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EasyFinder™ Fixed Curve Diagnostic Catheter is used for electrogram recording and cardiac stimulation during diagnostic electrophysiology studies.

The EasyFinder™ Fixed Curve Diagnostic Catheter is a sterile, single-use diagnostic catheter with multiple electrodes and a fixed distal curve. It has been designed to facilitate electrophysiological mapping of cardiac structures in 28 models and 6 kinds of curves.

The catheter has a high-torque shaft with a fixed curve section containing an array of platinum electrodes. The high-torque shaft allows the plane of the curved tip to be rotated to facilitate accurate positioning of the catheter tip at the desired site.

The catheter is connected to separately cleared diagnostic electrophysiology equipment via an accessory, the FORLNK™ Cable for Mapping Catheter.

The provided document, a 510(k) summary for the EasyFinder™ Fixed Curve Diagnostic Catheter, indicates that no clinical study was included in the submission. Therefore, information regarding acceptance criteria derived from a clinical study, sample sizes for test and training sets, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance, as requested, is not available from this document.

The substantial equivalence determination for this device is based on non-clinical performance testing and comparison to a predicate device.

Here's the information that can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly define "acceptance criteria" in a quantitative sense as might be seen for a new AI/software device. Instead, it states that the device complies with specific industry standards and regulatory guidance, which serve as the "acceptance criteria" for demonstrating safety and effectiveness. The "reported device performance" is its compliance with these standards.

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

• Not Applicable. No clinical study or separate test set in the context of an AI/software device performance evaluation was conducted or reported. Performance was based on non-clinical (bench) testing against established standards and comparison to a predicate device.

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

• Not Applicable. No clinical study or expert-adjudicated test set in the context of an AI/software device performance evaluation was conducted or reported.

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

• Not Applicable. No expert adjudication was conducted or reported.

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 a hardware medical device (diagnostic catheter), not an AI-assisted diagnostic tool for human readers. No MRMC study was conducted or reported.

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

• Not Applicable. This is a hardware medical device, not an algorithm.

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

• Not Applicable. For the non-clinical tests, the "ground truth" was established by the specifications defined in the referenced international standards (e.g., ISO, IEC). For equivalence to the predicate, the characteristics of the predicate device served as the reference.

8. The sample size for the training set:

• Not Applicable. No training set, in the context of an AI/software device, was used or reported.

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

• Not Applicable. No training set was used.

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The catheter is indicated for electrophysiological mapping of cardiac structures in adult patients; i.e., stimulation and recording only.

The MultiCath* and the AcQRate Dx Fixed Curve Catheter are pre-shaped multipolar catheters for sensing of intracardiac signals and diagnostic pacing, in combination with an electrophysiological investigation and recording device.

The device consists of a catheter body with a distal curve, an array of platinum/iridium (PtIr) electrodes, and a proximal multipolar connector. Multiple electrode configurations are available with various numbers of electrodes and electrode spacing.

• Unless otherwise noted, the term "MultiCath" is used throughout to represent either MultiCath or the AcQRate Dx Fixed Curve Catheter.

The provided text is a 510(k) Summary for the BIOTRONIK MultiCath and AcQRate Dx Fixed Curve Catheter, and related MPK patient cables. It details the device's characteristics, intended use, and the non-clinical testing performed to establish substantial equivalence to a predicate device.

However, the document does NOT describe a study that proves the device meets specific acceptance criteria in terms of AI/algorithm performance (e.g., sensitivity, specificity, accuracy). The device in question is an electrophysiological catheter and patient cables for cardiac mapping and recording, which are hardware devices, not AI/algorithm-based diagnostic software.

Therefore, I cannot fulfill your request for information related to AI/algorithm performance, acceptance criteria for such algorithms, sample sizes for test/training sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance.

The provided text focuses on the following types of performance data for a medical device (hardware):

• Nonclinical Bench Testing: This includes design verification (dimensional, visual inspection, functional/compatibility, mechanical, corrosion testing) and design validation (usability testing).
• Biocompatibility Testing: To ensure the materials are safe for human contact.
• Sterilization, Shelf Life, and Packaging Validations: To ensure the device remains sterile and functional over time.

The acceptance criteria are implicitly that the device passes these various engineering and safety tests and demonstrates substantial equivalence to the predicate device in terms of functionality and safety. The reported device performance is "pass" for all listed tests.

To directly answer your request based only on the provided text, while acknowledging the mismatch with an AI/algorithm context:

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

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

• The document does not specify exact sample sizes (N) for each individual test. It states "All bench testing was conducted on the MultiCath Catheters necessary for Electrophysiological Diagnostics."
• Data provenance: Not explicitly stated, but implies internal company testing (BIOTRONIK / VascoMed GmbH in Germany) for the devices. It is non-clinical bench data.

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

• Not applicable as this is hardware testing against engineering standards, not a diagnostic algorithm requiring expert ground truth for interpretation.

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

• Not applicable; standard engineering and laboratory testing protocols are followed, where pass/fail is determined by objective measurements against predefined specifications.

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 device is a catheter and cables, not an AI-assisted diagnostic tool. No MRMC study was performed or required.

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

• Not applicable. This is a hardware device submission.

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

• For hardware, "ground truth" is established by adherence to recognized international and national standards (e.g., ISO, IEC, ASTM) and the manufacturer's own validated design specifications. The performance is objectively measured against these, not against human expert consensus or clinical outcomes data in the context of this 510(k).

8. The sample size for the training set:

• Not applicable. This is not an AI/ML algorithm that requires training data.

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

• Not applicable.

In summary, the provided document is a 510(k) submission for a physical medical device (catheter and cables), not an AI/ML-based diagnostic software. Therefore, many of the questions regarding AI/ML performance metrics, data sets, and expert involvement are not relevant to this document's content.

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