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The Ion™ Endoluminal System (Model IF1000) assists the user in navigating a catheter and endoscopic tools in the pulmonary tract using endoscopic visualization of the tracheobronchial tree for diagnostic and therapeutic procedures. The Ion™ Endoluminal System enables fiducial marker placement. It does not make a diagnosis and is not for pediatric use.

The PlanPoint™ Software uses patient CT scans to create a 3D plan of the lung and navigation pathways for use with the Ion™ Endoluminal System.

The Ion™ Endoluminal System, Model IF1000, is a software-controlled, electromechanical system designed to assist qualified physicians to navigate a catheter and endoscopic tools in the pulmonary tract using endoscopic visualization of the tracheobronchial tree for diagnostic and therapeutic procedures. It consists of a Planning Laptop with PlanPoint™ Software, a System Cart with System Software, a Controller, Instruments, and Accessories. The IF1000 Instruments include the Ion™ Fully Articulating Catheter, the Ion™ Peripheral Vision Probe, and the Flexision™ Biopsy Needles.

The Planning Laptop is a separate computer from the System Cart and Controller. A 3D airway model is generated from the patient's chest CT scan using the PlanPoint™ Software.

The System Cart contains the Instrument Arm, electronics for the follower portion of the servomechanism, and two monitors. The System Cart allows the user to navigate the Catheter Instrument with the Controller, which represents the leader-follower relationship. For optimal viewing, the physician can position the monitors in both vertical and horizontal axes.

The Controller is the user input device on the Ion™ Endoluminal System. It provides the controls to command insertion, retraction, and articulation of the Catheter. The Controller also has buttons to operate the Catheter control states.

The Ion Endoluminal System enables optional Network and Virtual Reference features, streamlined mid-procedure restart, and enhances the control algorithm to provide an additional safety margin.

The provided text is a 510(k) summary for the Ion Endoluminal System (Model IF1000). While it describes software verification and validation, cybersecurity testing, and animal testing to demonstrate substantial equivalence to a predicate device, it does not contain specific acceptance criteria or detailed study results for an AI/algorithm's performance.

The device is primarily an electromechanical system with software for navigation and planning. The "PlanPoint™ Software" uses patient CT scans to create 3D plans, which is a software function, but the document does not treat it as a standalone AI algorithm that makes diagnoses or performs automated tasks requiring specific performance metrics like sensitivity, specificity, or AUC against a defined ground truth.

Therefore, I cannot provide the requested information in the format of a table outlining acceptance criteria and reported device performance for an AI algorithm, nor can I detail specific ground truth establishment, sample sizes for training/test sets, or information regarding multi-reader multi-case studies, as this information is not present in the provided document.

The document focuses on demonstrating that modifications to an existing device (adding support for optional network and virtual reference features, and streamlining mid-procedure restart) do not raise new questions of safety or effectiveness, and that the subject device remains substantially equivalent to its predicate.

In summary, the document you provided does not describe the kind of AI performance study details you are asking for.

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The Ion™ Endoluminal System (Model IF1000) assists the user in navigating a catheter and endoscopic tools in the pulmonary tract using endoscopic visualization of the tracheobronchial tree for diagnostic and therapeutic procedures. The Ion™ Endoluminal System enables fiducial marker placement. It does not make a diagnosis and is not for pediatric use.

The Flexision™ Biopsy Needle is used with the Ion™ Endoluminal System to biopsy tissue from a target area in the lung.

The PlanPoint™ Software uses patient CT scans to create a 3D plan of the lung and navigation pathways for use with the Ion™ Endoluminal System.

The Ion™ Endoluminal System, Model IF1000, is a software-controlled, electromechanical system designed to assist qualified physicians to navigate a catheter and endoscopic tools in the pulmonary tract using endoscopic visualization of the tracheobronchial tree for diagnostic and therapeutic procedures. It consists of a Planning Laptop with PlanPoint™ Software, a System Cart with System Software, a Controller, Instruments, and Accessories. The IF1000 Instruments include the Ion™ Fully Articulating Catheter, the Ion™ Peripheral Vision Probe, and the Flexision™ Biopsy Needles.

The Planning Laptop is a separate computer from the System Cart and Controller. A 3D airway model is generated from the patient's chest CT scan using the PlanPoint™ Software.

The System Cart contains the Instrument Arm, electronics for the slave portion of the servomechanism, and two monitors. The System Cart allows the user to navigate the Catheter Instrument with the Controller, which represents the master slave relationship. For optimal viewing, the physician can position the monitors in both vertical and horizontal axes.

The Controller is the user input device on the Ion™ Endoluminal System. It provides the controls to command insertion, retraction, and articulation of the Catheter. The Controller also has buttons to operate the Catheter control states.

The IF1000 System software is modified to optionally receive an intra-procedural cone beam CT image to enhance the virtual target location based on user input.

The provided text is a 510(k) summary for the Intuitive Surgical Ion™ Endoluminal System (Model IF1000). This document focuses on demonstrating substantial equivalence to a predicate device (K202370) rather than presenting a detailed clinical study for a novel AI algorithm's performance against specific acceptance criteria.

Therefore, much of the requested information regarding "acceptance criteria," "study that proves the device meets the acceptance criteria," "sample size for the test set and data provenance," "number of experts and their qualifications," "adjudication method," "MRMC study," "standalone performance," "type of ground truth," "training set sample size," and "ground truth for training set" is not explicitly available in the provided document.

The document primarily discusses software verification and validation, cybersecurity testing, and animal testing to demonstrate that the modified device is still substantially equivalent to the predicate device and performs as intended. It does not describe a clinical study measuring the performance of an AI-driven diagnostic or assistive algorithm against specific clinical endpoints or human expert performance.

Here's a breakdown of what can be gleaned from the text, and where information is missing:

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

• Acceptance Criteria: Not explicitly stated as quantifiable metrics for clinical performance (e.g., sensitivity, specificity, accuracy). The acceptance criteria mentioned are related to software verification and validation, cybersecurity, and the general demonstration that the "design output meets the design input requirements" and "the System performs effectively according to its intended use."
• Reported Device Performance: Instead of performance metrics, the document reports:
  • "The software testing results demonstrate the System meets design specifications and user needs."
  • "The cybersecurity verification and validation test results demonstrate the adequacy of the implemented cybersecurity controls."
  • "The test results demonstrate that the System performs effectively according to its intended use and does not raise different questions of safety or effectiveness."

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

• Test Set Sample Size: Not specified for any performance evaluation in terms of patient numbers or clinical cases. The "animal testing" refers to an "in-vivo animal testing" but doesn't quantify the number of animals or trials.
• Data Provenance: The animal testing is described as a "simulated animal model." There's no mention of human patient data, its origin (country), or whether it was retrospective or prospective for performance testing.

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

• Not applicable/Discussed. This document does not describe a study where ground truth was established by human experts for the purpose of validating an AI's performance.

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

• Not applicable/Discussed.

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 described. The device assists in navigation and tool placement, it is not an AI diagnostic tool that human readers would interpret assisted by AI.

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

• The device is a system that "assists the user in navigating," implying human-in-the-loop operation. No standalone algorithm performance is described. The software V&V confirms the system meets design specifications, but not in terms of standalone clinical performance metrics.

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

• Not explicitly defined in the context of clinical performance. The validation relies on "design specifications," "user needs," and "intended use" verified through software testing and animal models.

8. The sample size for the training set:

• Not applicable/Discussed. This document is about a 510(k) submission for a modified device, not the development and training of a novel AI algorithm with a training set. The device uses "System Software" and "PlanPoint™ Software" but the document doesn't detail their development or training data.

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

• Not applicable/Discussed.

In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence of a modified medical device to a previously cleared predicate device. It does so by describing software verification and validation, cybersecurity testing, and limited animal testing to show the modifications do not raise new questions of safety or effectiveness. It does not provide the type of detailed performance study data typically associated with the rigorous evaluation of a novel AI algorithm against specific clinical acceptance criteria, expert ground truth, or human performance metrics.

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