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The EnSite® Multi-electrode Diagnostic Catheter used with the EnSite 3000 Electrophysiology Workstation is intended to be used in the right atrium of patients with complex arrhythmias that may be difficult to identify using conventional mapping systems alone (i.e., linear mapping catheters).

The EnSite 3000 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. Unlike currently available electrode recording catheters, the EnSite Catheter does not require direct contact with the endocardium for the detection of intracardiac electrograms. The EnSite 3000 Electrophysiology Workstation connected to the EnSite Catheter utilizes proprietary software algorithms to reconstruct and display right atrial electrograms detected by the EnSite Catheter. This information can be presented as color-coded three-dimensional maps to provide global electrical activation patterns of the heart chamber. The EnSite 3000 System may also be used in conjunction with standard electrode mapping catheters, programmable cardiac stimulators, ECG leads, and other analog or digital inputs.

The EnSite 3000 System also incorporates a navigational tool to provide real-time feedback regarding the position of an auxiliary catheter for creation of a geometrical model of the heart chamber or for guiding therapy to a designated location.

This 510(k) notification describes a device modification, making it a "Special 510(k)". The core assertion is that the modified device is as safe and effective as its predicate. Therefore, the study presented focuses on demonstrating equivalence rather than establishing new performance criteria.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Study Details Proving Device Meets Acceptance Criteria

The document does not detail specific acceptance criteria in terms of numerical performance metrics (e.g., sensitivity, specificity, accuracy) for a standalone AI or a human-in-the-loop scenario. Instead, the acceptance criteria are implicitly met by demonstrating that the modified device performs comparably to the predicate device without introducing new risks.

The study described is focused on validating the changes made to the EnSite 3000 System.

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

• Sample Size for Test Set: The document states "a battery of bench and user tests." It does not specify the sample size for these tests.
• Data Provenance: The document does not specify the country of origin of the data or whether the data was retrospective or prospective. It only mentions "in-house procedures" for testing.

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

The document does not provide information about "experts" or the establishment of "ground truth" in the context of clinical performance evaluation. The testing appears to be focused on engineering validation (bench and user tests) to confirm the modified device's functionality and safety equivalent to the predicate.

4. Adjudication Method for the Test Set

The document does not mention any adjudication method for a test set. This type of methodology is usually relevant for studies involving human interpretation or clinical outcomes, which are not detailed here.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not reported. The study described is not a clinical effectiveness study involving human readers and AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The document describes "bench and user tests" for the system, not specifically a standalone algorithm performance test. The EnSite 3000 System itself is a computerized system with proprietary software algorithms, but the testing reported is for the system's operational equivalence to the predicate, not a standalone AI performance.

7. The Type of Ground Truth Used

The concept of "ground truth" as typically used in AI/diagnostic device validation (e.g., pathology, expert consensus, outcomes data) is not explicitly stated or described. The validation appears to be against established functional specifications of the predicate device and safety standards.

8. The Sample Size for the Training Set

The document does not provide any information about a "training set" or its sample size. This type of information is typically relevant for machine learning model development, and while the EnSite 3000 System uses "proprietary software algorithms," the submission focuses on device modification validation rather than algorithm development or training.

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

Since no training set is mentioned, there is no information on how its ground truth was established.

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