: persistent AF was independently related to an increased RA FDG uptake, irrespective of age. Furthermore, current drinking and increased atrial FDG uptake association raises the hypothesis that young AF may, in part, be driven by lifestyle-related atrial metabolic alterations, given their higher prevalence of alcohol consumption.
Keywords: Atrial fibrillation, Young, Age, FDG PET, Atrial metabolic activity, Right atrium
Abstract
Background and Objectives
The atrial metabolic profile and underlying pathophysiology of young-onset atrial fibrillation (AF) may differ from those of old-onset AF, but age-related alterations in atrial metabolism remain poorly understood. We explored potential age-related atrial metabolic differences using 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging.
Methods
We prospectively performed FDG PET with myocardial suppression in 40 young-onset and 40 old-onset AF patients. FDG uptake of the right and left atrium (RA and LA) was assessed visually (grade 0–3) and quantitatively using target-to-background ratio (TBR).
Results
The mean age was 59.3±13.5 (young-onset, 47.0±5.2; old-onset, 71.6±5.5) years, with a median AF duration of 3.6 (0.8–6.8) years. Among 80 patients (41 paroxysmal, 39 persistent AF), the distribution of AF type was similar between age groups (p=0.121). A total of 51 patients (63.7%) showed atrial FDG uptake ≥mild (grade≥1). No significant age-related differences were observed in visual FDG uptake or TBR in either atrial wall or appendage. Current drinking and persistent AF type were independently associated with increased atrial FDG uptake, primarily in the RA. Persistent AF was consistently associated with elevated RA uptake across age groups (adjusted odds ratio, 10.2, 95% confidence interval, 1.9–55.3; p=0.007). Quantitative analysis revealed significantly higher RA-to-LA metabolic ratios in persistent AF, consistent across age groups.
Conclusions
Atrial FDG uptake patterns did not differ by age in patients with AF. Increased RA FDG uptake in persistent AF was consistently observed, suggesting a shared metabolic alteration underlying AF progression transcending age-related pathological differences.
Graphical Abstract
INTRODUCTION
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia with increasing prevalence and related healthcare burden.1),2) AF is often prevalent among the elderly with concomitant cardiovascular risk factors, but an increasing number of younger individuals are being diagnosed, often in the absence of overt structural heart disease or related comorbidities.3) This has raised important questions about the underlying mechanisms contributing to AF in different age groups.
Atrial metabolic deregulation and consequent structural or functional remodeling are well-established hallmarks of the initiation and maintenance of AF.4) Alterations in myocardial glucose metabolism, oxidative stress, and mitochondrial function have been implicated in atrial remodeling with the consequence of electrophysiologic change.5),6),7) Although several studies demonstrated altered atrial energy demands in AF resulting in metabolic stress,8),9) it remains unclear whether the metabolic profile of the atrial myocardium differs between young and elderly patients with AF.
18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is a non-invasive imaging modality that allows for the in vivo assessment of myocardial glucose uptake and has been increasingly used to explore cardiac metabolic activity.10) By utilizing FDG PET, we can quantitatively evaluate atrial myocardial metabolic changes associated with AF.11) Several studies have reported associations between altered atrial metabolic status in AF and increased FDG uptake, thereby validating FDG PET as a promising tool for investigating the atrial substrate in this population.4),12)
In this study, we aimed to compare the cardiac metabolic profiles of young and elderly patients with AF using FDG PET imaging. Our goal was to identify potential distinct metabolic signatures associated with atrial remodeling in young and elderly AF patients and provide insights into age-specific pathophysiological mechanisms of AF.
METHODS
Ethical statement
The Institutional Review Board at Seoul National University Hospital (H-2108-043-1243) approved this study. Written informed consent was obtained from all the participants who agreed and understood our research.
Study participants
From October 2021 to June 2024, we prospectively enrolled patients at a tertiary referral center (Seoul National University Hospital) diagnosed with AF. There is no universally accepted age cutoff to define early-onset AF. Previous studies have applied thresholds such as 40 or 66 years, largely based on investigators’ discretion.13),14),15) In this study, we adopted an age cutoff of 60 years, consistent with prior large cohort studies investigating early-onset AF.16),17),18),19) To better capture age-related differences in AF pathophysiology, we also introduced an intentional 10-year gap. Accordingly, we defined the “young AF” group as patients diagnosed with AF at ≤50 years of age and who were younger than 60 years at the time of enrollment. As a comparator, the “old AF” group included patients diagnosed with AF at ≥60 years of age, matched to the young AF group by sex and AF type. Patients were excluded if they had structural heart disease, a history of cardiac surgery, myocardial infarction or non-cardiac surgery within 3 months prior to enrollment, malignancy, active infectious or autoimmune disease, a history of AF catheter ablation within one year, or current pregnancy.
Sample size calculation
Given the lack of prior research on age-associated differences in atrial metabolic activity in AF, the number of patients to be included were exploratorily determined. At the time of 35 young AF patients were prospectively enrolled, we observed 24 (68.5%) patients demonstrated increased atrial FDG uptake. This proportion was notably higher than the 37.5–54.5% prevalence reported in prior studies of older AF populations with mean ages of 65–72 years.8),9),20) Based on the hypothesis that young AF would demonstrate a higher prevalence of atrial FDG uptake than old AF, and assuming proportions of 0.685 vs. 0.4, we estimated that 39 patients per group (approximately 80 in total) would be required, with power (1−β) of 0.8 and a type I error (α) of 5%, using a 1:1 sampling ratio. We prospectively enrolled 42 young and 43 old AF patients. Of these, 4 patients withdrew consent, and 1 patient was diagnosed with metastatic cancer shortly after enrollment. Finally, study population comprised 40 young and 40 old AF patients.
The demographic information, comorbidities, and laboratory results were collected at the time of enrollments. Lifestyle behavior (i.e., current smoking and current drinking) was investigated in a self-reported way. The questionnaire assessed both the frequency of drinking per week and the amount consumed per session. Echocardiographic parameters were investigated based on the most recent value from the enrollment date (median time duration to the echocardiographic examination, interquartile range (IQR): 1.3 [0.2–2.9] years).
The evaluation of atrial 18F-fluorodeoxyglucose positron emission tomography uptake
The patients had a high-fat low-carbohydrate diet and extended fasting (≥12 hours) before FDG injection to suppress physiological myocardial FDG uptake.20),21) As a result, 85% of the patients (68/80) achieved fair or better myocardial suppression.
FDG PET images were obtained using a dedicated PET/computed tomography (CT) scanner (Biograph mCT40; Siemens, Erlangen, Germany), 60 minutes after intravenous administration of FDG (5.2 MBq/kg). Unenhanced CT scan was performed first for attenuation correction and anatomical localization. PET images were acquired for 6–7 bed positions, from the vertex to the upper thigh, for 1 min/bed position. PET images were reconstructed using an iterative algorithm (ordered-subset expectation maximization) with CT-based attenuation correction.
For qualitative analysis of atrial uptake, the PET/CT fusion images were independently reviewed by 2 nuclear physicians (JCP and KK) who were blinded to patient’s medical records, using a 4-point grading system: grade 0, atrial FDG uptake was lower than the adjacent blood pool (background); grade 1, mild atrial FDG uptake which was slightly higher than the background; grade 2, moderate atrial FDG uptake which was significantly higher than the background; and grade 3, marked atrial FDG uptake which was evidently higher than the background. Grade 1–3 (≥ mild) atrial FDG uptake was defined as increased atrial uptake. The representative grading of visual atrial uptake is presented in Figure 1. The uptake site in the atria was recorded as wall or appendage in right atrium (RA) or left atrium (LA). Any increased atrial uptake in RA or LA was defined as biatrial uptake. In cases of discordant findings, the final decision was made by consensus.
Figure 1. Representative figures of 18F-fluorodeoxyglucose positron emission tomography visual uptake and corresponding target-to-background ratio of right atrium wall.
For quantitative analysis, standardized uptake value (SUV) was measured using a vendor-supplied tool package (Syngo.via; Siemens). A volume-of-interest (VOI) was drawn to encircle the highest uptake in each of RA, LA, RA appendage (RAA), and LA appendage (LAA), and the maximum SUV (SUVmax) was measured. As a reference tissue, blood pool activity was measured on LA and RV, respectively. Spherical VOIs of 2.0 cm3 size were drawn not to include any wall uptake, and the mean SUVs (SUVmean) of LA and RV were averaged. Target-to-background ratio (TBR) was calculated by dividing atrial SUVmax by SUVmean of blood pool.
Statistical analysis
Continuous variables are expressed as mean ± standard deviation or as median with IQR, depending on their distribution. Comparisons between groups for continuous variables were performed using Student’s t-test or the Mann–Whitney U test, as appropriate. Categorical variables are summarized as counts and percentages, and were compared using Pearson’s χ2 test or Fisher’s exact test, as required. Clinical factors associated with an increased atrial FDG uptake (visual grade ≥ mild) were evaluated by multivariable logistic regression analysis and reported as odds ratio (OR) with 95% confidence intervals (CIs). In multivariable logistic regression model, elevated blood pressure (BP) was defined as either systolic BP ≥120 mmHg or diastolic BP ≥70 mmHg.22) LA volume index >40mL/m2 and E/E’ ≥8 were regarded as increased values with significance.23)
To confirm the consistency of the major finding, sensitivity analysis was performed by dividing patients into 3 age categories (<50, 50–70, and >70 years). Considering the small sample size of each age group, the number of covariates included in the multivariable logistic regression was minimized.
All analyses were conducted using Stata (version 18; StataCorp LLC, College Station, TX, USA). A 2-sided p value <0.05 was considered as statistically significant. The reliability of FDG uptake measurement was assessed using the intraclass and interclass correlation coefficients (ICCs).
RESULTS
Baseline characteristics
The baseline characteristics of the study participants are described in Table 1. Of the total population (mean age, 59.3±13.5 years; male, 72.5%; persistent AF, 48.8%), the median AF duration was 3.6 (0.8–6.8) years. The mean CHA2DS2-VASc score was 1.8±1.4 and 51.2% (n=41) of the participants were on current drinking status. The mean LA diameter was 43.7±8.7 mm and E/e’ was 9.1±3.0.
Table 1. Baseline characteristics of the participants.
| Total (n=80) | Young AF group (n=40) | Old AF group (n=40) | p value | ||
|---|---|---|---|---|---|
| Age (years) | 59.3±13.5 | 47.0±5.2 | 71.6±5.5 | <0.001 | |
| Male | 58 (72.5) | 31 (77.5) | 27 (67.5) | 0.318 | |
| BMI (kg/m2) | 25.3±2.9 | 25.7±3.0 | 24.9±2.8 | 0.288 | |
| AF type | 0.121 | ||||
| Paroxysmal | 41 (51.2) | 24 (60.0) | 17 (42.5) | ||
| Persistent | 39 (48.8) | 16 (40.0) | 23 (57.5) | ||
| AF duration (years) | 3.6 (0.8–6.8) | 3.3 (0.8–6.9) | 3.7 (0.9–6.8) | 0.843 | |
| Comorbidities | |||||
| Hypertension | 40 (50.0) | 17 (42.5) | 23 (57.5) | 0.181 | |
| Diabetes mellitus | 19 (23.8) | 6 (15.0) | 13 (32.5) | 0.066 | |
| Heart failure | 6 (7.5) | 1 (2.5) | 5 (12.5) | 0.090 | |
| Vascular disease | 3 (3.8) | 0 (0.0) | 3 (7.5) | 0.077 | |
| Stroke/systemic embolism | 2 (2.5) | 0 (0.0) | 2 (5.0) | 0.145 | |
| Hyperlipidemia | 29 (36.2) | 8 (20.0) | 21 (52.5) | 0.002 | |
| CHA2DS2-VASc | 1.8±1.4 | 0.8±0.9 | 2.7±1.2 | <0.001 | |
| Current smoking | 8 (10.0) | 5 (12.5) | 3 (7.5) | 0.012 | |
| Current alcohol drinking | 41 (51.2) | 22 (55.0) | 19 (47.5) | 0.002 | |
| Medications | |||||
| Class Ic AAD | 35 (43.8) | 19 (47.5) | 16 (40.0) | 0.200 | |
| Class III AAD | 12 (15.0) | 7 (17.5) | 5 (12.5) | 0.761 | |
| Beta blocker | 51 (63.8) | 24 (60.0) | 27 (67.5) | 0.163 | |
| Calcium channel blocker | 10 (12.5) | 1 (2.5) | 9 (22.5) | 0.028 | |
| Oral anticoagulants | 45 (56.3) | 9 (22.5) | 36 (90.0) | <0.001 | |
| Antiplatelets | 10 (12.5) | 7 (17.5) | 3 (7.5) | 0.261 | |
| Laboratory tests | |||||
| SBP (mmHg) | 130.5±15.1 | 130.7±14.9 | 130.2±15.4 | 0.892 | |
| DBP (mmHg) | 76.5±11.2 | 79.6±10.2 | 73.4±11.4 | 0.014 | |
| HR (/min) | 78.4±13.3 | 79.6±14.6 | 77.2±11.9 | 0.419 | |
| WBC (103/μl) | 6.3±1.4 | 6.3±1.5 | 6.2±1.2 | 0.904 | |
| Hb (g/dL) | 14.5±1.7 | 14.7±1.7 | 14.2±1.7 | 0.221 | |
| Platelet (103/μl) | 222.5±53.8 | 245.5±46.3 | 200.7±51.7 | <0.001 | |
| Fasting glucose (mg/dL) | 108.3±17.2 | 105.8±16.8 | 110.8±17.4 | 0.209 | |
| Echocardiography | |||||
| LVEF (%) | 60.0±4.9 | 59.8±5.0 | 60.2±4.9 | 0.748 | |
| LVIDd (mm) | 47.8±4.7 | 48.0±4.4 | 47.5±5.0 | 0.671 | |
| LVIDs (mm) | 30.4±4.0 | 30.7±4.1 | 30.1±4.0 | 0.603 | |
| LA diameter (mm) | 43.7±8.7 | 41.6±7.5 | 45.6±9.3 | 0.056 | |
| LAVI (mL/m2) | 44.3±16.7 | 42.7±18.6 | 45.6±15.3 | 0.534 | |
| E/E' | 9.1±3.0 | 7.5±2.4 | 10.4±3.0 | <0.001 | |
Values are presented as number (%).
AAD = antiarrhythmic drug; AF = atrial fibrillation; BMI = body mass index; DBP = diastolic blood pressure; Hb = hemoglobin; HR = heart rate; LA = left atrium; LAVI = left atrial volume index; LVEF = left ventricular ejection fraction; LVIDd = left ventricular internal dimension at end-diastole; LVIDs = left ventricular internal dimension at end-systole; SBP = systolic blood pressure; WBC = white blood cell.
The mean age of the young AF and old AF was 47.0±5.2 and 71.6±5.5 years: mean CHA2DS2-VASc score, 0.8±0.9 and 2.7±1.2, respectively (p<0.001). The proportion of persistent AF was 40.0% (n=16) in young AF and 57.5% (n=23) in old AF without a significant difference (p=0.121).
Compared to the old AF, the young AF participants had a higher proportion of current smoking (12.5% vs. 7.5%, p=0.012) and current drinking habits (55.0% vs. 47.5%, p=0.002). The LA tends to be more dilated in the old than the young (41.6±7.5 mm vs. 45.6±9.3 mm, p=0.056) with higher E/E’ value (7.5±2.4 vs. 10.4±3.0, p<0.001).
The baseline characteristics according to AF type is presented in Supplementary Table 1. The mean age and CHA2DS2-VASc score were similar between paroxysmal and persistent AF (p>0.05). The mean AF duration was 2.8 (0.7–5.0) and 4.1 (1.9–7.7) years for paroxysmal and persistent AF, respectively (p=0.031). Those with persistent AF had a larger LA diameter than paroxysmal AF (39.3±6.8 mm vs. 48.3±8.0 mm, p<0.001).
18F-fluorodeoxyglucose positron emission tomography uptake of atrium
The qualitative and quantitative assessment of FDG PET uptake of atrium is summarized in Table 2. Intra-observer variability and inter-observer variability between 2 independent investigators were excellent for the TBR measurement of RA wall, RAA, LA wall, and LAA (all ICCs, 0.963–0.998) (Supplementary Table 2).
Table 2. The qualitative and quantitative assessment of atrial FDG uptake.
| Total (n=80) | Young AF (n=40) | Old AF (n=40) | p value | Paroxysmal AF (n=41) | Persistent AF (n=39) | p value | |||
|---|---|---|---|---|---|---|---|---|---|
| FDG visual uptake | |||||||||
| RA wall | 0.061 | 0.001 | |||||||
| No | 36 (45.0) | 17 (42.5) | 19 (47.5) | 27 (65.9) | 9 (23.1) | ||||
| Mild | 29 (36.2) | 19 (47.5) | 10 (25.0) | 10 (24.4) | 19 (48.7) | ||||
| Moderate | 11 (13.8) | 2 (5.0) | 9 (22.5) | 2 (4.9) | 9 (23.1) | ||||
| Marked | 4 (5.0) | 2 (5.0) | 2 (5.0) | 2 (4.9) | 2 (5.1) | ||||
| RAA | 0.013 | <0.001 | |||||||
| No | 52 (65.0) | 32 (80.0) | 20 (50.0) | 35 (85.4) | 17 (43.6) | ||||
| Mild | 18 (22.5) | 6 (15.0) | 12 (30.0) | 3 (7.3) | 15 (38.5) | ||||
| Moderate | 6 (7.5) | 0 (0.0) | 6 (15.0) | 1 (2.4) | 5 (12.8) | ||||
| Marked | 4 (5.0) | 2 (5.0) | 2 (5.0) | 2 (4.9) | 2 (5.1) | ||||
| LA wall | 0.481 | 0.329 | |||||||
| No | 49 (61.3) | 24 (60.0) | 25 (62.5) | 25 (61.0) | 24 (61.5) | ||||
| Mild | 19 (23.8) | 8 (20.0) | 11 (27.5) | 11 (26.8) | 8 (20.5) | ||||
| Moderate | 8 (10.0) | 6 (15.0) | 2 (5.0) | 2 (4.9) | 6 (15.4) | ||||
| Marked | 4 (5.0) | 2 (5.0) | 2 (5.0) | 3 (7.3) | 1 (2.6) | ||||
| LAA | 0.563 | 0.110 | |||||||
| No | 60 (75.0) | 31 (77.5) | 29 (72.5) | 34 (82.9) | 26 (66.7) | ||||
| Mild | 8 (10.0) | 5 (12.5) | 3 (7.5) | 2 (4.9) | 6 (15.4) | ||||
| Moderate | 8 (10.0) | 3 (7.5) | 5 (12.5) | 2 (4.9) | 6 (15.4) | ||||
| Marked | 4 (5.0) | 1 (2.5) | 3 (7.5) | 3 (7.3) | 1 (2.6) | ||||
| Atrial visual uptake ≥ mild | |||||||||
| RA | |||||||||
| Wall | 44 (55.0) | 23 (57.5) | 21 (52.5) | 0.650 | 14 (34.1) | 30 (76.9) | <0.001 | ||
| Appendage | 28 (35.0) | 8 (20.0) | 20 (50.0) | 0.005 | 6 (14.6) | 22 (56.4) | <0.001 | ||
| Either wall or appendage | 46 (57.5) | 24 (60.0) | 22 (55.0) | 0.645 | 15 (36.6) | 31 (79.5) | <0.001 | ||
| LA | |||||||||
| Wall | 31 (38.8) | 16 (40.0) | 15 (37.5) | 0.818 | 16 (39.0) | 15 (38.5) | 0.964 | ||
| Appendage | 20 (25.0) | 9 (22.5) | 11 (27.5) | 0.612 | 7 (17.1) | 13 (33.3) | 0.093 | ||
| Either wall or appendage | 33 (41.2) | 16 (40.0) | 17 (42.5) | 0.819 | 16 (39.0) | 17 (43.6) | 0.675 | ||
| Biatrium | |||||||||
| Wall | 50 (62.5) | 25 (62.5) | 25 (62.5) | 1.000 | 20 (48.8) | 30 (76.9) | 0.009 | ||
| Appendage | 32 (40.0) | 12 (30.0) | 20 (50.0) | 0.068 | 9 (22.0) | 23 (59.0) | <0.001 | ||
| Either wall or appendage | 51 (63.7) | 26 (65.0) | 25 (62.5) | 0.821 | 20 (48.8) | 31 (79.5) | 0.004 | ||
| FDG SUV and TBR | |||||||||
| LA SUVave | 1.59 (1.44–1.69) | 1.58 (1.42–1.68) | 1.60 (1.52–1.76) | 0.221 | 1.57 (1.41–1.68) | 1.61 (1.49–1.69) | 0.293 | ||
| RA wall SUVmax | 2.67 (2.29–3.23) | 2.67 (2.38–3.16) | 2.73 (2.25–3.33) | 0.649 | 2.42 (2.14–2.65) | 3.07 (2.70–3.47) | 0.005 | ||
| RAA SUVmax | 2.15 (1.93–2.96) | 2.04 (1.87–2.32) | 2.41 (2.00–3.12) | 0.031 | 1.98 (1.69–2.14) | 2.44 (2.16–3.12) | 0.019 | ||
| LA wall SUVmax | 2.66 (2.34–3.15) | 2.73 (2.40–3.38) | 2.62 (2.26–2.83) | 0.599 | 2.63 (2.20–2.89) | 2.75 (2.43–3.23) | 0.988 | ||
| LAA SUVmax | 2.37 (2.12–2.84) | 2.41 (2.15–2.84) | 2.31 (2.11–2.90) | 0.663 | 2.22 (1.96–2.44) | 2.62 (2.26–2.95) | 0.642 | ||
| LV wall SUVmax | 3.97 (2.64–6.14) | 3.62 (2.59–5.81) | 4.08 (2.80–6.29) | 0.651 | 4.02 (2.76–6.68) | 3.93 (2.56–6.00) | 0.751 | ||
| RA wall TBR | 1.66 (1.41–1.99) | 1.68 (1.53–1.86) | 1.48 (1.34–2.07) | 0.932 | 1.49 (1.38–1.70) | 1.89 (1.61–2.16) | 0.083 | ||
| RAA TBR | 1.33 (1.19–1.74) | 1.31 (1.20–1.46) | 1.44 (1.18–1.91) | 0.071 | 1.26 (1.15–1.38) | 1.53 (1.26–1.94) | 0.129 | ||
| LA wall TBR | 1.66 (1.49–1.91) | 1.71 (1.52–2.21) | 1.56 (1.40–1.82) | 0.499 | 1.57 (1.45–1.86) | 1.69 (1.53–1.94) | 0.555 | ||
| LAA TBR | 1.46 (1.33–1.76) | 1.51 (1.40–1.68) | 1.37 (1.26–1.81) | 0.877 | 1.38 (1.32–1.53) | 1.59 (1.38–1.97) | 0.864 | ||
| LV wall TBR | 2.44 (1.55–4.13) | 2.24 (1.59–3.87) | 2.62 (1.55–4.18) | 0.735 | 2.41 (1.70–4.36) | 2.47 (1.52–4.10) | 0.851 | ||
Values are presented as number (%) or number (range).
AF = atrial fibrillation; FDG = 18F-fluorodeoxyglucose; LA = left atrium; LAA = left atrial appendage; RA = right atrium; RAA = right atrial appendage; SUV = standardized uptake value; SUVave = average standardized uptake value; SUVmax = maximal standardized uptake value; TBR = target-to-background ratio.
Of total, increased FDG uptake in RA and LA (visual grade ≥ mild) was observed in 57.5% (n=46) and 41.2% (n=33) of the participants, respectively. Accordingly, 63.7% (n=51) had increased FDG uptake in either RA or LA. Compared to the young AF, a higher proportion of increased FDG uptake in RAA was observed in the old AF (50% vs. 20%; p=0.005).
With respect to the AF type, there was no difference in the pattern of LA FDG uptake between paroxysmal and persistent AF participants. However, persistent AF patients showed a higher proportion of increased FDG uptake in RA than those with paroxysmal AF: either for RA or RAA, 36.6% (n=15) vs. 79.5% (n=31), p<0.001. Contributed by a higher FDG uptake in RA, the increased biatrial FDG uptake was more frequently observed in persistent AF than paroxysmal AF: 31 (79.5%) vs. 20 (48.8%), p=0.004. Quantitatively, the SUVmax of RA wall in paroxysmal and persistent AF was 2.42 (2.14–2.65) vs. 3.07 (2.70–3.47), respectively (p=0.005). The SUVmax of RAA in paroxysmal and persistent AF was 1.98 (1.69–2.14) vs. 2.44 (2.16–3.12), respectively (p=0.019).
Clinical factors associated with an increased atrial 18F-fluorodeoxyglucose uptake
The multivariable logistic regression analysis of clinical risk factors related to an increased atrial FDG uptake is presented in Table 3. For biatrial, persistent AF type and current drinking were associated with an increased atrial FDG uptake (visual grade ≥ mild): adjusted OR (95% CI) was 5.490 (1.028–29.330) for persistent AF and 4.837 (1.142–20.477) for current drinking (both p<0.05). The increased odds of biatrial uptake according to persistent AF was predominantly driven by an increased uptake of RA. The clinical factor associated with an increased RA FDG uptake was persistent AF: adjusted OR (95% CI), 10.193 (1.878–55.324), p=0.007. There was no significant clinical factor related to an increased LA FDG uptake. When stratified by age, the increased biatrial FDG uptake in accordance with persistent AF type and current drinking status was consistent between young and old AF (p-for-interaction=0.836 and 0.714, respectively). The increased RA FDG uptake in persistent AF type was also consistent across age group (p-for-interaction=0.819, Table 4). When patients were divided into 3 age categories (<50, 50–70, and >70 years), the association between increased RA FDG uptake and persistent AF was consistently observed across subgroups (p-for-interaction=0.246, Supplementary Table 3).
Table 3. Multivariable logistic regression of clinical factors associated with an increased visual atrial FDG uptake.
| Clinical factors related to atrial FDG visual uptake ≥ mild (grade 1) | Adjusted OR (95% CI) for each atrium | |||||
|---|---|---|---|---|---|---|
| Biatrial (RA or LA) | p value | RA | p value | LA | p value | |
| Age (per 1 year increase) | 0.999 (0.944–1.058) | 0.984 | 0.968 (0.911–1.028) | 0.284 | 1.009 (0.958–1.062) | 0.739 |
| AF type (persistent AF) | 5.490 (1.028–29.330) | 0.046 | 10.193 (1.878–55.324) | 0.007 | 1.336 (0.332–5.370) | 0.683 |
| Current drinking | 4.837 (1.142–20.477) | 0.032 | 2.707 (0.643–11.403) | 0.175 | 1.876 (0.545–6.460) | 0.319 |
| Elevated BP (SBP ≥120 mmHg or DBP ≥70 mmHg) | 3.193 (0.594–17.172) | 0.176 | 2.372 (0.404–13.929) | 0.339 | 1.050 (0.237–4.659) | 0.949 |
| LVEF (per 1% increase) | 1.003 (0.869–1.157) | 0.968 | 1.062 (0.919–1.227) | 0.417 | 0.910 (0.799–1.036) | 0.154 |
| LAVI (>40 mL/m2) | 0.690 (0.143–3.322) | 0.643 | 1.850 (0.394–8.685) | 0.436 | 0.601 (0.157–2.308) | 0.459 |
| E/E' (≥8) | 2.366 (0.453–12.361) | 0.307 | 2.254 (0.433–11.726) | 0.334 | 0.938 (0.230–3.821) | 0.929 |
AF = atrial fibrillation; BP = blood pressure; CI = confidence interval; DBP = diastolic blood pressure; FDG = 18F-fluorodeoxyglucose; LA = left atrium; LAVI = left atrial volume index; LVEF = left ventricular ejection fraction; OR = odds ratio; RA = right atrium; SBP = systolic blood pressure.
Table 4. The clinical factors associated with an increased atrial FDG uptake and the interaction across age groups.
| Clinical factors related to atrial FDG visual uptake ≥ mild (grade 1) | Adjusted OR (95% CI) in each age group | p-for-interaction between age groups | ||||
|---|---|---|---|---|---|---|
| Young AF | p value | Old AF | p value | |||
| Biatrial (RA or LA) | ||||||
| AF type (persistent AF) | 6.948 (0.350–138.116) | 0.204 | 6.096 (0.409–90.914) | 0.187 | 0.836 | |
| Current drinking | 7.519 (0.655–86.316) | 0.105 | 3.608 (0.404–32.253) | 0.251 | 0.714 | |
| RA | ||||||
| AF type (persistent AF) | 11.751 (0.591–233.852) | 0.106 | 19.627 (1.028–374.722) | 0.048 | 0.819 | |
| Current drinking | 6.438 (0.539–76.897) | 0.141 | 1.197 (0.111–12.850) | 0.882 | 0.379 | |
AF = atrial fibrillation; CI = confidence interval; FDG = 18F-fluorodeoxyglucose; LA = left atrium; OR = odds ratio; RA = right atrium.
Increased right atrial uptake in persistent atrial fibrillation across age group
The right-to-left atrial ratio of TBR according to AF type is presented in Figure 2. The FDG uptake of RA wall had a trend that is greater than LA wall in persistent AF with median right-to-left TBR index of 1.08. The degree of increased RA wall uptake than LA wall was higher in persistent AF than paroxysmal AF: RA wall TBR/LA wall TBR was 0.94 (0.79–1.04) and 1.08 (0.96–1.25) in paroxysmal and persistent AF, respectively (p<0.001). The right-to-left appendage FDG uptake ratio was also higher in persistent AF (0.96 [0.82–1.13]) than paroxysmal AF (0.86 [0.78–0.96]), p=0.018 (Figure 2, Supplementary Table 4). The higher ratio of right-to-left atrial TBR in persistent AF than paroxysmal AF was consistent across age group: p-for-interaction of RA TBR/LA wall TBR was 0.084 and RAA TBR/LAA TBR was 0.614 (Supplementary Table 5).
Figure 2. The right-to-left atrial ratio of 18F-fluorodeoxyglucose positron emission tomography target-to-background ratio.
AF = atrial fibrillation; LA = left atrium; LAA = left atrial appendage; RA = right atrium; RAA = right atrial appendage; TBR = target-to-background ratio.
DISCUSSION
The principal findings are as follows: (1) the young AF patients had a higher prevalence of unhealthy lifestyle behaviors, including current smoking and drinking, than old AF patients; (2) there was no significant age-related difference in the atrial FDG uptake; (3) across the overall study population, persistent AF and current drinking were the 2 primary clinical factors independently associated with an increased atrial FDG uptake in AF, with the pattern predominantly driven by increased uptake in the RA; (4) interestingly, persistent AF was associated with 10.2-fold higher likelihood of an increased RA metabolic activity, a relationship that remained robust regardless of age group; and (5) in quantitative analysis, a ratio of RA metabolic activity compared to LA—either wall or appendage—was significantly higher in persistent AF showing consistent trends across age groups.
We observed a consistent pattern of atrial metabolic activity across the age groups and provides clinical factors related to an increased atrial metabolic activity in patients with AF. An incidental yet intriguing finding was the presence of increased right atrial metabolic activity in patients with persistent AF, independent of age. This raises the hypothesis that the RA may play a contributory role in AF chronicity.
In contrast to older patients, pathophysiology of young AF is less well understood and may involve a broader range of contributing mechanisms.24),25) Interestingly, despite significant differences in clinical profiles—including a higher prevalence of lifestyle-related risk factors in younger patients—we observed no significant age-related differences in atrial FDG uptake. This suggests that metabolic remodeling in AF may occur through potentially age-independent pathways. Nonetheless, definitive conclusions regarding age-related differences in atrial metabolic activity warrant further investigation in larger, more diverse cohorts. Indeed, in our study cohort with a mean age of 59.3 years, 63.7% of individuals demonstrated increased atrial FDG uptake (≥ mild). This proportion is relatively higher than those reported in previous studies, where atrial FDG uptake was observed in 37.5% (median age 70.2 years),20) 50.5% (approximate median age 68 years),9) and 54.0% (median age 72.7 years)8) of AF patients. Given that our cohort comprised relatively younger individuals with AF compared to these prior studies, and despite the absence of age-dependent differences in atrial uptake within our own dataset, the inter-study comparison may suggest a trend toward higher atrial metabolic activity in younger AF patients.
Notably, the consistent pattern of increased right atrial metabolic activity in persistent AF, regardless of age, raises the hypothesis that the RA may play a central role or be a chamber of altered metabolism in AF persistence. This is consistent with previous studies reporting a higher prevalence of FDG uptake in the RA in patients with persistent AF compared to those with paroxysmal AF. A retrospective analysis of 48 AF patients demonstrated that atrial uptake was predominantly observed in the RA in persistent AF cases.26) Similarly, a prospective study of 100 AF patients showed a nearly 3-fold higher rate of increased atrial FDG uptake in persistent AF, with a predominance in the RA.9) Another prospective case-control study involving 70 AF patients further confirmed significantly greater RA uptake in persistent compared to paroxysmal AF.25) Notably, these findings highlight increased metabolic activity in the RA—rather than the LA, traditionally considered the primary substrate of AF—in advanced stages of the disease. Building upon these prior observations, our study further demonstrates that increased RA FDG uptake is consistently observed regardless of age, suggesting a shared metabolic alteration underlying AF progression that transcends age-related pathological differences. The mechanism underlying increased FDG uptake in the RA remains largely hypothetical. However, findings from several studies suggest explanations that may account for this observation. Analysis of RAA specimens has shown that patients with persistent AF, but not paroxysmal, exhibit significantly higher mRNA expression levels of pro-brain natriuretic peptide (proBNP) in the RA.27) Notably, proBNP mRNA expression in the RA has been shown to correlate directly with mean RA pressure in humans.28) The finding is translated into that persistent AF have an increased RA pressure resulting in an augmented proBNP expression in RA. It is plausible that prolonged AF—i.e., persistent AF—leads to fibrotic changes in the LA,29) resulting in elevated RA pressure and subsequently enhanced metabolic activity in the RA. Given that atrial pressure overload or increased metabolic activity is associated with increased FDG uptake,30),31) increased RA FDG uptake in persistent AF might be the consequence of presumed increase in workload on the right side of the heart as an adaptive or compensatory response. Nonetheless, it remains to be studied whether increased RA activity contributes to the maintenance or progression of AF, or rather represents a concomitant consequence of AF persistence.
In addition to persistent AF, several other clinical factors have been previously associated with increased atrial FDG uptake in patients with AF, including female gender, elevated epicardial adipose tissue activity, and higher BNP levels.9),26) In our study, we additionally identified current alcohol consumption as a factor associated with increased atrial FDG uptake. Alcohol consumption is known to contribute to systolic hypertension, cardiac inflammation, and atrial enlargement with adverse atrial remodeling, all of which are linked to altered atrial metabolism and, consequently, increased FDG uptake.32),33) This finding aligns with the current understanding that both acute and chronic alcohol intake can elevate the risk of AF. Notably, we demonstrated a direct association between chronic alcohol exposure and increased atrial metabolic activity, supporting previous findings that acute alcohol intake triggers AF,34) alcohol is a significant risk factor in AF development,35) and alcohol abstinence can reduce AF burden over time.36) Although we did not observe a significant age-related difference in atrial metabolic activity a few observations warrant attention. Taken together—(1) alcohol consumption is linked to increased atrial FDG uptake, which is related to AF and its persistence, and (2) young AF patients show a higher prevalence of current drinking—these findings raise the possibility that younger patients with AF may represent a subgroup with a distinct pathophysiological background, potentially driven by unhealthy lifestyle factors and altered atrial metabolism.
Atrial FDG uptake may reflect a variety of pathological processes, including pressure overload, inflammation, or myocardial ischemia.9),37) Overall, it is considered to represent atrial metabolism and has emerged as a promising noninvasive tool to evaluate the atrial substrate, particularly under well-controlled imaging protocols. Although FDG uptake is a surrogate marker and may not exclusively distinguish underlying mechanisms, thus requiring histopathological validation and advanced multimodality imaging, it has appreciable role as a representative marker of atrial metabolic alteration. Indeed, recent FDG PET studies in patients with AF have demonstrated that lower atrial FDG uptake correlates with atrial fibrosis, as indicated by low-voltage areas on electroanatomical mapping, while increased atrial stress and glucose uptake can be reversed following sinus rhythm restoration by catheter ablation.4),12) Furthermore, a meta-analysis of 6 studies concluded that atrial FDG uptake is strongly associated with AF, suggesting the presence of altered metabolism or inflammation in this condition.38) Our study has a significance in its attempt to compare atrial metabolic differences between young and old AF patients and in demonstrating the age-transcending increase in RA FDG uptake observed in persistent AF.
We have several limitations. First, the sample size was modest from a single-center cohort, limiting the power to detect subtle age-related differences in AF and to adjust for potential confounders. Second, although certain diagnoses were excluded, there may still be underlying confounding factors that could influence atrial FDG uptake. Third, our analysis was primarily focused on atrial metabolic alterations evaluated by FDG PET. Thus, future studies incorporating genetic data as well as biomarkers of inflammation or atrial overload are warranted to elucidate potential molecular mechanisms underlying atrial metabolic remodeling in AF. Despite the limitations noted above, our prospective case-control study uniquely included a substantial proportion of young AF patients (mean age 47.0 years), a demographic that has been largely underrepresented in previous studies, thereby allowing for more comparative observations across different age groups.
In this prospective cohort of 80 young and old AF patients undergoing FDG PET imaging, atrial FDG uptake patterns did not differ by age in patients with AF. Meanwhile, an increased FDG uptake in persistent AF—predominantly RA—was consistently observed regardless of age, suggesting a common metabolic pathway underlying AF progression transcending age-related pathological differences. In addition to persistent AF, current drinking was an independent clinical factor associated with an increased atrial FDG uptake in the overall cohort, raising the hypothesis that young-onset AF may be partly driven by unhealthy lifestyle-related atrial metabolic alterations, given their higher prevalence of alcohol consumption.
Footnotes
Funding: This research was supported by a grant from the Korean Cardiac Research Foundation (202402-01), the Seoul National University Hospital Research Fund (3020210230), and the Korean Heart Rhythm Society, Grant/Award Number (KHRS2024-7).
Conflict of Interest: Hyo-Jeong Ahn, Kwanghoon Kim, Chan Soon Park, Seil Oh: None.
Jin Chul Paeng: Speaking fees from Pfizer.
So-Ryoung Lee: Speaking fees from Bayer, BMS/Pfizer, Biosense Webster, Daiichi-Sankyo, Sanofi-Aventis, Daewoong Pharmaceutical Co., Samjinpharm, Seers Technology, Biotronik, Boston Scientific and Medtronic. Consultant for Biosense Webster. No fees are received personally and no fees are related to this work.
Eue-Keun Choi: Research grants or speaking fees from Abbott, Bayer, BMS/Pfizer, Biosense Webster, Chong Kun Dang, Daewoong Pharmaceutical Co., Daiichi-Sankyo, DeepQure, Dreamtech Co., Ltd., Jeil Pharmaceutical Co. Ltd, Medtronic, Samjinpharm, Seers Technology, and Skylabs.
Data Sharing Statement: All data generated or analyzed during this study are included in this published article and its Supplemental information files. The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
- Conceptualization: Ahn HJ, Park CS, Oh S.
- Data curation: Ahn HJ, Paeng JC.
- Formal analysis: Ahn HJ, Paeng JC, Kim K.
- Funding acquisition: Ahn HJ, Oh S.
- Investigation: Ahn HJ, Oh S.
- Methodology: Ahn HJ, Paeng JC.
- Project administration: Oh S.
- Resources: Ahn HJ, Paeng JC, Oh S.
- Software: Paeng JC.
- Supervision: Oh S.
- Validation: Ahn HJ.
- Visualization: Ahn HJ.
- Writing - original draft: Ahn HJ, Paeng JC.
- Writing - review & editing: Ahn HJ, Paeng JC, Lee SR, Choi EK, Oh S.
SUPPLEMENTARY MATERIALS
Baseline characteristics of the study population according to the type of AF (paroxysmal vs. persistent) and atrial FDG uptake (none vs. ≥ mild)
Intra- and inter-observer variability of atrial FDG uptake measurement
The association between persistent AF and increased right atrium FDG uptake (≥ mild) in age subgroups
The right-to-left atrial ratio of FDG TBR
The right-to-left atrial ratio of FDG TBR according to age and type of AF
References
- 1.Kornej J, Börschel CS, Benjamin EJ, Schnabel RB. Epidemiology of atrial fibrillation in the 21st century: novel methods and new insights. Circ Res. 2020;127:4–20. doi: 10.1161/CIRCRESAHA.120.316340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Dong XJ, Wang BB, Hou FF, et al. Global burden of atrial fibrillation/atrial flutter and its attributable risk factors from 1990 to 2019. Europace. 2023;25:793–803. doi: 10.1093/europace/euac237. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Vermond RA, Geelhoed B, Verweij N, et al. Incidence of atrial fibrillation and relationship with cardiovascular events, heart failure, and mortality: a community-based study from the Netherlands. J Am Coll Cardiol. 2015;66:1000–1007. doi: 10.1016/j.jacc.2015.06.1314. [DOI] [PubMed] [Google Scholar]
- 4.Marchandise S, Roelants V, Raoult T, et al. Left atrial glucose metabolism evaluation by 18F-FDG-PET in persistent atrial fibrillation and in sinus rhythm. JACC Basic Transl Sci. 2024;9:459–471. doi: 10.1016/j.jacbts.2023.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Ozcan C, Battaglia E, Young R, Suzuki G. LKB1 knockout mouse develops spontaneous atrial fibrillation and provides mechanistic insights into human disease process. J Am Heart Assoc. 2015;4:e001733. doi: 10.1161/JAHA.114.001733. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Ghezelbash S, Molina CE, Dobrev D. Altered atrial metabolism: an underappreciated contributor to the initiation and progression of atrial fibrillation. J Am Heart Assoc. 2015;4:e001808. doi: 10.1161/JAHA.115.001808. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Chiang DY, Zhang M, Voigt N, et al. Identification of microRNA-mRNA dysregulations in paroxysmal atrial fibrillation. Int J Cardiol. 2015;184:190–197. doi: 10.1016/j.ijcard.2015.01.075. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Watanabe E, Miyagawa M, Uetani T, et al. Positron emission tomography/computed tomography detection of increased 18F-fluorodeoxyglucose uptake in the cardiac atria of patients with atrial fibrillation. Int J Cardiol. 2019;283:171–177. doi: 10.1016/j.ijcard.2018.10.106. [DOI] [PubMed] [Google Scholar]
- 9.Xie B, Chen BX, Nanna M, et al. 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in atrial fibrillation: a pilot prospective study. Eur Heart J Cardiovasc Imaging. 2021;23:102–112. doi: 10.1093/ehjci/jeab088. [DOI] [PubMed] [Google Scholar]
- 10.Taegtmeyer H. Tracing cardiac metabolism in vivo: one substrate at a time. J Nucl Med. 2010;51(Suppl 1):80S–87S. doi: 10.2967/jnumed.109.068205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hesse M, Marchandise S, Gerber B, Roelants V. Cardiac atrial metabolism quantitative assessment with analog and digital time of flight-PET/computed tomography. Nucl Med Commun. 2023;44:646–652. doi: 10.1097/MNM.0000000000001694. [DOI] [PubMed] [Google Scholar]
- 12.Raoult T, Gerber BL, Garnir Q, et al. Left atrial remodeling identification and catheter ablation outcomes with 18F-fluorodeoxyglucose positron emission tomography in persistent atrial fibrillation. J Am Heart Assoc. 2025;14:e041491. doi: 10.1161/JAHA.124.041491. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Yoneda ZT, Anderson KC, Quintana JA, et al. Early-onset atrial fibrillation and the prevalence of rare variants in cardiomyopathy and arrhythmia genes. JAMA Cardiol. 2021;6:1371–1379. doi: 10.1001/jamacardio.2021.3370. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Olesen MS, Andreasen L, Jabbari J, et al. Very early-onset lone atrial fibrillation patients have a high prevalence of rare variants in genes previously associated with atrial fibrillation. Heart Rhythm. 2014;11:246–251. doi: 10.1016/j.hrthm.2013.10.034. [DOI] [PubMed] [Google Scholar]
- 15.Choi SH, Weng LC, Roselli C, et al. Association between titin loss-of-function variants and early-onset atrial fibrillation. JAMA. 2018;320:2354–2364. doi: 10.1001/jama.2018.18179. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Lee JY, Kim TH, Yang PS, et al. Korean atrial fibrillation network genome-wide association study for early-onset atrial fibrillation identifies novel susceptibility loci. Eur Heart J. 2017;38:2586–2594. doi: 10.1093/eurheartj/ehx213. [DOI] [PubMed] [Google Scholar]
- 17.De With RR, Marcos EG, Van Gelder IC, Rienstra M. Atrial fibrillation progression and outcome in patients with young-onset atrial fibrillation. Europace. 2018;20:1750–1757. doi: 10.1093/europace/euy028. [DOI] [PubMed] [Google Scholar]
- 18.Marcos EG, De With RR, Mulder BA, Van Gelder IC, Rienstra M. Young-onset atrial fibrillation: Sex differences in clinical profile, progression rate and cardiovascular outcome. Int J Cardiol Heart Vasc. 2019;25:100429. doi: 10.1016/j.ijcha.2019.100429. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Alzahrani Z, Ornelas-Loredo A, Darbar SD, et al. Association between family history and early-onset atrial fibrillation across racial and ethnic groups. JAMA Netw Open. 2018;1:e182497. doi: 10.1001/jamanetworkopen.2018.2497. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Sinigaglia M, Mahida B, Piekarski E, et al. FDG atrial uptake is associated with an increased prevalence of stroke in patients with atrial fibrillation. Eur J Nucl Med Mol Imaging. 2019;46:1268–1275. doi: 10.1007/s00259-019-4274-6. [DOI] [PubMed] [Google Scholar]
- 21.Mathieu C, Mikaïl N, Benali K, et al. Characterization of 18F-fluorodeoxyglucose uptake pattern in noninfected prosthetic heart valves. Circ Cardiovasc Imaging. 2017;10:e005585. doi: 10.1161/CIRCIMAGING.116.005585. [DOI] [PubMed] [Google Scholar]
- 22.McEvoy JW, McCarthy CP, Bruno RM, et al. 2024 ESC guidelines for the management of elevated blood pressure and hypertension. Eur Heart J. 2024;45:3912–4018. doi: 10.1093/eurheartj/ehae178. [DOI] [PubMed] [Google Scholar]
- 23.Mitter SS, Shah SJ, Thomas JD. A test in context: E/A and E/e′ to assess diastolic dysfunction and LV filling pressure. J Am Coll Cardiol. 2017;69:1451–1464. doi: 10.1016/j.jacc.2016.12.037. [DOI] [PubMed] [Google Scholar]
- 24.Wutzler A, von Ulmenstein S, Attanasio P, et al. Where there’s smoke, there’s fire? Significance of atrial fibrillation in young patients. Clin Cardiol. 2016;39:229–233. doi: 10.1002/clc.22516. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Wan P, Wang B, Yu W, et al. Right atrial wall inflammation detected by 18F-FDG PET/CT may be significantly associated with persistent atrial fibrillation: a prospective case-control study. BMC Cardiovasc Disord. 2023;23:587. doi: 10.1186/s12872-023-03592-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Xie B, Chen BX, Wu JY, Liu X, Yang MF. Factors relevant to atrial 18F-fluorodeoxyglucose uptake in atrial fibrillation. J Nucl Cardiol. 2020;27:1501–1512. doi: 10.1007/s12350-018-1387-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Tuinenburg AE, Brundel BJ, Van Gelder IC, et al. Gene expression of the natriuretic peptide system in atrial tissue of patients with paroxysmal and persistent atrial fibrillation. J Cardiovasc Electrophysiol. 1999;10:827–835. doi: 10.1111/j.1540-8167.1999.tb00263.x. [DOI] [PubMed] [Google Scholar]
- 28.Doyama K, Fukumoto M, Takemura G, et al. Expression and distribution of brain natriuretic peptide in human right atria. J Am Coll Cardiol. 1998;32:1832–1838. doi: 10.1016/s0735-1097(98)00494-x. [DOI] [PubMed] [Google Scholar]
- 29.Goette A, Corradi D, Dobrev D, et al. Atrial cardiomyopathy revisited-evolution of a concept: a clinical consensus statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asian Pacific Heart Rhythm Society (APHRS), and the Latin American Heart Rhythm Society (LAHRS) Europace. 2024;26:euae204. doi: 10.1093/europace/euae204. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hagan G, Southwood M, Treacy C, et al. (18)FDG PET imaging can quantify increased cellular metabolism in pulmonary arterial hypertension: a proof-of-principle study. Pulm Circ. 2011;1:448–455. doi: 10.4103/2045-8932.93543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Xi XY, Zhang F, Wang J, et al. Functional significance of post-myocardial infarction inflammation evaluated by 18F-fluorodeoxyglucose imaging in swine model. J Nucl Cardiol. 2020;27:519–531. doi: 10.1007/s12350-019-01952-0. [DOI] [PubMed] [Google Scholar]
- 32.Husain K, Ansari RA, Ferder L. Alcohol-induced hypertension: mechanism and prevention. World J Cardiol. 2014;6:245–252. doi: 10.4330/wjc.v6.i5.245. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Voskoboinik A, Wong G, Lee G, et al. Moderate alcohol consumption is associated with atrial electrical and structural changes: insights from high-density left atrial electroanatomic mapping. Heart Rhythm. 2019;16:251–259. doi: 10.1016/j.hrthm.2018.10.041. [DOI] [PubMed] [Google Scholar]
- 34.Marcus GM, Modrow MF, Schmid CH, et al. Individualized studies of triggers of paroxysmal atrial fibrillation: the I-STOP-AFib randomized clinical trial. JAMA Cardiol. 2022;7:167–174. doi: 10.1001/jamacardio.2021.5010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kodama S, Saito K, Tanaka S, et al. Alcohol consumption and risk of atrial fibrillation: a meta-analysis. J Am Coll Cardiol. 2011;57:427–436. doi: 10.1016/j.jacc.2010.08.641. [DOI] [PubMed] [Google Scholar]
- 36.Voskoboinik A, Kalman JM, De Silva A, et al. Alcohol abstinence in drinkers with atrial fibrillation. N Engl J Med. 2020;382:20–28. doi: 10.1056/NEJMoa1817591. [DOI] [PubMed] [Google Scholar]
- 37.Lanctôt-Bédard J, Melhem HB, Harel F, Pelletier-Galarneau M. Atrial FDG uptake: etiologies, clinical significance, and implications. Curr Cardiol Rep. 2025;27:22. doi: 10.1007/s11886-024-02166-8. [DOI] [PubMed] [Google Scholar]
- 38.Kassar A, Chamoun N, Haykal R, et al. Atrial FDG uptake and atrial fibrillation: a systematic review and meta-analysis. Heart Rhythm O2. 2025;6:417–423. doi: 10.1016/j.hroo.2025.01.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Baseline characteristics of the study population according to the type of AF (paroxysmal vs. persistent) and atrial FDG uptake (none vs. ≥ mild)
Intra- and inter-observer variability of atrial FDG uptake measurement
The association between persistent AF and increased right atrium FDG uptake (≥ mild) in age subgroups
The right-to-left atrial ratio of FDG TBR
The right-to-left atrial ratio of FDG TBR according to age and type of AF