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The intended use of the Prucka Engineering, Inc. CardioLab EP 4.2 System is to acquire, filter, digitize, amplify, display, and record electrical signals obtained during electrophysiological studies and related procedures conducted in an electrophysiological laboratory. Signal types acquired include ECG signals, direct cardiac signals, and pressure recordings. Physiological parameters such as diastolic, systolic, and mean blood pressure, heart rate, and cycle length may be derived from the signal data, displayed and recorded. The system allows the user to monitor the acquisition of data, review the data, store the data, perform elementary caliper-type measurements of the data, and generate reports on the data. Additionally, the system may acquire, amplify, display, and record data received from other medical devices typically used during these procedures, such as imaging devices and RF generators.

The CardioLab EP system does not control the delivery of energy, administer drugs, perform any life-supporting or life-sustaining functions, or analyze physiological data or other data acquired during an EP procedure. It does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities.

The CardioLab EP System is a microprocessor based data acquisition system used during electrophysiology procedures to accquire ECG, intracardiac, pressure, and digital data from other devices such as RF generators and fluoro video systems. The ECG, intracardiac and pressure data are acquired by an amplifier that is connected to the patient by third-party devices such as ECG leadwires and catheters. The amplifier filters, amplifies, digitizes and transmits the data to the computer. The computer stores the data on optical disks, displays the data on the video monitors, allows the user to perform basic signal measurements, and prints out waveforms on a laser printer or continuous paper recorder. The software has three major functions: data acquisition and display, data storage, and reporting of data. The system is able to acquire signal data in the presence of pacing pulses. In addition to signal waveform display and basic caliper-type measurement, the system allows the user to create isopotential and isochronal activation maps of waveform timing information. The system can also be used to accept video input from a fluoroscopy system for either single frame capture or full motion video display. The system can also acquire data from an RF generator via standard computer RS-232 serial port. The CardioLab EP system does not control the delivery of energy, administer drugs, perform any life-supporting or life-sustaining functions, or analyze physiological data or other data acquired during an EP procedure. It does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities.

Here's an analysis of the provided text regarding the Prucka Engineering, Inc. CardioLab EP System's performance testing:

The document does not describe acceptance criteria for the device's performance in analyzing physiological data or detecting arrhythmias, as the device explicitly states it "does not analyze physiological data or other data acquired during an EP procedure. It does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities."

Instead, the non-clinical tests described focus on electrical safety, EMC (Electromagnetic compatibility), and basic functional validation of the system's ability to acquire, filter, digitize, amplify, display, and record various physiological signals and data from other medical devices.

Therefore, the table for "acceptance criteria and the reported device performance" will focus on these aspects related to the system's operational integrity and safety, rather than diagnostic performance on a specific medical condition.

Acceptance Criteria and Reported Device Performance

Study Information

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

   • The document does not specify a sample size for a test set in the context of physiological signal analysis or diagnostic performance.
   • The tests described are primarily non-clinical (electrical safety, EMC, and functional validation).
   • The data provenance is not relevant in the typical sense (e.g., country of origin of patient data) as these are engineering and safety tests on the device itself. The tests were performed by SEMKO and ETL Testing Laboratories, and in-house validation.

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

   • This is not applicable as the study concerns technical and safety compliance, not diagnostic performance requiring expert interpretation of medical images or signals. The "ground truth" for electrical safety tests are the defined limits and parameters in the international standards (IEC 601 series) and FDA guidance, as assessed by accredited testing laboratories and internal engineering teams.

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

   • Not applicable as the tests are objective measures against technical standards (e.g., leakage current, resistance to interference) and functional checks, not subjective interpretations requiring adjudication.

4. 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:

   • No MRMC study was done. The device explicitly states it "does not control the delivery of energy, administer drugs, perform any life-supporting or life-sustaining functions, or analyze physiological data or other data acquired during an EP procedure. It does not transmit alarms or arrhythmias, and does not have arrhythmia detection capabilities." Therefore, there is no AI component or diagnostic assistance for human readers to evaluate.

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

   • No standalone algorithm-only performance study was conducted. As stated above, the device does not perform analysis or detection, thus no algorithm for such tasks exists in this device.

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

   • The "ground truth" for the non-clinical tests is based on engineering specifications, international electrical safety and EMC standards (IEC 601 series), and FDA guidance. For the in-house functional validation, the ground truth would be the expected operational parameters and outputs of the system according to its design specifications.

7. The sample size for the training set:

   • Not applicable. This device does not use machine learning or AI that would require a training set.

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

   • Not applicable, as there is no training set mentioned or implied by the device's capabilities.

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The Biosense NOGA system is designed to acquire, analyze, and display electroanatomical maps of the human heart.

The Biosense NOGA system is designed to acquire, analyze, and display electroanatomical maps of the human heart. The maps are reconstructed using the combination of information gathered from the integration of a plurality of intracardiac electrograms with their respective endocardial locations. In the NOGA system the location information needed to create the cardiac maps is acquired simultaneously with the local electrogram using STAR catheters, which are locatable-tip catheters equipped with a Biosense sensor. The NOGA system also allows presentation of electro-anatomical maps as a function of time over the cardiac cycle. The NOGA system is for the most part identical in design and construction to the Biosense CARTO system. The NOGA system uses the same Biosense nonfluoroscopic location technology used in the CARTO system. The NOGA system additionally uses this technology to collect additional information about the heart chamber geometry as a function of time over the cardiac cycle.

This document describes the Biosense NOGA system, a cardiac mapping system. However, the provided text does not contain the detailed study information required to fully answer your request regarding acceptance criteria and performance studies. The document is primarily a 510(k) summary focused on demonstrating substantial equivalence to a predicate device (Biosense CARTO system) and compliance with standards.

Here's an analysis based on the available information and what's missing:

1. Table of Acceptance Criteria and Reported Device Performance

This table cannot be fully generated from the provided text. The document states:

• "The non-clinical bench and animal testing show that the device is as safe and as effective as the previously marketed device to which it is being compared and does not raise any new questions of safety or effectiveness."

This is a general statement of equivalency, not specific performance metrics or acceptance criteria. It implies that the NOGA system met the same (unspecified) safety and effectiveness criteria as the CARTO system.

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

This information is not provided in the document.

• Sample Size (Test Set): Not mentioned. The document refers to "non-clinical bench and animal testing" but does not quantify the sample size (e.g., number of animals, number of bench tests).
• Data Provenance: Not mentioned (e.g., country of origin, retrospective/prospective). While Biosense Ltd. is located in Israel, there's no explicit statement about where the testing was conducted or the origin of any data used. The testing is described as "non-clinical bench and animal testing," indicating it's likely proprietary data rather than data from external clinical trials.

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

This information is not provided in the document.

• The document implies that the ground truth for "safety and effectiveness" was established by comparison to the predicate CARTO system and by standard engineering and animal testing. However, it does not mention the involvement of human experts in establishing a specific "ground truth" for a test set, nor their qualifications.

4. Adjudication Method for the Test Set

This information is not provided in the document.

• No adjudication method (e.g., 2+1, 3+1) is mentioned, as there is no description of a clinical test set requiring expert review and adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This information is not applicable and not provided.

• The NOGA system is a cardiac mapping system, not an AI-assisted diagnostic device where "human readers" would be involved in interpreting its output in the context of an MRMC study. Its function is to acquire, analyze, and display electroanatomical maps, directly providing geometric and electrical information.
• The concept of "AI assistance" and human reader improvement is not relevant to the description of this device.

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

This information is partially inferable but not explicitly stated in a structured way.

• The NOGA system is inherently a "standalone" system in the sense that its primary function is to collect and process data to generate maps. The "algorithm only" performance would be its ability to accurately acquire and display electro-anatomical maps and location information.
• The statement "The non-clinical bench and animal testing show that the device is as safe and as effective as the previously marketed device" implies that the system, as a whole, performed effectively in these tests without necessarily quantifying a distinct "algorithm only" performance separate from the entire device operation. The system's "performance" is its ability to generate the maps.

7. The Type of Ground Truth Used

Based on the description:

• Comparison to the predicate device (Biosense CARTO system): The NOGA system's performance for "safety and effectiveness" is benchmarked against the existing CARTO system, which itself presumably had established ground truth metrics during its own development and regulatory clearance.
• Conventional methods/technologies: The text mentions "Conventionally, such information [heart chamber geometry as a function of time] would be collected using fluoroscopy or cine while injecting a radiopaque contrast agent into the heart chamber (ventriculography)." This suggests that conventional methods like fluoroscopy or ventriculography likely served as a form of ground truth for evaluating the NOGA system's ability to provide similar information without radiation.
• Bench and animal testing: This implies various quantifiable parameters in these controlled environments were used as ground truth for aspects like accuracy of location, electrogram acquisition, and mapping capabilities.

8. The Sample Size for the Training Set

This information is not provided in the document.

• The NOGA system, as described, is a mapping technology, not a machine learning model that would typically have an explicit "training set" in the modern sense. It relies on physical principles and signal processing algorithms rather than learned patterns from a large dataset. Therefore, the concept of a "training set sample size" as usually applied to AI/ML devices is likely not directly applicable here.

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

This information is not provided and is not applicable for the same reasons mentioned in point 8.

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