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The EnSite ™ X EP System is a suggested diagnostic tool in patients for whom electrophysiology studies have been indicated.
The EnSite ™ X EP System provides information about the electrical activity of the heart and displays catheter location during conventional electrophysiological (EP) procedures.
When used with the TactiSys™ Quartz Equipment, the EnSite™ X EP System Contact Force Module is intended to provide visualization of force information from compatible catheters.
The EnSite ™ X EP Surface Electrode Kit is indicated for use with the EnSite ™ X EP System in accordance with the EnSite™ X EP System indications for use.

The EnSite™ X EP System is a catheter navigation and mapping system. A catheter navigation and mapping system is capable of displaying the 3-dimensional (3-D) position of conventional and Sensor Enabled™ (SE) electrophysiology catheters, as well as displaying cardiac electrical activity as waveform traces and as three-dimensional (3D) isopotential and isochronal maps of the cardiac chamber.
The contoured surfaces of the 3D maps are based on the anatomy of the patient's own cardiac chamber. The system creates a model by collecting and labeling the anatomic locations within the chamber. A surface is created by moving a selected catheter to locations within a cardiac structure. As the catheter moves, points are collected at and between all electrodes on the catheter. A surface is wrapped around the outermost points.

Here's an analysis of the provided text regarding the acceptance criteria and study proving device performance.

Important Note: The provided document is an FDA 510(k) clearance letter and a 510(k) Summary. It does not contain detailed information about a comprehensive clinical study to establish performance, especially not in the depth typically seen for AI/ML device clearances (e.g., MRMC studies, specific performance metrics against ground truth for diagnostic accuracy). This document primarily focuses on demonstrating substantial equivalence to a predicate device, specifically for software updates to an existing system. Therefore, many of the requested details, particularly those related to a new AI/ML model's performance validation, are not present in this type of submission.

Based on the provided document, here's what can be inferred and what information is missing:

The device in question is the EnSite™ X EP System, and the 510(k) (K242016) is a "Special 510(k)" for software updates (Version 3.1) to an already cleared predicate device (EnSite™ X EP System, K231415). Special 510(k)s are typically used for changes that do not alter the fundamental technology or indications for use.

The "study" referenced in this context is primarily software verification and validation testing to ensure the updated software maintains the safety and effectiveness of the previously cleared predicate device. It's not a clinical performance study in the sense of evaluating a new diagnostic algorithm's accuracy against a clinical ground truth with human agreement.

1. Table of Acceptance Criteria & Reported Device Performance

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

• Sample Size: Not specified in terms of clinical cases or data points. The "test set" here refers more to the scope of software testing rather than a clinical dataset for diagnostic performance.
• Data Provenance: Not specified. Given it's a software update to an existing system, the "data" would likely be the system's internal functions, compatibility with hardware, and simulated/recorded electrophysiology data used for testing. It's not a retrospective or prospective clinical study on patient data in the typical sense of evaluating a new AI/ML diagnostic model.

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

• Number of Experts: Not specified. Given the nature of a software update, ground truth for software functionality would be established by software engineers, quality assurance personnel, and potentially subject matter experts (e.g., electrophysiologists) for clinical workflow and output validity, but not in the context of diagnostic "ground truth" derived from patient-specific interpretations.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable or not specified in this type of submission. The "ground truth" is based on system specifications and expected software behavior, not human interpretation requiring adjudication.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not performed as described for AI assistance. This submission is for software updates to a diagnostic system, not a new AI-powered diagnostic algorithm designed to assist human readers directly in interpreting images or data.
• Effect Size of Improvement: Not applicable, as no such study was conducted.

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

• Standalone Study: Not directly applicable in the typical sense of evaluating an AI algorithm's diagnostic performance. The device is a "Programmable Diagnostic Computer" used in electrophysiology procedures. Its performance is evaluated by ensuring its internal computations, mapping, and display functions are accurate and consistent with its design specifications and the predicate device. It's not a standalone "algorithm" providing a diagnosis independent of human interaction.

7. Type of Ground Truth Used

• Type of Ground Truth: For software verification, the ground truth is primarily based on design specifications, established functional requirements, and the expected behavior of the system as defined by its engineers and clinical subject matter experts. This is not clinical "ground truth" like pathology, expert consensus on imaging, or outcomes data, as this is a functional system, not an AI diagnostic algorithm.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This document does not describe the development or training of a new AI/ML model. The updates are to existing software components (bug fixes, compatibility, minor enhancements).

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

• Establishing Ground Truth for Training Set: Not applicable, as no new AI/ML training data or process is described.

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