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The Medtronic CardioInsight® Cardiac Mapping System is intended for acquisition, analysis, display and storage of cardiac electrophysiological data and maps for analysis by a physician.

The Medtronic CardioInsight® Cardiac Mapping System is a non-invasive mapping system for beat-by-beat, multichamber, 3D mapping of the heart. The CardioInsight Cardiac Mapping System displays cardiac maps and virtual electrograms from real-time chest ECG signals (measured by a Sensor Array placed on the torso) and CT scan data. The ECG signals in concert with the CT scan information (geometrical information) are used in mathematical algorithms to transform the measured body surface signals into epicardial signals via solving the cardiac inverse problem. The CardioInsight Cardiac Mapping System software uses this data to provide various cardiac signal analyses and displays interactive 3D color maps including potential, activation, voltage, propagation, and phase maps. The CardioInsight Cardiac Mapping System system is mobile and can be used for mapping at the patient's bedside or in the EP lab.

This looks like a 510(k) summary for the Medtronic CardioInsight® Cardiac Mapping System.

Based on the provided document, the device described is a cardiac mapping system, not an AI/ML algorithm that predicts or diagnoses. Therefore, much of the requested information (like acceptance criteria for AI performance, sample sizes for training/test sets, expert adjudication, MRMC studies, or standalone algorithm performance) is not applicable to this device submission.

The document focuses on demonstrating substantial equivalence to a predicate device (ECVUE MAPPING SYSTEM) based on shared intended use, technology, and performance, rather than providing specific performance metrics against clinical acceptance criteria in the context of an AI model's output.

Here's what can be extracted and what is explicitly stated as not applicable:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes various performance tests conducted to verify the device's compliance with safety and specifications, and that it "performs as designed." However, it does not present a table of specific clinical acceptance criteria with corresponding performance metrics in the way one would for a diagnostic or predictive AI device. The performance data highlighted are primarily related to electrical safety, mechanical safety, software/firmware verification, algorithm testing (to ensure it met requirements and functioned as intended), packaging validation, and usability testing.

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

• Not Applicable in the traditional AI sense. The document states: "Preclinical and clinical testing were not required for the CardioInsight Cardiac Mapping System." This implies there wasn't a specific "test set" of clinical cases used to evaluate an algorithm's performance against ground truth in the way an AI model would be tested. The validation was primarily system functionality and safety.

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

• Not Applicable. As no clinical "test set" was described for an AI algorithm's output, there's no mention of experts establishing ground truth in this context.

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

• Not Applicable.

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:

• Not Applicable. This is not an AI-assisted diagnostic device where human reader improvement would be measured. The device provides data and maps for analysis by a physician.

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

• Not Applicable. The device is a system for "acquisition, analysis, display and storage of cardiac electrophysiological data and maps for analysis by a physician." It's an instrument providing information to a human. There is no mention of a standalone diagnostic algorithm being evaluated.

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

• Not Applicable in the context of AI performance. The system's "truth" is its ability to accurately acquire and transform ECG and CT data into epicardial signals and maps, which is verified through engineering and functional testing rather than clinical expert ground truth for interpretation.

8. The sample size for the training set:

• Not Applicable. The device is not an AI/ML model that undergoes a "training phase" with a specific dataset. Its algorithms are based on mathematical principles (solving the cardiac inverse problem) and are validated through standard software and system verification.

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

• Not Applicable. See point 8.

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The CardioInsight ECVUE Mapping System is intended for acquisition, analysis, display and storage of cardiac electrophysiological data and maps for analysis by a physician.

ECVUE is a non-invasive mapping system for beat-by-beat, multi-chamber, 3D mapping of the heart. The system displays cardiac maps and virtual electrograms from real-time chest ECG signals (measured by a Sensor Array placed on the torso) and CT scan data. The ECVUE software provides various cardiac signal analyses and displays interactive 3D color maps including potential, activation, voltage, propagation, and phase maps. The system is mobile and can be used for mapping at the patient's bedside or in the EP lab.

This document does not contain the detailed information necessary to answer all parts of your request. It is a 510(k) summary for a medical device and primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a comprehensive study report with acceptance criteria and performance metrics in the way you've outlined.

Here's what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance:

This information is not present in the provided document. The 510(k) summary states "Testing demonstrated that the modified ECVUE Mapping System is substantially equivalent to the original (predicate) system." and "Full system, integration, unit regression testing was performed." However, it does not specify what the acceptance criteria for these tests were or report specific performance metrics against those criteria.

2. Sample sized used for the test set and the data provenance:

This information is not present in the provided document. The document states "No clinical testing was conducted." The non-clinical testing ("Full system, integration, unit regression testing") does not specify a test set size or data provenance.

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

This information is not present in the provided document, as no clinical testing with a "test set" and "ground truth" established by experts is mentioned.

4. Adjudication method for the test set:

This information is not present in the provided document, as no clinical testing with adjudication is mentioned.

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:

This information is not present in the provided document. The device is a "mapping system" that "displays cardiac maps and virtual electrograms from real-time chest ECG signals... for analysis by a physician." It's not described as an AI-powered diagnostic tool that assists human readers in the context of an MRMC study.

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

This information is not present in the provided document, as no explicit performance study (standalone or otherwise) is detailed. The device is intended for "analysis by a physician," implying a human-in-the-loop system.

7. The type of ground truth used:

This information is not present in the provided document, as no clinical testing with a defined ground truth is mentioned.

8. The sample size for the training set:

This information is not present in the provided document. The document refers to "updates to the software based on internal/user feedback and maintenance updates to the OTS," but does not describe a training set for an algorithm.

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

This information is not present in the provided document, as no training set or its ground truth establishment is mentioned.

Summary of what is available from the document:

• Device Name: ECVUE Mapping System, Model AT200
• Intended Use: Acquisition, analysis, display and storage of cardiac electrophysiological data and maps for analysis by a physician.
• Regulatory Status: Class II, Product Code DOK (Programmable Diagnostic Computer).
• Predicate Device: ECVUE Mapping System (K140497) - implying the current device is an updated version of an already cleared device.
• Changes from Predicate: Software updates based on internal/user feedback and maintenance updates to OTS (Off-The-Shelf) components. These changes are described as "very small and do not change the functionality or technological characteristics of the device. The Intended Use of the device is not affected."
• Testing Performed: "Full system, integration, unit regression testing was performed."
• Clinical Testing: "No clinical testing was conducted."
• Conclusion: The modified system is "substantially equivalent to the original (predicate) system and the changes did not affect the safety and effectiveness of the device when it is used as labeled."

The document focuses on demonstrating that the changes made to the device (mostly software updates) do not affect its safety and effectiveness, thus maintaining substantial equivalence to its predicate. It does not provide performance data or acceptance criteria for an initial clearance study of the device's efficacy in the way a new, de novo device might.

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The CardioInsight ECVUE Mapping System is intended for acquisition, and storage of cardiac electrophysiological data and maps for analysis by a physician.

ECVUE is a non-invasive mapping system for beat-by-beat, multi-chamber, 3D mapping of the heart. The system displays cardiac maps and virtual electrograms from real-time chest ECG signals (measured by a Sensor Array placed on the torso) and CT scan data. The ECVUE software provides various cardiac signal analyses and displays interactive 3D color maps including potential, activation, voltage, propagation, and phase maps. The system is mobile and can be used for mapping at the patient's bedside or in the EP lab.

The CardioInsight ECVUE Mapping System's acceptance criteria and studies are described below:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size and Data Provenance for Test Set

• Sample Size (Clinical Experience): 60 patients.
• Data Provenance: From two European centers (retrospective, given the phrase "Clinical experience with commercially available device").
• Sample Size (Animal Study): Not explicitly stated, but described as a "controlled porcine model" in a GLP study.
• Data Provenance (Animal Study): Not explicitly stated but assumed to be prospective due to the nature of a GLP "study."

3. Number of Experts and Qualifications for Ground Truth (Test Set)

The document does not explicitly state the number of experts used to establish ground truth for the test set or their specific qualifications (e.g., "radiologist with 10 years of experience").

• For the animal study, the comparison was made "as compared to a standard electrophysiology (EP) study," implying that the ground truth was established by standard EP procedures and potentially interpreted by associated EP specialists.
• For the clinical experience, the data represents "routine EP clinical practice," suggesting that the interpretation and ground truth were established by the treating physicians in those EP centers.

4. Adjudication Method for the Test Set

The document does not explicitly mention an adjudication method (e.g., 2+1, 3+1, none) for establishing ground truth in either the animal study or the clinical experience. The ground truth seems to be derived from the "standard electrophysiology (EP) study" in the animal model and from "routine EP clinical practice" in the clinical experience.

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

No multi-reader multi-case (MRMC) comparative effectiveness study is described where the effect size of human readers improving with AI vs. without AI assistance is quantified. The focus is on the device's performance compared to standard EP studies or its performance in clinical practice, not on the improvement of human readers specifically with AI assistance.

6. Standalone Performance Study

Yes, a standalone (algorithm only without human-in-the-loop performance) study was effectively done. The GLP animal study aimed to "demonstrate the performance of the ECVUE system in identifying origin and pattern of various rhythms as compared to a standard electrophysiology (EP) study." This suggests an assessment of the device's capability to localize rhythms and characterize timings on its own, without explicit interaction with a human reader for real-time decision-making in the performance evaluation. The clinical experience section also states that the device "performs as intended," implying its standalone functionality.

7. Type of Ground Truth Used

• Animal Study: The ground truth was established by "a standard electrophysiology (EP) study." This typically involves invasive mapping techniques that are considered the gold standard for cardiac electrophysiology.
• Clinical Experience: The ground truth was derived from "routine EP clinical practice," which would involve standard diagnostic and treatment procedures by physicians, using a range of available tools and expert interpretation.

8. Sample Size for the Training Set

The document does not explicitly state the sample size used for the training set.

9. How Ground Truth for the Training Set was Established

The document does not explicitly describe how the ground truth for any potential training set was established. The studies mentioned focus on verification and validation (for performance testing and clinical experience) rather than the development or training of the system.

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