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The MAGELLAN™ system, which is comprised of a medical workstation, a magnetic location system and a range of locatable tools is intended to be used as an image guided neurosurgery navigation system to pre-operatively and intra-operatively perform the following functions:

• process and display pre-operatively radiographic images on a monitor; .
• provide intra-operative image control based on the position and orientation of a . user directed tool;
• . allow for the integration and usage of the Blosense magnetic location system and a range of different tool attachments; and
• store/retrieve image data on computer access media (e.g. hard disks, archive . media)

Circumstances:
The MAGELLAN™ system is intended to be used during planning of a procedure, when more than one approach (c.g. cntry point, trajectory, craniotomy size) is being considered, and also during surgery when:

• . the target or approach is in a region with few anatomical landmarks (e.g. subcortical brain) or with complex anatomy;
• 방 the target or approach is in a region where normal landmarks have been distorted either by disease or by previous surgery;
• the target or approach is in close proximity to critical structures) e.g. venous sinuses, air sinuses, blood vessels, nerves) which must be avoided or negotiated; Or
• the target delineation is important and will not move significantly during the . implementation of the approach (e.g. skull-based tumors. sinus diseases, corpus callosotomies).

I Jisease or Conditions:
The MAGELLAN™ system is indicated for patients who have imaged space occupying lesions or malfunctions (both soft tissue and osscous) in the head.

The Magellan system is a subset of the CARTO system. The CARTO system consists of the location system and the viewing station for the EP application combined together in one product. The Magellan system is the same location system used in CARTO, to be sold separately for use with a range of different 510(k) approved locatable accessory devices and viewing stations for applications.

The provided text describes the Magellan system, a location system intended for intrabody mapping and navigation, specifically for image-guided neurosurgery. However, it does not contain information regarding acceptance criteria, device performance, or any specific study detailing such performance.

The document states that "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 statement implies that the device was evaluated against a predicate device (Biosense CARTO system, K954395), and the testing confirmed substantial equivalence. However, no specific data, acceptance criteria, or study details are provided to support this claim.

Therefore, I cannot fulfill the request to provide:

1. A table of acceptance criteria and reported device performance.
2. Sample size used for the test set or data provenance.
3. Number of experts used to establish ground truth or their qualifications.
4. Adjudication method for the test set.
5. Information on a multi-reader multi-case (MRMC) comparative effectiveness study or effect size.
6. Information on standalone performance.
7. The type of ground truth used.
8. Sample size for the training set.
9. How ground truth for the training set was established.

The provided text focuses on the 510(k) summary, regulatory compliance (EMC directive, IEC standards), and the intended use and indications for the Magellan system, along with its substantial equivalence to the CARTO system. It does not elaborate on the specific performance studies that would include the requested criteria.

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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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