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The Noga Automated Sleep Study Scoring and Data Management System is a computer program (software) intended for use as an aid for the diagnosis of respiratory related sleep disorders.

The Noga System is intended to be used for analysis, display, redisplay (retrieve), summarize, reports generation and networking of physiological data received from a physiological activity monitoring device.

Physiological data includes: ECG, SpO2, EtCO2 and Impedance respiration.

The Noga Automated Study Scoring and Data Management System (Noga System) is a Web-based computer program (software), intended for use as an aid to the diagnosis of respiratory-related sleep disorders.

The Noga System is designed to process the raw signal data acquired by a third party physiological activity monitoring device in standard medical download format, analyze them, obtain the study's analysis results, generate summary reports, and display the signals' data and reports on a personal computer, using a standard Internet Explorer Browser.

Signals from the physiological activity monitoring device include the following:

• ECG
• Impedance respiration
• EtCO2
• SpO2

Scoring Analysis includes:

• Apnea/Hypopnea Index (AHI)
• Sleep Staging (Sleep - Wake stages, and Total Sleep Time)
• Respiratory Events Detection (Apnea and Hypopnea)

Here's a summary of the acceptance criteria and the study details for the Noga Automated Sleep Study Scoring and Data Management System, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

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

   • The document states that "A clinical study was conducted," but it does not explicitly state the sample size (number of patients or studies) used for the test set.
   • Data provenance: Not specified in the provided text (e.g., country of origin, retrospective or prospective).

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

   • The document does not explicitly state the number of experts used to establish the ground truth for the test set.
   • Qualifications of experts: The ground truth was established against "gold-standard PSG manual scoring." This implies human experts (sleep technologists or physicians) performed the manual scoring, but their specific qualifications (e.g., years of experience, board certification) are not provided.

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

   • The document does not specify an adjudication method. It simply refers to "gold-standard PSG manual scoring."

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:

   • The document does not describe an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The study focused on the standalone performance of the Noga system compared to gold-standard and a predicate device.

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

   • Yes, a standalone performance study was done. The clinical study validated "the accuracy of the Noga System to detect respiratory related sleep disorders against both a gold-standard PSG and the Morpheus predicate device." This assesses the algorithm's performance directly.

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

   • The primary ground truth used was expert consensus / manual scoring, specifically "gold-standard PSG manual scoring". It was also compared against the performance of a predicate device (Morpheus).

7. The sample size for the training set:

   • The document does not provide information on the sample size used for the training set. It only mentions that the Noga software program is "based on the Morpheus software program."

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

   • The document does not explicitly state how the ground truth for the training set was established. Given that the Noga software is based on Morpheus, it is likely that Morpheus's training data and ground truth establishment methods would be relevant, but this is not detailed for Noga itself.

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The intended use of the NOGA™ XP Cardiac Navigation System with QwikMap™ Software is catheter-based cardiac mapping.

The NOGA™ XP Cardiac Navigation System with QwikMap™ Software allows realtime display of cardiac maps in a number of different formats. Maps may be displayed as cardiac electrical activation maps, cardiac electrical propagation maps, cardiac electrical potential maps, cardiac chamber geometry maps, cardiac dynamic maps, cardiac hemodynamic maps, and cardiac electromechanical maps. The acquired patient signals, including body surface ECG and intracardiac electrograms may also be displayed in real time on the display screen.

The NOGA™ XP Cardiac Navigation System with QwikMap™ Software is a modification of the NOGA™ Cardiac Navigation System cleared for marketing under K000332. Like the predicate device, the NOGA™ XP System is a computerized electromechanical mapping system designed to acquire, analyze, and display electromechanical maps of the heart in a clear and intuitive manner. Maps are constructed by combining and integrating information from intracardiac electrograms with the respective endocardial locations. Like the CARTO™ Cardiac Navigation systems (K992968, K993729, K000248, K000190, K013083, and K020863), all commercially available Biosense Webster catheters equipped with the proprietary location sensor(s) that provide(s) real-time information on the location of the catheter can be used with the NOGA™ XP Cardiac Navigation System.

The current NOGA™ Cardiac Navigation System software was upgraded to allow for:

• . on-screen visualization of the catheter shaft.
• reduction of the steps required to create electromechanical maps .
  • · NOGA™ XP software creates the equivalent of a 50-point map with only 8-10 contact points, and
  • · easier mapping of transient events.

Here's an analysis of the provided text regarding the acceptance criteria and study for the NOGA™ XP Cardiac Navigation System with QwikMap™ Software:

Acceptance Criteria and Device Performance Study

The provided document describes the NOGA™ XP Cardiac Navigation System with QwikMap™ Software as a modification to an existing device, the NOGA™ Cardiac Navigation System. The primary method for demonstrating safety and effectiveness relied on showing substantial equivalence to predicate devices. This means that instead of establishing new performance metrics, the device's performance was compared to that of already cleared devices to ensure it performed in an equivalent manner and did not raise new questions of safety or effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

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

• Test Set Sample Size: The document does not specify a distinct "test set" in terms of number of cases, patients, or data points for a traditional clinical study. Instead, it mentions "non-clinical bench and animal testing."
  • For the animal testing, it explicitly states "testing in the porcine model." The number of animals used is not provided.
• Data Provenance:
  • Bench Testing: Implied to be laboratory-based.
  • Animal Testing: Porcine (pig) model.
  • The document does not mention human data for either retrospective or prospective studies. The focus is on demonstrating equivalence through non-clinical means.

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

The document does not mention the use of experts to establish ground truth for the "test set" in the context of a clinical study or even for the bench and animal testing. The evaluation appears to be based on engineering and physiological testing rather than expert-derived ground truth.

4. Adjudication Method for the Test Set

Not applicable. There is no mention of a ground truth adjudication process involving multiple reviewers for a test set.

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

No, a Multi Reader Multi Case (MRMC) comparative effectiveness study was not conducted or reported in this document. The device is a "cardiac navigation system," which is a tool for clinicians, but the submission focuses on its technical equivalence and functionality rather than changes in human reader performance or diagnostic accuracy.

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

The device is a "cardiac navigation system" and "programmable diagnostic computer." It is inherently a device that provides information and displays data for human clinicians. Therefore, a purely standalone algorithm performance without human-in-the-loop context would not be directly applicable to its intended use. The "performance data" section focuses on the system's ability to acquire, analyze, and display information equivalently to predicate devices.

7. The Type of Ground Truth Used

• For the bench testing, the ground truth would likely be based on engineering specifications, known physical properties, electrical signal characteristics, and defined system outputs.
• For the animal (porcine) model testing, the ground truth would be based on physiological measurements and observations within the animal model, ensuring the system accurately represented cardiac activity and geometry as expected.

8. The Sample Size for the Training Set

The document does not mention a "training set" or machine learning aspects in a way that implies a distinct dataset for training an AI algorithm. The device is described as a "computerized electromechanical mapping system," suggesting a model-based or rule-based system rather than a machine learning one that requires a dedicated training set. Software validation typically involves testing against requirements and known scenarios, not "training" in the AI sense.

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

Not applicable, as a discrete "training set" for an AI algorithm is not identified in the provided text.

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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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