
==== Front
Clinics (Sao Paulo)
Clinics (Sao Paulo)
Clinics
1807-5932
1980-5322
Hospital das Clinicas da Faculdade de Medicina da Universidade de Sao Paulo

S1807-5932(24)00164-9
10.1016/j.clinsp.2024.100487
100487
Original Articles
Clinical value of artificial intelligence 3D echocardiography in evaluating left atrial volume and pulmonary vein structure in patients with atrial fibrillation
Yang Xiaomin a1
He Shujun b1
Pang Yang c
Rong Kun kittenRongkun@hotmail.com
d⁎
a Department of Cardiovascular Medicine, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai City, China
b Department of Ultrasound, Ezhou Central Hospital, Ezhou City, Hubei Province, China
c Department of Cardiovascular Medicine, Shanghai Changzheng Hospital (The Second Affiliated Hospital of Naval Medical University), Shanghai City, China
d Department of Ultrasound Diagnosis, Qingdao Special Servicemen Recuperation Center of PLA Navy, Qingdao City, Shandong Province, China
⁎ Corresponding author. kittenRongkun@hotmail.com
1 Equal contributions to this study.

14 9 2024
Jan-Dec 2024
14 9 2024
79 1004879 4 2024
30 6 2024
11 8 2024
© 2024 HCFMUSP. Published by Elsevier España, S.L.U.
2024
HCFMUSP
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Highlights

• The ADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAPEF, LSPV CSA, LIPV CSA, RSPV CSA, RIPV CSA of AF patients were significantly higher.

• There was a significant positive correlation between left atrial diameter and pulmonary vein structure.

• There was a significant positive correlation between left atrial volume and pulmonary vein structure.

• There was a negative correlation between left atrial active ejection fraction and pulmonary vein structure.

• LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAPEF, LSPV CSA, LIPV CSA, RSPV CSA, RIPV CSA have diagnostic value for AF patients.

Objective

To explore the clinical value of 3D Echocardiography (3DE) in evaluating the changes of left atrial volume and pulmonary vein structure in patients with Atrial Fibrillation (AF).

Methods

Clinical data were collected from 54 AF patients. Left Atrial Anteroposterior Diameter (LADap), Left Atrial left and right Diameter (LADml), and Left Atrial upper and lower Diameter (LADsi) were measured; the maximum Left Atrial Volume (LAVmax), minimum Left Atrial Volume (LAVmin), left atrial presystolic volume (LAVpre), and Cross-Sectional Area (CSA) of each pulmonary vein were analyzed. Passive Ejection Fraction (LAPEF) was calculated. The differences in left atrial volume and pulmonary vein structure between patients with AF and healthy people were compared, and the correlation between the indexes was analyzed. The diagnostic value of the above indicators for AF patients was analyzed.

Results

LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAPEF, LSPV CSA, LIPV CSA, RSPV CSA, and RIPV CSA of AF patients were significantly higher. There was a significant positive correlation between left atrial diameter and pulmonary vein structure. There was a significant positive correlation between left atrial volume and pulmonary vein structure. There was a negative correlation between LAPEF and pulmonary vein structure. LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAPEF, LSPV CSA, LIPV CSA, RSPV CSA, and RIPV CSA had a diagnostic value for AF patients.

Conclusion

3DE is applicable for evaluating left atrial volume and pulmonary vein structure in patients with AF.

Keywords

Atrial Fibrillation
Left atrial volume
Pulmonary vein structure
Three dimensional echocardiography
Clinical value
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pmcIntroduction

Atrioventricular Arrhythmia (AF) is one of the most common types of arrhythmias in clinical practice. AF is primarily characterized by absolute ventricular arrhythmia and variations in heart sound intensity.1 According to statistics, there are about 33 million AF patients worldwide.2,3 In China, about 10 million people suffer from AF, and the incidence of AF is about 0.77 %.4,5 AF can be categorized as paroxysmal, persistent, and permanent6 and is associated with common cardiovascular and cerebrovascular diseases such as heart failure, stroke, and pulmonary embolism, and the risk of the disease increases significantly with age, resulting in a relatively heavy social and economic burden.7,8 It has been confirmed that ectopic pacing points in the Pulmonary Vein (PV) are a major trigger for AF, which further leads to remodeling of the left atrium and PVs. Therefore it is important to quickly and accurately assess the structure and function of the left atrium and PV.9,10

Two-Dimensional Echocardiography (ECG) is currently the main method used in clinics to evaluate AF patients' functional status. Due to advanced age, lung gas interference, and patient body size, it is often difficult to acquire clear two-dimensional ultrasound images, impacting the accuracy of the structural and functional assessment of the LA and PV.11 In contrast, Three-Dimensional ECG (3DE) can well display the endocardial boundary, improve the clarity of ultrasound images in patients with AF, and more accurately evaluate cardiac function.12 Early 3DE is based on manual scanning or mechanical sensors to collect images, so this method is cumbersome and time-consuming, and cannot be applied to daily clinical work.

Artificial Intelligence (AI) is a technology that attempts to automate tasks completed by humans. Its research progress in image processing stems from the vigorous development of its convolutional neural network.13. In recent years, AI has been continuously applied to medical fields, including static image analysis such as X-Ray, Computed Tomography (CT), and Cardiac Magnetic Resonance imaging (CMR). Moreover, AI technology is also applied to dynamic image analysis.14,15 A variety of 3DE software packages have been developed to assist image analysis with AI techniques to assess the structure and function of the heart and veins.16, 17, 18 In line with this, this study was to explore the clinical value of AI 3DE in evaluating the changes in left atrial volume and PV structure in patients with AF.

Materials and methods

General information

54 AF patients hospitalized in Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine from October 2020 to October 2022 were selected. Inclusion criteria: (1) Patients meeting the diagnostic criteria of AF management guidelines issued by the American College of Cardiology (ACC), American Heart Association (AHA), the Heart Rhythm Society (HRS), and Society of Thoracic Surgeons (STS); (2) Patients diagnosed as AF by ECG or dynamic ECG; (3) Age > 18-years-old; (4) Patients with normal mentality who can cooperate with the investigation and analysis. Exclusion criteria: (1) Congenital heart disease; (2) Heart valve disease; (3) Coronary atherosclerotic heart disease; (4) Previous cardiac surgery history; (5) AF caused by hyperthyroidism or mental factors; (6) Other diseases unsuitable for 3DE. 26 healthy people who came to the Xinhua Hospital Affiliated To Shanghai Jiao Tong University School of Medicine for physical examination at the same time were selected. Clinical data of all subjects were collected, including age, sex, Body Mass Index (BMI), Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), history of smoking, and complications such as hypertension, diabetes, and coronary heart disease. The study was approved by the Xinhua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine ethics committee (n° 201903S10). All patients signed the consent form. This study follows the STROBE statement.

Detection of two-dimensional 3DE

SIEMEMS ACUSON SC2000 EPIQ 7C color Doppler ultrasound diagnostic instrument, equipped with S5-1 two-dimensional probe and 4Z1c 3D probe, with a frequency of 1‒5 MHz, was used for analysis with Syngo Via Q-LAB quantitative analysis software. ECGs were routinely connected to subjects lying on their left side and breathing calmly. The Left Atrial Anteroposterior Diameter (LADap), Left Atrial Left and Right Diameter (LADml), and Left Atrial Upper and Lower Diameter (LADsi) were measured with S5-1 two-dimensional probe. With the real-time 3D ultrasound full-volume mode, the X5-1 3D probe was used to collect images of three consecutive cardiac cycles from the apical four-chamber view. The images were imported into the Q-LAB workstation and analyzed by the 3DQA mode. The maximum Left Atrial Volume (LAVmax), minimum Left Atrial Volume (LAVmin), and Left Atrial Presystolic Volume (LAVpre) were analyzed. Left Atrial Appendage Ejection Fraction (LAAEF) was calculated as (LAVmax LAVmin)/LAVpre. Left Atrial Passive Ejection Fraction (LAPEF) was measured as (LAVmax LAVmin)/LAVmin. The position and changes of each PV were confirmed according to the coronal, sagittal, and axial 3D images. The maximum Cross-Sectional Area (CSA) of each PV in the sagittal plane perpendicular to the blood flow direction was analyzed, including the CSA of the Left Superior PV (LSPV CSA), the CSA of the Left Inferior PV (LIPV CSA), the CSA of the Right Superior PV (RSPV CSA), and the CSA of the Right Inferior PV (RIPV CSA).

Statistical analysis

The measurement data were expressed as mean ± standard deviation. Comparisons between the two groups should be made using the t-test if the measurements conform to a normal distribution or the Wilcoxon rank sum test if they do not conform to a normal distribution. The counting data were expressed in cases or percentages, and the Chi-Square test or Fisher test was used; p < 0.05 indicates a statistical difference.

Results

Comparison of general data

Of the 54 AF patients, 31 were male (57.41 %) and 23 were female (42.59 %); The average age was (60.91 ± 11.38) years old; BMI was (23.41 ± 1.17) kg/m2, systolic blood pressure was (129.54 ± 9.97) mmHg, and diastolic blood pressure was (71.74 ± 5.24) mmHg; 32 cases (59.26 %) had a history of smoking, 10 cases (18.52 %) had a history of hypertension, 5 cases (44.44 %) had a history of diabetes, and 27 cases (50.00 %) had a history of coronary heart disease. In all 26 healthy subjects, 14 males (53.85 %) and 12 females (46.15 %) were included; The average age was (60.38 ± 11.59) years old; BMI was (23.52 ± 0.90) kg/m2, systolic blood pressure was (129.85 ± 8.40) mmHg, and diastolic blood pressure was (71.77 ± 5.73) mmHg. There were 10 cases (38.46 %) with smoking history, 8 cases (19.23 %) with hypertension history, 11 cases (42.31 %) with diabetes history, and 8 cases (30.77 %) with coronary heart disease history. There was no statistical difference in general data between the two groups (p > 0.05) Table 1.Table 1 Comparison of general data of subjects.

Table 1:Item	AF group (n = 54)	NC group (n = 26)	p-value	
Male [n (%)]	31/57.41 %	14/53.85 %	0.7636	
Age (years)	60.91 ± 11.38	60.38 ± 11.59	0.8488	
BMI (kg/m2)	23.41 ± 1.17	23.52 ± 0.90	0.6788	
SBP (mmHg)	129.54 ± 9.97	129.85 ± 8.40	0.8919	
DBP (mmHg)	71.74 ± 5.24	71.77 ± 5.73	0.9824	
Smoking history [n (%)]	32/59.26 %	10/38.46 %	0.0810	
Hypertension history [n (%)]	10/18.52 %	5/19.23 %	0.9391	
Diabetes history [n (%)]	24/44.44 %	11/42.31 %	0.8568	
History of coronary heart disease [n (%)]	27/50.00 %	8/30.77 %	0.1044	

Left atrial volume comparison

In order to study the left atrial function of AF patients, the authors measured the left atrial volume of all subjects by two-dimensional and 3DE. Two-dimensional ECG showed that in the AF group, LADap was (38.31 ± 2.58) mm, LADml was (39.34 ± 2.72) mm, and LADsi was (55.46 ± 2.33) mm. In the NC group, LADap was (33.28 ± 1.59) mm, LADml was (35.83 ± 1.92) mm, and LADsi was (51.50 ± 3.23) mm. These results suggest that LADap, LADsi, and LADml of AF patients are significantly higher than those of healthy people (p < 0.0001) (Fig. 1). 3DE showed that in AF group, LAVmax was (41.36 ± 3.13) mL/m2, LAVmin was (21.44 ± 2.14) mL/m2, and LAVpre was (25.24 ± 2.23) mL/m2. In the NC group, LAVmax was (34.49 ± 1.89) mL/m2, LAVmin was (16.20 ± 1.90) mL/m2, and LAVpre was (21.72 ± 2.18) mL/m2. LAAEF and LAPEF were calculated. In the AF group, LAAEF was (0.80 ± 0.17) % and LAPEF was (0.95±0.25) %; LAAEF and LAPEF in the NC group were (0.85 ± 0.13) % and (1.15 ± 0.26) %, respectively. These results suggest that LAVmax, LAVmin, and LAVpre of AF patients are significantly higher than those of healthy people (p < 0.0001) (Fig. 2), and LAPEF is lower than that of healthy people (p < 0.001) (Fig. 3).Fig. 1 Left atrial diameter. (A‒C) Results of LADap (A), LADml (B), and LADsi (C). **** p < 0.0001.

Fig 1:

Fig. 2 Pulmonary vein structure. (A‒D) Results of LSPV CSA (A), LIPV CSA (B), RSPV CSA (C), and RIPV CSA (D). ****p < 0.0001.

Fig 2:

Fig. 3 Left atrial volume. (A‒D) Results of LAVmax (A), LAVmin, (B) LAVpre (C), LAAEF (D), and LAPEF (E). *** p < 0.001, **** p < 0.0001.

Fig 3:

Comparison of PV structure

The authors detected the structure of PVs in all subjects by 3DE. The results showed that in the AF group, LSPV CSA was (261.44 ± 19.53) mm2, LIPV CSA was (177.15 ± 11.53) mm2, RSPV CSA was (304.87 ± 18.39) mm2, and RIPV CSA was (213.46 ± 22.89) mm2. In the NC group, LSPV CSA was (229.63 ± 23.94) mm2, LIPV CSA was (156.60 ± 14.73) mm2, RSPV CSA was (255.74 ± 18.62) mm2, and RIPV CSA was (191.64 ± 13.34) mm2. These results suggest that LSPV CSA, LIPV CSA, RSPV CSA, and RIPV CSA in AF patients are significantly higher than those in healthy people (p < 0.0001) (Fig. 2).

Correlation analysis of left atrial volume and PV structure

PCA analysis showed that the samples of AF patients and healthy people were separated among PC1 dimension groups (Fig. 4A). At the same time, PLS-DA discriminant analysis based on indicators showed that AF patients and healthy people tended to gather in the sample group and tended to be dispersed between groups (Fig. 4B). Cluster analysis heat map shows that AF patients and healthy people were obviously separated, suggesting that left atrial volume related indicators (LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAAEF, LAPEF) and PV structure related indicators (LSPV CSA, LIPV CSA, RSPV CSA, RIPV CSA) can distinguish AF patients and healthy people (Fig. 4C). Further correlation analysis was carried out, showing that the related indexes of left atrial diameter and PV structure were significantly positively correlated (p < 0.01, p < 0.001), and the related indexes of left atrial volume and PV structure were significantly positively correlated (p < 0.05, p < 0.01, p < 0.001), and there was a negative correlation between LAAEF and the relevant indicators of PV structure (p < 0.05) (Fig. 4D).Fig. 4 Expression pattern of indexes related to left atrial volume and pulmonary vein structure in subjects. (A) PCA analysis; (B) PLS-DA analysis; (C) Cluster thermogram analysis; (D) Correlation analysis. *p < 0.05, **p < 0.01, ***p < 0.001.

Fig 4:

Diagnostic value of left atrial volume in evaluating AF

The diagnostic value of left atrial volume was evaluated by ROC. The AUC of LADap, LADml, and LADsi was 0.980 (95 % CI 0.9575‒1.000; p < 0.0001), 0.847 (95 % CI 0.7608‒0.9336; p < 0.0001), and 0.833 (95 % CI 0.7274‒0.9385; p < 0.0001), respectively (Fig. 5A). The AUC of LAVmax, LAVmin, LAVpre, LAAEF, LAPEF was 0.981 (95 % CI 0.9569‒1.000; p < 0.0001), 0.966 (95 % CI 0.9301‒1.000; p < 0.0001), 0.868 (95 % CI 0.7883‒0.9474; p < 0.0001), 0.615 (95 % CI 0.4905‒0.7389), and 0.713 (95 % CI 0.5989‒0.8263; p < 0.01), respectively (Fig. 5B). These results suggest that LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, and LAPEF have a diagnostic value for AF patients.Fig. 5 Diagnostic value of left atrial volume index. (A) Diagnostic value of indexes related to left atrial diameter; (B) Diagnostic value of left atrial volume related indexes.

Fig 5:

Diagnostic value of PV structure evaluation on AF

The diagnostic value of PV structure was evaluated by ROC. The results showed that the AUC of LSPV CSA, LIPV CSA, RSPV CSA, and RIPV CSA was 0.850 (95 % CI 0.7614‒0.9380; p < 0.0001), 0.871 (95 % CI 0.7871‒0.9551; p < 0.0001), 0.977 (95 % CI 0.9468‒1.000; p < 0.0001), and 0.807 (95 % CI 0.7087‒0.9053; p < 0.0001), respectively (Fig. 6), indicating that LSPV CSA, LIPV CSA, RSPV CSA, and RIPV CSA have a diagnostic value for AF patients.Fig. 6 The diagnostic value of PV structural indicators in patients with AF.

Fig 6:

Discussion

AF is a common arrhythmia in clinical practice.19 On the one hand, AF increases the afterload on the left atrium, causes mechanical and electrical remodeling of the left atrium, and ultimately enlarges the diameter of the left atrium and decreases its function.20 After AF is converted and maintained in sinus rhythm, myocardial fibrosis is improved, and atrial remodeling is reversed, which is conducive to inhibiting remodeling and improving cardiac function.21,22 This is because the effect of AF on cardiac function is related to its reduction of left atrial filling to the left ventricle and normal stroke volume.23 On the other hand, the adverse prognosis of patients with AF is related to thromboembolism events caused by thrombosis shedding.24 The traditional diagnostic methods of AF mainly include cardiac examination and electrocardiogram. The 12 lead ECG is the gold standard for diagnosing AF according to the RR interval and P wave.25,26 The sharp increase in the number of AF patients makes it sometimes difficult for doctors to diagnose a large number of ECGs in time. Paroxysmal AF may also lead to missed diagnosis due to failure to record the onset of AF in an ordinary 12-lead or 24 h dynamic ECG. Implantable ECG event recorders can extend the monitoring time to 3 years, but their high price also brings a burden to clinical work.27 In the absence of timely diagnosis, AF patients will suffer severe thromboembolism events. The need for a non-invasive, cheap, and simple method of monitoring AF is urgent, both for doctors and patients.

3D ultrasound technology integrates a matrix probe, a high-channel data processing system, and a 3D spatial positioning system. Research shows that 3DE has been initially applied to assess the structure and function of the left atrium in patients with AF.28,29 According to the three different stages of the normal cardiac cycle, the left atrial function can be divided into storage function, ductal function and auxiliary pump function. Storage function refers to how well the left atrium fills with blood returned by the PV during systole, a function that relates primarily to compliance of the left atrium. In early diastole, the ductal function reflects how well the left atrium delivers blood to the left ventricle, and it is affected by both left atrium compliance and left ventricle diastolic function. The auxiliary pump function reflects the ability of the left atrium to actively pump blood to the left ventricle in the late diastole and is related to the left atrial systolic force and the left atrial pre and post-load. The indexes related to the Left Atrium Volume (LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre, LAAEF, LAPEF) can well reflect the left atrium function.30, 31, 32 A study involving 47 patients with AF and 25 healthy volunteers showed that LAVmax and LAVmin in AF patients increased, while LATEF decreased. Six months after ablation, LAVmax and LAVmin decreased significantly, and LATEF increased significantly.33 The study also found that there was no significant change in all parameters 3 days after the operation, so it was speculated that after ablation, the left atrium may be stunned for a short period of time, and gradually recover after six months.33 Another study involving 62 AF patients who successfully received ablation showed that LAVmax and LAVpre decreased significantly, LAVmin did not change significantly, LAAEF and LATEF increased significantly, and LAPEF did not change significantly 3 months after operation.34 This study found that compared with healthy people, the left atrial volume of AF patients increased and left atrial remodeling existed. At the same time, LADml, LADsi, LAVmax, LAVmin, LAVpre and LAPEF were potential clinical indicators to predict AF.

A large number of previous studies have confirmed that most of the abnormal trigger foci of pulmonary venous origin in atrial fibrillation are located in the upper segment of the PVs.35,36 There are four PVs in the human body, two on the left and two on the left, which are respectively the left upper PV, the left lower PV, the right upper PV, and the right lower PV. The left upper PV and the left lower PV converge into a trunk and flow into the left atrium, or three right PVs from three lobes flow into the left atrium respectively. The study shows that the variation rate of PVs in AF patients is between 20 %‒40 %.37,38 Patients with atrial fibrillation have the most variable pulmonary venous coaptation, with PV orifice diameters being largest in systole and smallest in diastole. Preliminary results showed that 3DE can dynamically display the shape and displacement of each PV and the relationship of the PVs to the left atrium in most patients in a multidirectional and multifaceted manner, as well as measure each PV. Heart rate had no significant impact on the imaging quality.39,40 This study found that the structural indicators of PVs in patients with AF were significantly higher than those in healthy people, and LSPV CSA, LIPV CSA, RSPV CSA and RIPV CSA were also potential indicators to predict AF.

In conclusion, the indexes of left atrial volume in patients with AF are different from those in healthy people, and the indexes of PV structure are also significantly higher than those in healthy people. The indexes related to left atrial volume (LADap, LADml, LADsi, LAVmax, LAVmin, LAVpre) are significantly positively correlated with the indexes related to PV structure, and LAPEF is negatively correlated with the indexes related to PV structure. At the same time, the relevant indexes of left atrial volume and PV structure are potential indexes to predict AF. AI-3DE technology is expected to become a clinical diagnostic tool to evaluate the changes in left atrial volume and PV structure in patients with AF.

Availability of data and materials

The data and materials used to support the findings of this study are available from the corresponding author.

Ethics statement

The study was approved by the Xinhua Hospital Affiliated to the Shanghai Jiao Tong University School of Medicine ethics committee (n° 201903S10), and performed in accordance with The Declaration of Helsinki. Written informed consent was obtained from all patients prior to the study start.

Authors’ contributions

Xiaomin Yang and Shujun He designed the research study. Yang Pang and Kun Rong performed the research. Shujun He and Yang Pang provided help and advice on the experiments. Xiaomin Yang and Kun Rong analyzed the data. Xiaomin Yang and Shujun He wrote the manuscript. Kun Rong reviewed and edited the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript.

Funding

Not applicable.

Declaration of competing interest

The authors declare no conflicts of interest.

Acknowledgments

Not applicable.
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References

1 Cho DH Kim YG Choi J Kim HD Kim MN Shim J Atrial cardiomyopathy with impaired functional reserve in patients with paroxysmal atrial fibrillation J Am Soc Echocardiogr 36 2 2023 180 188 36162771
2 Jensen T Thrane PG Olesen KKW Würtz M Mortensen MB Gyldenkerne C Antithrombotic treatment beyond 1 year after percutaneous coronary intervention in patients with atrial fibrillation Eur Heart J Cardiovasc Pharmacother 9 3 2023 208 219 36269306
3 Karamitanha F Ahmadi F Fallahabadi H. Difference between various countries in mortality and incidence rate of the atrial fibrillation based on human development index in worldwide: data from global burden of disease 2010-2019 Curr Probl Cardiol 48 1 2023 101438
4 Kim DY Han SG Jeong HG Lee KJ Kim BJ Han MK Covert brain infarction as a risk factor for stroke recurrence in patients with atrial fibrillation Stroke. 54 1 2023 87 95 36268719
5 Zhong X Jiao H Zhao D Teng J. Association between serum albumin levels and paroxysmal atrial fibrillation by gender in a Chinese population: a case-control study BMC Cardiovasc Disord 22 1 2022 387 36031606
6 Isogai T Agrawal A Saad AM Kuroda S Shekhar S Abushouk AI Periprocedural and short-term outcomes of percutaneous left atrial appendage closure according to type of atrial fibrillation J Am Heart Assoc 10 22 2021 e022124
7 Presta R Brunetti E Polidori MC Bo M. Impact of frailty models on the prescription of oral anticoagulants and on the incidence of stroke, bleeding, and mortality in older patients with atrial fibrillation: a systematic review Ageing Res Rev 82 2022 101761
8 Farwati M Amin M Saliba WI Nakagawa H Tarakji KG Diab M Impact of redo ablation for atrial fibrillation on patient-reported outcomes and quality of life J Cardiovasc Electrophysiol 34 1 2023 54 61 36259719
9 Demarchi A Auricchio A Boveda S Bourenane H Dafaye P Carabelli A Catheter ablation of atrial fibrillation in patients with partial anomalous pulmonary venous return JACC Clin Electrophysiol 8 10 2022 1317 1319 36266010
10 Gottlieb LA Coronel R Dekker LRC. Reduction in atrial and pulmonary vein stretch as a therapeutic target for prevention of atrial fibrillation Heart Rhythm 20 2 2023 291 298 36265692
11 Karlsson M Wallman M Platonov PG Ulimoen SR Sandberg F. ECG based assessment of circadian variation in AV-nodal conduction during AF-Influence of rate control drugs Front Physiol 13 2022 976526
12 Akerström F Drca N Jensen-Urstad M Braunschweig F. Feasibility of a novel algorithm for automated reconstruction of the left atrial anatomy based on intracardiac echocardiography Pacing Clin Electrophysiol 45 11 2022 1288 1294 36193687
13 Zhou F Yuan Z Liu X Yu K Li B Li X Evaluation of atrial anatomical remodeling in atrial fibrillation with machine-learned morphological features Int J Comput Assist Radiol Surg 18 4 2023 603 610 36272019
14 Larson C Peele B Li S Robinson S Totaro M Beccai L Highly stretchable electroluminescent skin for optical signaling and tactile sensing Science 351 6277 2016 1071 1074 26941316
15 Murthy VL Nallamothu BK. An AI-ECG algorithm for atrial fibrillation risk: steps towards clinical implementation Lancet 396 10246 2020 235
16 Ji M He L Gao L Lin Y Xie M Li Y. Assessment of left atrial structure and function by echocardiography in atrial fibrillation Diagnostics (Basel). 12 8 2022 1898 36010248
17 Xing YY Xue HY Ye YQ. Heart model (A.I.) three-dimensional echocardiographic evaluation of left ventricular function and parameter setting Int J Gen Med 14 2021 7971 7981 34795512
18 Li Y Liang L Guo D Yang Y Gong J Zhang X Right ventricular function predicts adverse clinical outcomes in patients with chronic thromboembolic pulmonary hypertension: a three-dimensional echocardiographic study Front Med (Lausanne) 8 2021 697396
19 Osorio-Jaramillo E Cox JL Klenk S Kaider A Angleitner P Werner P Dynamic electrophysiological mechanism in patients with long-standing persistent atrial fibrillation Front Cardiovasc Med 9 2022 953622
20 Stacy MR Lin BA Thorn SL Lobb DC Maxfield MW Novack C Regional heterogeneity in determinants of atrial matrix remodeling and association with atrial fibrillation vulnerability postmyocardial infarction Heart Rhythm 19 5 2022 847 855 35066183
21 Sandeep B Ding W Huang X Liu C Wu Q Su X Mechanism and prevention of atrial remodeling and their related genes in cardiovascular disorders Curr Probl Cardiol 48 1 2023 101414
22 Bertelsen L Diederichsen SZ Frederiksen KS Haugan KJ Brandes A Graff C Left Atrial remodeling and cerebrovascular disease assessed by magnetic resonance imaging in continuously monitored patients Cerebrovasc Dis 51 3 2022 403 412 34883489
23 Noirclerc N Huttin O de Chillou C Selton-Suty C Fillipetti L Sellal JM Cardiac remodeling and diastolic dysfunction in paroxysmal atrial fibrillation J Clin Med 10 17 2021
24 D'Alessandro E Winters J van Nieuwenhoven FA Schotten U Verheule S The complex relation between atrial cardiomyopathy and thrombogenesis Cells 11 19 2022 2963 36230924
25 Hsieh JC Shih H Xin LL Yang CC Han CL. 12-lead ECG signal processing and atrial fibrillation prediction in clinical practice Technol Health Care 31 2 2023 417 433 36093717
26 Jekova I Christov I Krasteva V. Atrioventricular synchronization for detection of atrial fibrillation and flutter in one to twelve ECG leads using a dense neural network classifier Sensors (Basel) 22 16 2022 6071 36015834
27 Arya A Silberbauer J Teichman SL Milner P Sulke N Camm AJ. A preliminary assessment of the effects of ATI-2042 in subjects with paroxysmal atrial fibrillation using implanted pacemaker methodology Europace 11 4 2009 458 464 19174378
28 Deng B Nie R Qiu Q Wei Y Liu Y Lv H 3D transesophageal echocardiography assists in evaluating the morphology, function, and presence of thrombi of left atrial appendage in patients with atrial fibrillation Ann Transl Med 9 10 2021 876 34164510
29 Zhang Q Wang JF Dong QQ Yan Q Luo XH Wu XY Evaluation of left atrial volume and function using single-beat real-time three-dimensional echocardiography in atrial fibrillation patients BMC Med Imaging 17 1 2017 44 28732493
30 Istratoaie S Vesa Ș C Cismaru G Pop D Roșu R Puiu M Value of left atrial appendage function measured by transesophageal echocardiography for prediction of atrial fibrillation recurrence after radiofrequency catheter ablation Diagnostics (Basel) 11 8 2021 1465 34441399
31 Wu VC Otani K Yang CH Chu PH Takeuchi M. Optimal number of heartbeats required for representing left chamber volumes and function in patients with rate-controlled atrial fibrillation J Am Soc Echocardiogr 32 4 2019 495 502 e3 30718021
32 Shin SH Jang JH Baek YS Kwon SW Park SD Woo SI Prognostic impact of left atrial minimal volume on clinical outcome in patients with non-obstructive hypertrophic cardiomyopathy Int Heart J 59 5 2018 991 995 30158386
33 Bajraktari G Bytyçi I Henein MY. Left atrial structure and function predictors of recurrent fibrillation after catheter ablation: a systematic review and meta-analysis Clin Physiol Funct Imaging 40 1 2020 1 13 31556215
34 Antolini M Brustio A Morello M Bongiovanni F Fornengo C Gallo C Left atrial function after radiofrequency catheter ablation of atrial fibrillation-can pre-ablation function predict contractile improvement during follow-up? Circ J 79 12 2015 2576 2583 26447119
35 von Olshausen G Paul-Nordin A Tapanainen J Jensen-Urstad M Bastani H Saluveer O Electrical cardioversion for early recurrences post pulmonary vein isolation J Interv Card Electrophysiol 66 3 2023 577 584 36085243
36 Nie Z Chen S Lin J Lin J Dai S Zhang C Inferior vena cava as a trigger for paroxysmal atrial fibrillation: incidence, characteristics, and implications JACC Clin Electrophysiol 8 8 2022 983 993 35981803
37 Cheruiyot I Munguti J Olabu B Gichangi P. A meta-analysis of the relationship between anatomical variations of pulmonary veins and atrial fibrillation Acta Cardiol 75 1 2020 1 9 30736723
38 Ferrari R Bertini M Blomstrom-Lundqvist C Dobrev D Kirchhof P Pappone C An update on atrial fibrillation in 2014: from pathophysiology to treatment Int J Cardiol 203 2016 22 29 26490502
39 Ortiz-Leon XA Posada-Martinez EL Bregasi A Chen W Crandall I Pereira J Changes in left atrial appendage orifice following percutaneous left atrial appendage closure using three-dimensional echocardiography Int J Cardiovasc Imaging 38 6 2022 1361 1369 35064846
40 Delgado V Vidal B Sitges M Tamborero D Mont L Berruezo A Fate of left atrial function as determined by real-time three-dimensional echocardiography study after radiofrequency catheter ablation for the treatment of atrial fibrillation Am J Cardiol 101 9 2008 1285 1290 18435959
