Background: Detailed visualization and precise measurements of aortic valve dimensions are critical for the success of transcatheter aortic valve implantation and for the prevention of complications. Currently, multislice computed tomography is the gold standard for assessment of the aortic annulus and surrounding structures to determine the prosthesis size. New technologies such as virtual reality (VR) not only enable 3‐dimensional (3D) visualization with the potential to improve understanding of anatomy and pathology but also allow measurements in 3D. This study aims to investigate the feasibility, accuracy, and reproducibility of VR for the visualization of the aortic valve, the surrounding structures, and its role in preprocedural sizing for transcatheter aortic valve implantation. Methods and Results: Based on the preprocedural multislice computed tomography data, 3mensio measurements and 3D visualizations and measurements using VR software were performed retrospectively on 60 consecutive patients who underwent transcatheter aortic valve implantation at our heart center. There were no significant differences but strong correlations between the VR measurements compared with those performed with the 3mensio software. Furthermore, excellent or good intra‐ and interobserver reliability could be demonstrated for all values. In a structured questionnaire, users reported that VR simplified anatomical understanding, improved 3D comprehension of adjacent structures, and was associated with very good self‐perceived depth perception. Conclusions: The use of VR for preprocedural transcatheter aortic valve implantation sizing is feasible and has precise and reproducible measurements. In addition, 3D visualization improves anatomical understanding and orientation. To evaluate the potential benefits of 3D visualization for planning further cardiovascular interventions, research in this field is needed.

Background: An accurate device sizing for percutaneous left atrial appendage closure (LAAC) can be challenging. Intraprocedural automated LAA evaluation by transoesophageal echocardiography (TEE) based on an artificial intelligence-assisted 3D model may facilitate sizing and prediction of C-arm angulation for device implantation in a one-stop-shop procedure. This study aimed to evaluate the feasibility and accuracy of automated echocardiographic LAA sizing based on a patient-specific 3D heart model prototype in real-time. Methods: A prospective monocentric study was conducted in 66 patients who underwent LAAC with the Amulet device. All major LAA morphologies were represented. Preprocedural multidetector computed tomography (MSCT) measurements and intraprocedural TEE and angiography measurements of the ostium, landing zone, and C-arm angulation were compared with the 3D heart model measurements. Results: The procedure achieved a 100% success rate. The measurements for the maximum diameter of the ostium in the 3D heart model were not significantly different from those obtained via angiography, TEE, and MSCT. Specifically, the maximum diameter of the landing zone did not differ significantly compared to TEE and angiographic measurements (20.90 ± 3.42 mm vs. 20.96 ± 4.81 mm, p = 0.563; compared to 21.20 ± 3.90 mm, p = 0.291). However, these measurements were significantly smaller than the average MSCT measurements (18.30 ± 2.68 mm vs. 21.03 ± 4.34 mm, p < 0.001). Additionally, the predicted implantation angles showed no significant differences between the 3D heart model and MSCT. Conclusions: The intraprocedural application of this prototype is both safe and feasible. The measurements obtained from the 3D heart model were consistent with those from TEE and angiography, although discrepancies were noted when compared to MSCT measurements. Notably, the predicted implantation angles demonstrated strong agreement with MSCT, further supporting the prototype’s efficacy in clinical settings.

Due to the complex and variable anatomy of the left atrial appendage, percutaneous left atrial appendage closure (LAAC) can be challenging. In this study, we investigated the impact of fusion imaging (FI) on the LAAC learning curve of two interventionalists. The first interventionalist (IC 1) was initially trained without FI and continued his training with FI. The second interventionalist (IC 2) performed all procedures with FI. We compared the first 36 procedures without FI of IC 1 (group 1) with his next 36 interventions with FI (group 2). Furthermore, group 1 was compared to 36 procedures of IC 2 who directly started his training with FI (group 3). Group 1 demonstrated that the learning curve without FI has a flat course with weak correlations for fluoroscopy time, contrast volume, and procedure time, but not for dose area product. Group 2 with FI showed improvement with a steep course and strong correlations for all four parameters. In group 3, we also saw a steep progression with strong correlations. Furthermore, the mean measurements of the parameters in the groups with FI decreased significantly as an indicator of procedural efficacy. We demonstrated that FI may improve the learning curve of experienced and non-experienced ICs.

(1) Background: Transesophageal echocardiography (TEE) is the gold standard for diagnosing patent foramen ovale (PFO) in cryptogenic ischemic stroke. However, false-positive diagnoses remain clinically relevant, exposing patients to unnecessary invasive procedures. (2) Methods: We retrospectively analyzed 346 patients with cryptogenic ischemic stroke who underwent TEE for PFO from 2012–2021. PFO was confirmed in 326 patients (94.2%), whereas 20 patients (5.8%, 95% CI 3.6–8.9%) were adjudicated as false positives during subsequent cardiac catheterization (intracardiac echocardiography, angiography, and inability to cross the interatrial septum). Univariable and multivariable logistic regression identified predictors of diagnostic accuracy. (3) Results: False-positive cases were associated with less frequent use of the mid-esophageal bicaval view (50% vs. 87%, p < 0.001) and absence of early bubble transit. Multivariable analysis confirmed the mid-esophageal bicaval view as an independent predictor of accurate diagnosis (OR 5.23, 95% CI 2.11–12.9, p < 0.001). (4) Conclusion: False-positive PFO diagnoses occur in ~6% of patients referred for closure. Three quality criteria—mid-esophageal aortic valve short axis, bicaval view, and bubble test with x-plane analysis—may improve diagnostic reliability. These hypothesis-generating findings require prospective validation and alignment with ASE/ESC guidelines to reduce unnecessary invasive procedures.

BACKGROUND: Accurate preprocedural planning is crucial for a successful transcatheter aortic valve implantation to ensure patient safety and valve longevity. Through 3-dimensional visualization, virtual reality (VR) offers the potential to enhance this process. The study investigated whether the inclusion of VR in preprocedural planning can improve the procedural preparation, impact intraprocedural parameters, and improve short-term patient outcomes. METHODS: This randomized, prospective, controlled study included 140 patients who underwent transcatheter aortic valve implantation at the University Hospital Duesseldorf between April and August 2024. In the control group, preprocedural planning was based on multislice computed tomography data using 3mensio software, while in the intervention group, it was supplemented with VR software. In addition, interventionalists assessed both tools via a structured questionnaire. RESULTS: The evaluation did not reveal any relevant differences in patient characteristics. VR was superior to 3mensio software with respect to the 3-dimensional understanding ( P <0.001). Similarly, depth perception, visualization of atherosclerotic plaques, and iliofemoral tortuosity were better in the VR group. Both methods were found to be useful and helpful in preparing for the procedure. There were no significant differences in procedural data between the 2 groups. However, the VR group had a lower rate of bleeding at the access site ( P <0.05). There was no significant difference in the length of hospital stay or postprocedural transthoracic echocardiography data evaluations. CONCLUSIONS: The data show that VR visualization can optimize preparation for the procedure by improving the 3-dimensional understanding of the aortic valve and adjacent structures. The detailed visualization of the access routes can lead to a reduction in periprocedural complications.

Due to the complex and variable anatomy of the left atrial appendage, percutaneous left atrial appendage closure (LAAC) can be challenging. In this study, we investigated the impact of fusion imaging (FI) on the LAAC learning curve of 2 interventionalists. The first interventionalist (IC 1) was initially trained without FI and continued his training with FI. The second interventionalist (IC 2) performed all procedures with FI. We compared the first 36 procedures without FI of IC 1 (group 1) with his next 36 interventions with FI (group 2). Furthermore, group 1 was compared to 36 procedures of IC 2 who directly started his training with FI (group 3). Group 1 demonstrated that the learning curve without FI has a flat course with weak correlations for fluoroscopy time, contrast volume, and procedure time, but not for dose area product. Group 2 with FI showed improvement with a steep course and strong correlations for all 4 parameters. In group 3 we also saw a steep progression with strong correlations. Furthermore, the mean measurements of the procedural parameters in the groups with FI decreased significantly as indicator for procedural efficacy. We demonstrated that FI may improve the learning curve of experienced and non-experienced ICs.