Abstract
Aims
Left atrial catheter ablation is well established in patients with symptomatic atrial fibrillation (AF) but associated with risk of embolism to the brain. The present analysis aims to assess the impact of diffusion-weighted imaging (DWI) slice thickness on the rate of magnetic resonance imaging (MRI)–detected ischaemic brain lesions after ablation.
Methods and results
AXAFA-AFNET 5 trial (NCT02227550) participants underwent MRI using high-resolution (hr) DWI (slice thickness: 2.5–3 mm) and standard DWI (slice thickness: 5–6 mm) within 3–48 h after ablation. In 321 patients with analysable brain MRI (mean age 64 years, 33% female, median CHA2DS2-VASc 2), hrDWI detected at least one acute brain lesion in 84 (26.2%) patients and standard DWI in 60 (18.7%; P < 0.01) patients. High-resolution diffusion-weighted imaging detected more lesions compared to standard DWI (165 vs. 104; P < 0.01). The degree of agreement for lesion confirmation using hrDWI vs. standard DWI was substantial (κ = 0769). Comparing the proportion of DWI-detected lesions, lesion distribution, and total lesion volume per patient, there was no difference in the cohort of participants undergoing MRI at 1.5 T (n = 52) vs. 3 T (n = 269).
Conclusion
The pre-specified AXAFA-AFNET 5 sub-analysis revealed significantly increased rates of MRI-detected acute brain lesions using hrDWI instead of standard DWI in AF patients undergoing ablation. In comparison to DWI slice thickness, MRI field strength had a no significant impact in the trial. Comparing the varying rates of ablation-related MRI-detected brain lesions across previous studies has to consider these technical parameters. Future studies should use hrDWI, as feasibility was demonstrated in the multicentre AXAFA-AFNET 5 trial.
Keywords: Ablation, Diffusion-weighted imaging, Slice thickness, Field strengths, Brain MRI
Graphical Abstract
Graphical Abstract.
Design of the pre-defined brain magnetic resonance imaging (MRI) sub-study of the AXAFA-AFNET 5 trial also demonstrating the main results comparing MRI-detected acute ischaemic brain lesions using high-resolution vs. standard diffusion-weighted imaging (DWI).
What’s new?
While left atrial catheter ablation with symptomatic atrial fibrillation (AF) is associated with brain magnetic resonance imaging (MRI)–detected acute brain lesions in 10–40% of all patients, depending on procedure-related factors, the investigator-initiated, multicentre AXAFA-AFNET 5 trial is the first randomized trial including a pre-defined MRI sub-study using standard diffusion-weighted imaging (DWI; slice thickness 5–6 mm) in addition to high-resolution DWI (slice thickness 2.5–3 mm).
Compared to standard DWI, high-resolution DWI significantly increased the rate of MRI-detected acute brain lesions after ablation per patient as well as the total number of lesions, while MRI field strength had a no significant impact in the trial.
Technical details of brain MRI and especially DWI slice thickness must be considered by comparing reported rates of ablation-related brain lesions of previous studies.
Future interventional studies should use high-resolution DWI to detect acute brain lesions, as feasibility was demonstrated in the AXAFA-AFNET 5 trial.
Introduction
Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia worldwide. Left atrial catheter ablation is an increasingly employed treatment option in patients with symptomatic AF to improve AF-related symptoms and quality of life.1–3 Catheter ablation is a main component of rhythm control therapy, which has the potential to reduce cardiovascular endpoints in patients with AF diagnosed within 12 months.4 However, left atrial catheter ablation comes at the cost of a measurable peri-procedural risk of embolism to the brain causing ischaemic stroke in <0.5% of ablated patients.2,5 Brain magnetic resonance imaging (MRI) using diffusion-weighted imaging (DWI) identifies clinically unapparent, so-called ‘silent’ or ‘covert’ acute brain lesions in 10–40% of all patients undergoing left atrial catheter ablation, depending on procedure-related factors, e.g. ablation catheter used, procedure duration, ablation method, peri-procedural anticoagulation on top of heparinization, and number of cardioversions.6–11 In addition, MRI parameters like DWI slice thickness12 or MRI field strengths may affect the detection of ablation-related brain lesions, which may add to cognitive decline in the long term.13–15 As demonstrated in (non-ablated) patients with acute ischaemic stroke, high-resolution DWI (hrDWI) using a DWI slice thickness of ≤3 mm (instead of ≥5 mm in routine care) increased spatial resolution, increased the signal to noise, and decreased artefacts leading to improved lesion detection, predominately in the cortical grey matter.16,17
To clarify the impact of DWI slice thickness on the detection rate of acute ischaemic brain lesions after catheter ablation, patients enrolled to the investigator-initiated, multicentre, randomized Anticoagulation using the direct factor Xa inhibitor apixaban during Atrial Fibrillation catheter Ablation: Comparison to vitamin K antagonist therapy (AXAFA-AFNET 5) MRI sub-study underwent standard DWI (using a slice thickness of 5–6 mm) in addition to hrDWI (using a slice thickness of 2.5–3 mm).18 The investigator-initiated AXAFA-AFNET 5 trial demonstrated that peri-procedural anticoagulation using apixaban is a safe alternative to vitamin K antagonists for patients with symptomatic paroxysmal AF undergoing catheter ablation with regard to major bleeding, stroke, and cognitive function.5 The pre-defined analysis of available brain MRIs revealed no effect of random treatment on acute brain lesions or cognitive function at 3 months after ablation.5,6
Methods
Study design and study population
The prospective, parallel-group, 1:1 randomized, open AXAFA-AFNET 5 trial was conducted in 49 centres in eight European countries and the USA in accordance with the Declaration of Helsinki and the International Conference on Harmonization Good Clinical Practice Guidelines.18 The ethical review board of all study centres approved the study protocol. All patients provided written informed consent. It was not appropriate to involve patients or the public in the design, conduct, reporting, or dissemination plans of our research. Inclusion and exclusion criteria were published previously and are listed in the Supplementary material online, Table S1. The study enrolled 674 patients with symptomatic non-valvular AF scheduled for a first ablation.5 Patients randomized to apixaban received 5 mg twice daily pre-ablation, which was continued during the ablation procedure without interruption. Dose adjustment was done according to its label. Patients randomized to a vitamin K antagonist (VKA) were treated according to site-specific anticoagulation therapy routine aiming for a target international normalizied ratio of 2–3.18 The ablation procedure could be either radiofrequency ablation or cryoballoon ablation and was conducted according to local practice. The trial sponsor was executed by the Clinical Research Institute, Munich, Germany, and sponsored by the AFNET, Münster, Germany. Brain MRIs were conducted in 25 centres in eight European countries and the USA using 1.5 or 3 T within 3–48 h after the ablation procedure. Offering participation to all eligible patients at MRI sites, 333 study patients underwent brain MRI, of which 12 scans were unanalysable (see Supplementary material online, Figure S1 for details).5,6 Baseline characteristics, demographics, and ablation characteristics of the brain MRI sub-study population were similar compared to the total AXAFA study population, and the AXAFA study population at study sites is able to provide brain MRI.6
Brain magnetic resonance imaging
The AXAFA-AFNET 5 imaging charts (see Supplementary material online, Table S2 for details) included hrDWI with 2.5–3 mm slice thickness as well as standard DWI with 5–6 mm slice thickness in the same patient to assess acute ischaemic brain lesions and to compare the impact of hrDWI vs. standard DWI.18 The additional acquisition time for hrDWI varied between 30 and 90 s across study centres. Magnetic resonance images were centrally read for new brain lesions in a core lab (Neuroscios, St Radegund, Graz, Austria). Two expert neuroradiologists (J.B.F, T.E.) served as independent raters and were blinded to randomization, MRI field strengths, DWI slice thickness used, and clinical information. The number of brain lesions and the total volume of brain lesions were documented per patient. The presence and localization of acute brain lesions was documented according to brain-supplying arteries. The volume of every single brain lesion was assessed by using DWI (at b = 1000 s/mm2) for planimetric delineation.
Statistics
The analysis population included all randomized patients that underwent left atrial catheter ablation. Descriptive statistics for continuous variables were summarized as means [standard deviations (SDs)] or as medians (interquartile range (IQR): 25th, 75th percentiles) and counts (percentages) for categorical variables. Comparisons between continuous variables were performed with the two-sample t-test or Wilcoxon rank-sum test, depending on normality; comparisons between nominal variables were performed with Pearson’s χ2 test or Fisher’s exact test, as appropriate. All analyses were exploratory and tested two sided at the nominal significance level of 0.05. No adjustments were made for multiple testing. Cohen’s kappa was calculated to determine the agreement of lesion detection using hrDWI vs. standard DWI.19 All statistical analyses were performed using R version 3.4.3.
Results
Baseline characteristics and ablation characteristics of 321 AXAFA-AFNET 5 patients with analysable MRI are depicted in Table 1. Mean age was 64 years, 33% were female, and the median CHA2DS2-VASc score was 2 points at the time of enrolment. Most patients underwent pulmonary vein isolation only, mainly using radiofrequency. Of the 321 patients, 52 (16.2%) underwent brain MRI at 1.5 T and 269 (83.8%) at 3 T (Supplementary material online, Figure S1). Apart from the type of energy used, ablation characteristics, patients’ baseline characteristics, and randomization to apixaban or VKA did not differ between the 1.5 T cohort and the 3 T cohort (Table 1). All 321 patients underwent standard DWI (slice thickness of 5–6 mm) and hrDWI (slice thickness of 2.5–3 mm) immediately afterwards.
Table 1.
Baseline characteristics and demographics of AXAFA-AFNET 5 patients according to availability/field strengths of brain MRI
| Brain MRI 1.5/3 T n = 321 |
Brain MRI at 1.5 T n = 52 |
Brain MRI at 3 T n = 269 |
P-value | |
|---|---|---|---|---|
| Age (years), median (IQR) | 64 (58–70) | 65 (58–71) | 64 (58–69) | 0.436 |
| Female sex, n (%) | 105 (33) | 12 (23) | 93 (35) | 0.145 |
| BMI (kg/m2), median (IQR) | 28 (25–30) | 28 (25–29) | 28 (25–30) | 0.847 |
| Type of AF, n (%) | 0.990 | |||
| Paroxysmal | 197 (61) | 32 (62) | 165 (61) | |
| Persistent | 117 (36) | 19 (37) | 98 (36) | |
| Long-standing persistent | 7 (2) | 1 (2) | 6 (2) | |
| CHA2DS2-VASc score, median (IQR) | 2 (1–3) | 2 (2–3) | 2 (1–3) | 0.221 |
| Older than 75 years, n (%) | 26 (8) | 5 (10) | 21 (8) | 0.873 |
| Prior stroke or TIA, n (%) | 28 (9) | 7 (13) | 21 (8) | 0.292 |
| Hypertension, n (%) | 295 (92) | 50 (96) | 245 (91) | 0.342 |
| Diabetes mellitus, n (%) | 38 (12) | 7 (13) | 31 (12) | 0.872 |
| Symptomatic heart failure, n (%) | 56 (17) | 11 (21) | 45 (17) | 0.569 |
| Vascular disease, n (%) | 40 (12) | 10 (19) | 30 (11) | 0.166 |
| Carotid stenosis (>50%), n (%) | 1 (0) | 0 (0) | 1 (0) | 0.999 |
| Anticoagulation before randomization, n (%) | 41 (13) | 8 (15) | 33 (12) | 0.697 |
| Antiplatelets at randomization, n (%) | 15 (5) | 5 (10) | 10 (4) | 0.137 |
| Statin before randomization, n (%) | 111 (35) | 22 (42) | 89 (33) | 0.262 |
| Type of index catheter ablation, n (%) | 0.059 | |||
| Pulmonary vein isolation | 286 (89) | 47 (90) | 239 (89) | |
| Pulmonary vein isolation + other | 34 (11) | 4 (8) | 30 (11) | |
| Other | 1 (0) | 1 (2) | 0 (0) | |
| Type of ablation energy, n (%) | <0.001 | |||
| Radio frequency | 217 (68) | 50 (96) | 167 (62) | |
| Cryoenergy | 68 (21) | 2 (4) | 66 (825) | |
| Other | 36 (11) | 0 (0) | 36 (13) | |
| Anticoagulation after randomization, n (%) | 0.999 | |||
| VKA | 165 (50) | 26 (50) | 133 (49) | |
| Apixaban | 167 (50) | 26 (50) | 136 (51) | |
| Use of TEE prior to ablation, n (%) | 279 (87) | 42 (81) | 237 (88) | 0.226 |
| Randomization to ablation (days), median (IQR) | 35 (22–46) | 34 (22–44) | 35 (21–47) | 0.884 |
| ACT during ablation (s), median (IQR) | 325 (300–365) | 339 (304–365) | 320 (297–352) | 0.44 |
| Heparin dose during ablation (IU), median (IQR) | 12 000 (10 000–15 983) | 10 863 (10 000–15 188) | 12 000 (9600–16 000) | 0.783 |
| Cardioversion(s) during ablation, median (IQR) | 0 (0–1) | 0 (0–1) | 0 (0–1) | 0.813 |
ACT, activated clotting time; BMI, body mass index; TEE, transesophageal echocardiogram; TIA, transient ischemic attack; VKA, vitamin K antagonist.
Using standard DWI, 104 acute brain lesions were found in 60 (18.7%) patients, whereas hrDWI revealed 165 acute brain lesions in 84 (26.2%) patients (Figure 1 and Table 2). Compared to standard DWI, hrDWI detected a significantly higher number of lesions (P < 0.01) in a significantly higher number of patients with at least a single lesion (P < 0.01). Examples for hrDWI and standard DWI in single patients are depicted in Supplementary material online, Figure S2. The distribution of lesion volumes per patients differed, as hrDWI more frequently detected patients with a total lesion volume ≤50 mm3.
Figure 1.
Design of the pre-defined brain MRI sub-study of the AXAFA-AFNET 5 trial also demonstrating the main results comparing MRI-detected acute ischaemic brain lesions using hr vs. standard DWI. DWI, diffusion-weighted imaging; MRI, magnetic resonance imaging.
Table 2.
Brain lesions detected by hrDWI compared to standard DWI in 321 patients with analysable MRI
| hrDWI n = 321 |
DWI n = 321 |
P-value | |
|---|---|---|---|
| Total number of brain lesions detected | 165 | 104 | <0.01 |
| Volume of brain lesions detected per patient | <0.01 | ||
| Total volume <20 mm3 | 9 (3) | 2 (1) | |
| Volume 21–50 mm3 | 26 (8) | 13 (4) | |
| Volume 51–100 mm3 | 22 (7) | 19 (6) | |
| Volume >100 mm3 | 27 (8) | 26 (8) | |
| Patients with at least one detected lesion, n (%) | 84 (26) | 60 (19) | <0.01 |
| DWI-detected brain lesions and MRI field strengths, n | |||
| 1.5 Tesla (in 52 patients) | 26 | 11 | 0.006 |
| 3 Tesla (in 269 patients) | 139 | 93 | <0.01 |
In 52 patients undergoing 1.5 T MRI, standard DWI detected 11 acute brain lesions in 8 (15.3%) patients, and hrDWI detected 26 acute brain lesions in 16 (30.8%) patients (P = 0.006; Table 2; Supplementary material online, Figure S2). In 268 patients undergoing 3 T MRI, standard DWI detected 93 acute brain lesions in 52 (19.4%) patients, and hrDWI detected 139 acute brain lesions in 68 (28.6%) patients (P < 0.01; Table 3; Supplementary material online, Figure S2). The number of detected lesions per patient and total lesion volume according to standard DWI and hrDWI is shown in Table 3. There was no significant difference in the 1.5 T cohort vs. the 3 T cohort using standard DWI or hrDWI regarding the proportion of detected lesions per patient (see Supplementary material online, Figure S2) and total lesion volume. Furthermore, the distribution of affected vessel territories was similar in the 1.5 T cohort and the 3 T cohort.
Table 3.
Acute ischaemic brain lesions detected in 321 patients with analysable MRI according to field strength
| Brain MRI at 1.5 T n = 52 |
Brain MRI at 3 T n = 269 |
P-value | |
|---|---|---|---|
| Standard DWI | |||
| Detected lesions, n (%) | 8 (15) | 52 (19) | 0.636 |
| Number of lesion per patient, n (%) | 0.808 | ||
| 0 | 44 (85) | 217 (81) | |
| 1 | 6 (12) | 30 (11) | |
| 2 | 1 (2) | 14 (5) | |
| ≥3 | 1 (2) | 7 (3) | |
| Total lesion volume, n (%) | 0.774 | ||
| <20 mm3 | 0 (0) | 2 (1) | |
| ≥20 and <50 mm3 | 3 (6) | 10 (4) | |
| ≥50 and <100 mm3 | 2 (4) | 17 (6) | |
| ≥100 mm3 | 3 (6) | 23 (9) | |
| high-resolution DWI | |||
| Detected lesions, n (%) | 16 (31) | 68 (25) | 0.514 |
| Number of lesion per patient, n (%) | 0.718 | ||
| 0 | 36 (69) | 201 (75) | |
| 1 | 11 (21) | 35 (13) | |
| 2 | 3 (6) | 18 (7) | |
| ≥3 | 2 (4) | 15 (6) | |
| Total lesion volume, n (%) | 0.943 | ||
| <20 mm3 | 2 (4) | 7 (3) | |
| ≥20 and <50 mm3 | 5 (10) | 21 (8) | |
| ≥50 and <100 mm3 | 4 (8) | 18 (7) | |
| ≥100 mm3 | 5 (10) | 22 (8) | |
| Affected vessel territory, n (%) | |||
| Arteria cerebri media | 11 (21) | 51 (19) | 0.861 |
| Arteria cerebri anterior | 0 (0) | 8 (3) | 0.439 |
| Arteria cerebri posterior | 3 (6) | 17 (6) | 0.999 |
| Vertebral/basilar artery | 5 (10) | 15 (6) | 0.430 |
DWI, diffusion-weighted imaging.
The degree of agreement for lesion detection using hrDWI vs. standard DWI was substantial (κ = 0.769) in all 321 patients, as well as in 52 patients undergoing brain MRI at 1.5 T (κ = 0.695) and in 269 patients undergoing brain MRI at 3 T (κ = 0.808).
Discussion
To the best of our knowledge, this is the largest prospective brain MRI study comparing standard DWI to hrDWI in AF patients undergoing left atrial catheter ablation.5,6 Using a multicentre approach, we demonstrate that brain MRI using hrDWI significantly improves the detection of ablation-related acute brain lesions, if compared to standard DWI. In particular, hrDWI detected at least one acute brain lesion in a significantly higher proportion of study patients (26% vs. 19% using standard DWI) and a significantly higher number of lesions (n = 165 vs. n = 104 using standard DWI) throughout the brain. In addition, hrDWI in comparison to standard DWI more frequently detected a total lesion volume ≤50 mm3. A small single-centre study from China reported similar findings regarding lesion load in patients with ablation-related brain lesions by comparing DWI using 1 mm vs. 5 mm slice thickness at 3 T in 55 AF patients,12 despite the fact that a slice thickness of 1 mm is not established in clinical practice.
Of note, the significantly higher rate of hrDWI vs. standard DWI detected lesions in AXAFA-AFNET 5 was similar using 1.5 T MRI compared to 3 T MRI, which is another novel finding of our analysis. Our finding is in line with a previous meta-analysis in patients with transient global amnesia (TGA),20 demonstrating a low impact of field strengths, despite a higher contrast-to-noise ratio in high-field-strength MRI. Subsequently, one might argue that 1.5 and 3 T MRI has equivalent sensitivity for detecting ablation-related brain lesions, if hrDWI is performed.
Taken together, our findings help to explain the varying frequency of MRI-detected acute brain lesions post-ablation in previous cohorts using similar ablation catheters but different DWI parameters while most often using a DWI slice thickness of 5–6 mm.2,7–9,12
The pre-defined analysis of the AXAFA-AFNET 5 study has several strengths beside the rather large sample size and the well-standardized assessment.18 It has to be mentioned, in addition, that independent raters were blinded to clinical or MRI information. Despite the fact that many of the contributing MRI teams in this multicentre study do mainly or exclusively cardiac MRI exams in their daily practice, the technical quality of the study-related brain exams was excellent, and the degree of agreement for lesion detection using hrDWI vs. standard DWI was substantial. In conclusion, hrDWI is feasible in a phase II trial setup and should be regarded as standard for future trials, which may help to further optimize the safety of the ablation procedure by reducing the procedure-related embolic risk. Besides the use of specific protection devices and optimization of peri-procedural anticoagulation, the types of energy application in the left atrium are modifiable drivers of ablation-associated stroke risk.14,21
Despite the reported strength, the following limitations must be considered. Although this was a pre-specified analysis of AXAFA-AFNET 5 trial,18 the brain MRI sub-study was not specifically powered to detect differences of brain lesions with regard to DWI slice thickness or MRI field strength. About half of the total AXAFA-AFNET 5 cohort underwent brain MRI. However, the participation rate is rather high if compared to the brain MRI sub-study of the randomized ELIMINATE-AF trial, including 177 (28%) of 632 AF patients only.2 Conducting a single brain MRI within 3–48 h post-ablation and no MRI immediately before ablation, we cannot rule out acute brain lesions within days before the ablation procedure, as DWI lesions are present for up to 14 days.7 Moreover, study patients were not examined at 1.5 and 3 T, as this was not feasible in the vast majority of study sites. Despite the fact that neuroradiologists were also blinded to information on slice thickness, the number of available slices differed in hrDWI and standard DWI data sets. Finally, we were not able to assess the impact of other technical MRI parameters like number of active receiver channels in the head coil or vendor-specific sequence parameters.
Conclusions
Using hrDWI instead of standard DWI, this pre-specified analysis of the AXAFA-AFNET 5 trial revealed markedly increased rates of MRI-detected acute brain lesions in patients with symptomatic AF undergoing first-time catheter ablation. In comparison to DWI slice thickness, MRI field strength had no significant impact in the trial. Comparing the varying rates of ablation-related brain lesions across previous studies must consider the technical details revealed by the pre-specified analysis of the AXAFA-AFNET 5 trial. Future interventional studies focusing on reducing the risk of ablation-related embolization to the brain should use hrDWI to detect acute lesions, as feasibility of this approach was demonstrated in the multicentre AXAFA-AFNET 5 trial.
Supplementary Material
Contributor Information
Karl Georg Haeusler, Atrial Fibrillation NETwork association (AFNET), Mendelstr. 11, 48149 Münster, Germany; Department of Neurology, Universitätsklinikum Würzburg Josef-Schneider-Str. 11, 97080 Würzburg, Germany.
Felizitas A Eichner, Institute of Clinical Epidemiology and Biometry, University Würzburg, Würzburg, Germany.
Peter U Heuschmann, Institute of Clinical Epidemiology and Biometry, University Würzburg, Würzburg, Germany; Clinical Trial Center, University Hospital Würzburg, Würzburg, Germany; Institute of Medical Data Science, University Hospital Würzburg, Würzburg, Germany.
Jochen B Fiebach, Center for Stroke Research Berlin, Charité—Universitätsmedizin Berlin, Berlin, Germany.
Tobias Engelhorn, Department of Neuroradiology, University of Erlangen-Nuremberg, Erlangen, Germany.
David Callans, Hospital of the University of Pennsylvania, Philadelphia, USA.
Tom De Potter, Cardiovascular Center, OLV Hospital, Aalst, Belgium.
Philippe Debruyne, Hospital Imelda, Bonheiden, Belgium.
Daniel Scherr, Division of Cardiology, Medical University Graz, Austria.
Gerhard Hindricks, Deutsches Herzzentrum der Charité, Berlin, Germany.
Hussein R Al-Khalidi, Department of Biostatistics & Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
Lluis Mont, Hospital Clínic, Universitat de Barcelona, IDIBAPS, Barcelona, Spain.
Won Yong Kim, Department of Cardiology, Aarhus University Hospital, Aarhus, Denmark.
Jonathan P Piccini, Duke Clinical Research Institute (DCRI), Durham, NC, USA; Division of Cardiology Duke University Medical Center, Duke University, Durham NC, USA.
Ulrich Schotten, Atrial Fibrillation NETwork association (AFNET), Mendelstr. 11, 48149 Münster, Germany; Departments of Cardiology and Physiology, University Maastricht, Maastricht, The Netherlands.
Sakis Themistoclakis, Department of Cardiology, Ospedale dell’Angelo, Mestre-Venice, Italy.
Luigi Di Biase, Albert Einstein College of Medicine at Montefiore Hospital, New York, NY, USA; Texas Cardiac Arrhythmia Institute at St.David’s Medical Center, Austin, TX, USA.
Paulus Kirchhof, Atrial Fibrillation NETwork association (AFNET), Mendelstr. 11, 48149 Münster, Germany; University of Birmingham Institute of Cardiovascular Sciences, Birmingham, UK; Department of Cardiology, University Heart and Vascular Center UKE Hamburg, Hamburg, Germany; German Center for Cardiovascular Research, Partner site Hamburg/Kiel/Lübeck, Germany.
Supplementary material
Supplementary material is available at Europace online.
Funding
AXAFA-AFNET 5 was an investigator-initiated trial. The study was sponsored by the AFNET. AXAFA-AFNET 5 was partially funded by Pfizer and Bristol Myers Squibb (grant number: CV185-244) and from the German Centre for Cardiovascular Research (grant number: 81X2800110) supported by the Bundesministerium für Bildung und Forschung. Über Bundesministerium für Bildung und Forschung (via a grant to AFNET). This work received additional support from the European Union [grant agreement no. 633196 (CATCH ME)], BigData@Heart (grant agreement EU IMI 116074), British Heart Foundation (FS/13/43/30324), and Leducq Foundation. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and in the decision to publish the results.
Conflict of interest: K.G.H. reports speaker’s honoraria, consulting fees, lecture honoraria, and/or study grants from Abbott, Alexion, Amarin, AstraZeneca, Bayer Healthcare, Biotronik, Boehringer Ingelheim, Boston Scientific, Bristol-Myers Squibb, Daiichi Sankyo, Edwards Lifesciences, Medtronic, Novartis, Pfizer, Portola, Premier Research, Sanofi, SUN Pharma, and W.L. Gore and Associates. P.U.H. reports research grants from the German Ministry of Research and Education, German Research Foundation, European Union, Charité—Universitätsmedizin Berlin, German Parkinson Society, University Hospital Würzburg, Robert Koch Institute, German Heart Foundation, Federal Joint Committee (G-BA) within the Innovationfond, University Hospital Heidelberg (within RASUNOA-prime; supported by an unrestricted research grant to the University Hospital Heidelberg from Bayer, BMS, Boehringer-Ingelheim, Daiichi Sankyo), Charité—Universitätsmedizin Berlin (within Mondafis; supported by an unrestricted research grant to the Charité from Bayer), and University Göttingen (within FIND-AF randomized; supported by an unrestricted research grant to the University Göttingen from Boehringer-Ingelheim), outside the submitted work. J.B.F. reports consulting and advisory board fees from Abbvie, AC Immune, Artemida, BioClinica/Clario, Biogen, BMS, Brainomix, Cerevast, Daiichi Sankyo, EISAI, F. Hoffmann-La Roche AG, Guerbet, Ionis Pharmaceuticals, Julius Clinical, jung diagnostics, Eli Lilly, Merck, and Tau Rx, outside the submitted work. T.E. reports consulting fees from ab medica, BALT, Bayer, Medtronic, Microvention, Parexel, and Phenox. D.S. is a consultant of Boston Scientific and Zoll Medical and has received speaker honoraria/travel support from Abbott Medical, AstraZeneca, Bayer, Biosense Webster, Biotronik, BMS/Pfizer, Boston Scientific, Daiichi Sankyo, Farapulse, Medtronic, and Zoll Medical. L.M. reports honoraria as lecturer, consulter, and Advisory Board to Abbott Medical, Medtronic, and Boston Scientific. U.S. received consulting fees or honoraria from Università della Svizzera Italiana, Roche Diagnostics, EP Solutions Inc., Johnson & Johnson Medical Limited, and Bayer Healthcare. U.S. is a co-founder and shareholder of YourRhythmics BV, a spin-off company of the University Maastricht. L.D.B. is a consultant for Biosense Webster, Stereotaxis, and Rhythm Management and has received speaker honoraria/travel from Biosense Webster, St. Jude Medical (now Abbott), Boston Scientific, Medtronic, Biotronik, Atricure, Pfizer, and Bristol Meyers Squibb. P.K. receives research support for basic, translational, and clinical research projects from the European Union, British Heart Foundation, Leducq Foundation, Medical Research Council (UK), and German Centre for Cardiovascular Research, from several drug and device companies active in atrial fibrillation, and has received honoraria from several such companies in the past. P.K. is listed as an inventor on two patents held by the University of Birmingham (Atrial Fibrillation Therapy WO 2015140571, Markers for Atrial Fibrillation WO 2016012783). All other authors declare that there is no conflict of interest.
Data availability
The data will be shared upon reasonable request to the AXAFA-AFNET 5 trial sponsor (via axafa@af-net.eu).
References
- 1. Hindricks G, Potpara T, Dagres N, Arbelo E, Bax JJ, Blomström-Lundqvist C et al. 2020 ESC guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association of Cardio-Thoracic Surgery (EACTS). Eur Heart J 2021;42:373–498. [DOI] [PubMed] [Google Scholar]
- 2. Hohnloser SH, Camm J, Cappato R, Diener HC, Heidbüchel H, Mont L, et al. Uninterrupted edoxaban vs. vitamin K antagonists for ablation of atrial fibrillation: the ELIMINATE-AF trial. Eur Heart J 2019; 40: 3013–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Willems S, Meyer C, de Bono J, Brandes A, Eckardt L, Elvan A et al. Cabins, castles, and constant hearts: rhythm control therapy in patients with atrial fibrillation. Eur Heart J 2019;40:3793–99c. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Kirchhof P, Camm AJ, Goette A, Brandes A, Eckardt L, Elvan A et al. Early rhythm-control therapy in patients with atrial fibrillation. N Engl J Med 2020;383:1305–16. [DOI] [PubMed] [Google Scholar]
- 5. Kirchhof P, Haeusler KG, Blank B, De Bono J, Callans D, Elvan A et al. Apixaban in patients at risk of stroke undergoing atrial fibrillation ablation. Eur Heart J 2018;39:2942–55. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Haeusler KG, Eichner F, Heuschmann PU, Fiebach JB, Englhorn T, Blank B et al. MRI-detected brain lesions and cognitive function in atrial fibrillation patients undergoing left atrial catheter ablation in the randomized AXAFA-AFNET 5 trial. Circulation 2022;145:906–15. [DOI] [PubMed] [Google Scholar]
- 7. Haeusler KG, Kirchhof P, Endres M. Left atrial catheter ablation and ischemic stroke. Stroke 2012;43:265–70. [DOI] [PubMed] [Google Scholar]
- 8. Haeusler KG, Koch L, Herm J, Kopp UA, Heuschmann PU, Endres M et al. 3 Tesla MRI-detected brain lesions after pulmonary vein isolation for atrial fibrillation: results of the MACPAF study. J Cardiovasc Electrophysiol 2013;24:14–21. [DOI] [PubMed] [Google Scholar]
- 9. Zheng J, Wang M, Tang QF, Xue F, Li KL, Dang SP et al. Atrial fibrillation ablation using robotic magnetic navigation reduces the incidence of silent cerebral embolism. Front Cardiovasc Med 2021;8:777355. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Calvert P, Kollias G, Pürerfellner H, Narasimhan C, Osorio J, Lip GYH et al. Silent cerebral lesions following catheter ablation for atrial fibrillation: a state-of-the-art review. Europace 2023;25:euad151. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Nagao T, Suzuki H, Matsunaga S, Nishikawa Y, Harada K, Mamiya K et al. Impact of periprocedural anticoagulation therapy on the incidence of silent stroke after atrial fibrillation ablation in patients receiving direct oral anticoagulants: uninterrupted vs. interrupted by one dose strategy. Europace 2019;21:590–7. [DOI] [PubMed] [Google Scholar]
- 12. Yu Y, Wang X, Li X, Zhou X, Liao S, Yang W et al. Higher incidence of asymptomatic cerebral emboli after atrial fibrillation ablation found with high-resolution diffusion-weighted magnetic resonance imaging. Circ Arrhythm Electrophysiol 2020;13:e007548. [DOI] [PubMed] [Google Scholar]
- 13. Dietzel J, Haeusler KG, Endres M. Does atrial fibrillation cause cognitive decline and dementia? Europace 2018;20:408–19. [DOI] [PubMed] [Google Scholar]
- 14. Rivard L, Friberg L, Conen D, Healey JS, Berge T, Boriani G et al. Atrial fibrillation and dementia: a report from the AF-SCREEN international collaboration. Circulation 2022;145:392–409. [DOI] [PubMed] [Google Scholar]
- 15. Koh YH, Lew LZW, Franke KB, Elliott AD, Lau DH, Thiyagarajah A et al. Predictive role of atrial fibrillation in cognitive decline: a systematic review and meta-analysis of 2.8 million individuals. Europace 2022;24:1229–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Benameur K, Bykowski JL, Luby M, Warach S, Latour LL. Higher prevalence of cortical lesions observed in patients with acute stroke using high-resolution diffusion-weighted imaging. Am J Neuroradiol 2006;27:1987–9. [PMC free article] [PubMed] [Google Scholar]
- 17. Khalil AA, Hohenhaus M, Kunze C, Schmidt W, Brunecker P, Villringer K et al. Sensitivity of diffusion-weighted STEAM MRI and EPI-DWI to infratentorial ischemic stroke. PLoS One 2016;11:e0161416. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Di Biase L, Callans D, Haeusler KG, Hindricks G, Al-Khalidi H, Mont L et al. Rationale and design of AXAFA-AFNET 5: an investigator-initiated, randomized, open, blinded outcome assessment, multi-centre trial to comparing continuous apixaban to vitamin K antagonists in patients undergoing atrial fibrillation catheter ablation. Europace 2017;19:132–8. [DOI] [PubMed] [Google Scholar]
- 19. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159–174. [PubMed] [Google Scholar]
- 20. Lim SJ, Kim M, Suh CH, Kim SY, Shim WH, Kim SJ. Diagnostic yield of diffusion-weighted brain magnetic resonance imaging in patients with transient global amnesia: a systematic review and meta-analysis. Korean J Radiol 2021;22:1680–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Kino T, Kagimoto M, Yamada T, Ishii S, Asai M, Asano S et al. Optimal anticoagulant strategy for periprocedural management of atrial fibrillation ablation: a systematic review and network meta-analysis. J Clin Med 2022;11:1872. [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
Data Availability Statement
The data will be shared upon reasonable request to the AXAFA-AFNET 5 trial sponsor (via axafa@af-net.eu).