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Indicated for displaying images of the tracheobronchial tree to aid the physician in guiding endoscopic tools or catheters in the pulmonary tract and to enable marker placement within soft lung tissue. It does not make a diagnosis and is not an endoscopic tool. Not for pediatric use.

The ILLUMISITE™ Platform is an image-guided electromagnetic navigation system used to guide catheters or endoscopic tools to predetermined targets in or adjacent to the bronchial tree on a path identified by CT scan. During a procedure, the physician navigates endoscopic tools to targets in the lungs such as lymph nodes and solitary pulmonary nodules.

The ILLUMISITE™ Platform, is a modification to the previously cleared predicate device, the superDimension™ navigation system. The primary difference is the ability of the ILLUMISITE Platform to provide continuous positional feedback throughout the procedure (i.e. continuous guidance) via a sensor in the extended working channel. The system console hardware, and extended working channel have been modified to incorporate the continuous guidance navigation feature.

The provided text does not contain specific acceptance criteria or a study that rigorously proves the device meets those criteria in a clinical or large-scale performance setting. The document is a 510(k) summary for the ILLUMISITE™ Platform, focusing on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance efficacy data against a set of predefined acceptance criteria for AI or diagnostic performance.

Here's an analysis of the provided text in relation to the requested information:

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

The document mentions "System Accuracy" with a reported performance of "≤3mm root mean square (RMS) based on accuracy bench testing". This is the closest thing to an acceptance criterion and reported performance. However, this is a bench test, likely for mechanical accuracy, and not a demonstration of clinical performance or AI-driven diagnostic accuracy.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document primarily discusses "Design verification and validation test results" and "Design validation was successfully performed under simulated use conditions by representative users." It does not specify a quantitative sample size for any clinical test set or details about data provenance (e.g., country of origin, retrospective/prospective). The testing appears to be functional and safety-focused, rather than a large-scale clinical performance study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

The document mentions "Design validation testing with qualified physicians, clinicians, and service personnel to confirm functionality and user interface." It does not specify the number of experts, their qualifications, or their role in establishing ground truth for a test set, as no diagnostic performance study is described. Their role appears to be evaluating usability and functionality rather than providing ground truth for diagnostic accuracy.

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

No information is provided regarding an adjudication method, as no study involving multiple readers or diagnostic assessments requiring adjudication is described.

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

No MRMC study is mentioned. The device is an image-guided electromagnetic navigation system, not an AI diagnostic tool primarily aimed at improving human reader performance.

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

The document does not describe a standalone AI algorithm performance study. The device provides "image-guided electromagnetic navigation" and "continuous positional feedback." Its function is to assist in guiding tools, not to autonomously provide a diagnosis or interpretation.

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

For the "System Accuracy" measurement, the ground truth would inherently be a precisely measured physical reference (e.g., a known distance or position on a test bench). However, for any clinical ground truth related to navigation or targeting, it's not specified. The device "does not make a diagnosis," so ground truth for diagnostic accuracy is not relevant to its stated function.

8. The sample size for the training set

The document pertains to a medical device's 510(k) submission, confirming substantial equivalence to a predicate device. It does not describe an AI model's training set or its sample size.

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

As there is no mention of an AI model with a training set, there is no information on how its ground truth was established.

Summary of what is present in the document:

The 510(k) summary focuses on demonstrating that the ILLUMISITE™ Platform is substantially equivalent to its predicate device (superDimension™ Navigation System) based on:

• Same indications for use, principle of operation, fundamental technology, and inherent design.
• Changes made (e.g., continuous guidance, hardware updates) do not affect safety and effectiveness.
• Design verification and validation (including software, electrical safety, biocompatibility, sterilization, mechanical, packaging, hardware component testing).
• User validation under simulated use conditions by representative users confirms functionality and user interface.
• Compliance with various international and FDA-recognized consensus standards.
• A "System Accuracy" bench test result of ≤3mm RMS.

The document explicitly states: "Clinical tests were not required to validate the changes to the ILLUMISITE Platform and accessories." This indicates that a study demonstrating clinical performance or meeting specific diagnostic acceptance criteria, as one might expect for an AI diagnostic device, was not conducted or presented as part of this 510(k) submission. The focus is on the safety and performance of the navigation system itself, and its substantial equivalence to an existing cleared device.

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