Search Results

Ask a specific question about this device

EnSite Fusion is indicated for registering the EnSite NavX navigation system to anatomic models, derived from CT scans, of the four individual cardiac chambers.

The EnSite System is a computerized storage and display system for use in electrophysiology studies of the human heart. The system consists of a console workstation, patient interface unit, and an electrophysiology mapping catheter or surface electrode kit.

Unlike currently available electrode recording catheters, the EnSite Array does not require direct contact with the endocardium for the detection of intracardiac electrograms. The EnSite System is a system that facilitates mapping and treatment of arrhythmias. When used with the EnSite catheter, the system is useful for treating patients with complex, non-sustained, or poorly tolerated arrhythmias that are difficult, if not impossible, to map with current mapping techniques. By visualizing the global activation pattern seen on the color-coded isopotential maps in the EnSite System, in conjunction with the reconstructed electrograms, the electrophysiologist can identify the arrhythmia source and can navigate to the defined area for therapy. When used with NavX patches, the system is useful in treating patients with simpler arrhythmias by providing non-fluoroscopic navigation and visualization of conventional EP catheters

Here's an analysis of the provided text regarding the acceptance criteria and study information for the EnSite Fusion Dynamic Registration Tool.

Based on the provided 510(k) summary, there is no explicit mention of acceptance criteria or a dedicated study designed to prove the device meets specific performance criteria in the way one might expect for a new diagnostic or AI-driven device. This 510(k) is for a modification/update to an existing system, and the filing primarily focuses on demonstrating substantial equivalence to a predicate device.

Key takeaway: The submission states that "The changes made to the EnSite System underwent a battery of bench and user tests. Device validation testing was conducted in accordance with in-house procedures." This implies internal testing was performed, but no details of these tests, their acceptance criteria, or their results are provided in the public summary. The conclusion explicitly states: "An evaluation of the device changes indicates that the device is as safe and effective as the previously marketed device to which it is being compared and does not raise any new issues of safety and effectiveness." This points to a substantial equivalence argument rather than a performance claim against predefined criteria.

Therefore, many of the requested sections below cannot be fully populated as the information is not present in the provided document.

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size (Test Set): Not specified in the provided document.
• Data Provenance: Not specified in the provided document. The statement "bench and user tests" suggests a mix, but no details are given. It's unclear if the "user tests" involved patient data, simulated data, or phantoms.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications

• Number of Experts: Not specified in the provided document.
• Qualifications of Experts: Not specified in the provided document.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified in the provided document.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No, an MRMC comparative effectiveness study is not mentioned or described in the provided document.
• Effect Size of Human Readers with AI vs. without AI: Not applicable, as no MRMC study was described.

6. Standalone (Algorithm Only without Human-in-the-Loop Performance) Study

• Was a standalone study done? A standalone algorithm performance study is not explicitly mentioned or described in the provided document. The device is a "registration tool" used within a larger system, implying human interaction.

7. Type of Ground Truth Used

• Type of Ground Truth: Not specified in the provided document. Given the device's function (registering a navigation system to CT-derived anatomic models), potential ground truths could involve geometric accuracy measurements (e.g., against physical phantoms or established anatomical landmarks on imaging). However, this is speculative as the document doesn't detail it.

8. Sample Size for the Training Set

• Sample Size (Training Set): Not specified in the provided document. It's unclear if machine learning was used in the traditional sense that requires a separate "training set" for the "EnSite Fusion Dynamic Registration Tool"; the document describes it as a "tool" for registration, which might be based on algorithmic rules rather than deep learning models.

9. How the Ground Truth for the Training Set Was Established

• How Ground Truth Was Established: Not specified in the provided document. As mentioned above, it's unclear if an explicit "training set" with ground truth, as understood in machine learning, was used.

Ask a specific question about this device