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The EnSite System is indicated for patients for whom electrophysiology studies are indicated.

• When used with the EnSite™ Catheter, the EnSite System 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.
  OR
• When used with the EnSite NavX™ Surface Electrode Kit, the EnSite System is . intended to display the position of conventional electrophysiology catheters in the heart.

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.

The provided text appears to be a 510(k) summary for the St. Jude Medical EnSite System (Model EE3000), along with its associated components. This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving that a new device meets specific acceptance criteria based on detailed performance studies with clinical endpoints.

Therefore, the document does not contain the detailed information requested for acceptance criteria, device performance, sample sizes, ground truth establishment, expert qualifications, or MRMC studies. The 510(k) process relies on demonstrating that the new device has "the same technological characteristics" and is "as safe and effective as the previously marketed device" based on a comparison to a predicate device.

Here's what can be extracted based on the provided text, and what is explicitly not available:

1. A table of acceptance criteria and the reported device performance

The document states: "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." and "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 document does not provide a table of
specific, quantifiable acceptance criteria or reported device performance metrics against such criteria. The focus is on demonstrating equivalence to a predicate device.

2. Sample size used for the test set and the data provenance

The document mentions "a battery of bench and user tests" and "device validation testing," but does not specify the sample size, data provenance (country of origin), or whether the data was retrospective or prospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not mention the use of experts to establish ground truth or their qualifications. Testing appears to be primarily bench and user-based as part of internal validation.

4. Adjudication method for the test set

The document does not mention any adjudication method for the test set.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

The document does not mention a multi-reader multi-case (MRMC) study or any comparison related to human readers improving with or without AI assistance. The EnSite system described is an electrophysiology cardiac mapping system, not an AI-assisted diagnostic tool in the typical sense that would necessitate an MRMC study for assessing reader improvement.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

The document does not provide details on standalone algorithmic performance. The system is described as a "computerized storage and display system for use in electrophysiology studies" which implies human interaction.

7. The type of ground truth used

The document does not specify the type of ground truth used. Given the context of comparing to a predicate device and internal validation, the "ground truth" would likely be based on established engineering and clinical standards for electrophysiology systems or direct comparison to the predicate device's output.

8. The sample size for the training set

The document does not mention a training set sample size. This type of 510(k) submission generally does not involve machine learning "training sets" in the way that AI/ML devices do.

9. How the ground truth for the training set was established

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

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The EnSite System is indicated for patients for whom electrophysiology studies are indicated.
When used with the EnSite* Catheter, the EnSite System 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.
OR
When used with the EnSite NavX™ Surface Electrode Kit, the EnSite System is . intended to display the position of conventional electrophysiology catheters in the heart.

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.

This 510(k) summary does not contain the level of detail necessary to answer all the questions about acceptance criteria and the study proving the device meets them as typically presented for AI/ML-based medical devices. This document predates the widespread use of sophisticated AI/ML in medical devices and therefore focuses on traditional medical device validation.

Based on the provided information, here's what can be extracted and what cannot:

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics in the format requested for an AI/ML device. Instead, it relies on a qualitative assessment of "safety and effectiveness" compared to a predicate device.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. The abstract mentions "bench and user tests," but details on sample size, data type, or provenance are omitted.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided. Given the nature of the device (an electrophysiology cardiac mapping system and its components), ground truth would likely be established through physician observation during electrophysiology studies, but the specifics are absent.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

A multi-reader multi-case (MRMC) comparative effectiveness study as typically understood for AI/ML evaluation was not performed or reported. The document describes a traditional medical device submission based on substantial equivalence to a predicate device, not an AI efficacy study. The concept of "human readers improve with AI vs without AI assistance" is not applicable here as it is not an AI/ML device in the modern sense.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This concept is not applicable to this device. The EnSite System is a computerized storage and display system that supports electrophysiology studies, not a standalone AI algorithm producing diagnoses or interpretations without human involvement. Its "performance" is inherently linked to its use by an electrophysiologist in conjunction with catheters or surface electrodes.

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

The document does not specify the type of ground truth. For an electrophysiology mapping system, "ground truth" would likely relate to accurate identification and visualization of cardiac activation patterns and catheter positions, validated through clinical observation and established electrophysiological principles, rather than pathology or outcomes data in the traditional sense of a diagnostic AI device.

8. The sample size for the training set

This information is not provided and is not applicable in the context of this traditional medical device submission. The device is not an AI/ML system that undergoes "training" in the computational sense.

9. How the ground truth for the training set was established

This information is not provided and is not applicable.

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