Volta AF-Xplorer

The Volta AF-Xplorer is an advanced cardiac mapping system that utilizes machine and deep learning algorithms to assist operators in the real-time identification and annotation of spatiotemporal dispersion in intra-cardiac atrial electrograms during atrial fibrillation or tachycardia. While it provides sophisticated analysis of 3D anatomical and electrical maps, its direct clinical significance for guiding catheter ablation therapies for these arrhythmias remains to be established through further clinical investigation.

The Volta AF-Xplorer is a medical device designed to assist clinicians in evaluating cardiac arrhythmias, specifically atrial fibrillation and atrial tachycardia. It employs machine learning and deep learning algorithms to analyze multipolar intra-cardiac atrial electrograms in real-time, identifying areas exhibiting spatiotemporal dispersion. The system integrates with existing electrophysiology catheters and data acquisition systems, including EP recording systems (via analog communication) and the EnSite X 3D mapping system (via bidirectional digital communication). It consists of a computing platform and software, presenting its analysis graphically on a display located outside the sterile field, allowing for either manual or automatic annotation of 3D anatomical and electrical maps of the human atria. The device processes intra-cardiac signals and, in digital mode, 3D electrode locations to output the presence or absence of electrogram dispersion, cycle length estimations, and tag regions of interest on 3D maps. Key functionalities include the real-time cueing of operators to dispersed electrograms and the generation of color-coded symbols to indicate these areas. While the Volta AF-Xplorer provides advanced mapping capabilities by highlighting electrograms with spatiotemporal dispersion, the document explicitly states that the clinical significance of using this information for guiding catheter ablation of atrial arrhythmias has not yet been established through clinical investigations. The AF-Xplorer builds upon previous iterations by combining specific pre-processing from VX1 and post-processing features from VX1+.

AI Regulatory Concerns

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Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

• Q1. What specific features or patterns in intra-cardiac atrial electrograms does the Volta AF-Xplorer's machine learning algorithm identify as 'spatiotemporal dispersion,' and how is this definition quantitatively validated?; Given that its clinical significance for catheter ablation is not established, what are the current primary research or investigational applications for identifying areas with spatiotemporal dispersion using the Volta AF-Xplorer?; How does the performance (e.g., sensitivity, specificity, processing speed) of the automatic annotation feature using bidirectional digital communication with the EnSite X system compare to manual annotation or analog system integration?; What is the typical learning curve for an electrophysiologist to effectively integrate the Volta AF-Xplorer's real-time feedback and annotations into their existing workflow for diagnosing atrial arrhythmias?; Are there any ongoing or planned clinical investigations designed to establish the clinical significance of targeting areas with spatiotemporal dispersion (identified by Volta AF-Xplorer) for improving outcomes in atrial fibrillation ablation procedures?