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IDENTIFY is indicated for adult patients undergoing radiotherapy treatment simulation and/or delivery. IDENTIFY is indicated for positioning of patients, and for monitoring patient motion including respiratory patterns. It allows for data output to radiotherapy devices to synchronize image acquisition or treatment delivery with the acquired motion information.

IDENTIFY is a system for motion monitoring during radiotherapy treatment simulation and delivery. It incorporates patient safety, quality, and workflow efficiency. Its high precision SGRT cameras support proper patient positioning and enable to monitor the patient's respiratory motion and to detect intra-fraction patient position changes during the treatment.

The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets these criteria with reported performance metrics. The document is primarily a 510(k) summary for the IDENTIFY (4.0) device, outlining its intended use, description, and non-clinical testing for substantial equivalence to a predicate device.

Therefore, I cannot fulfill all parts of your request. I can, however, extract information about what non-clinical testing was conducted, which suggests certain underlying acceptance criteria related to safety, effectiveness, and performance against standards.

Here's what can be inferred and stated based on the provided text:

Acceptance Criteria and Study Information (Based on Inferred Information from Non-Clinical Testing Section):

The document does not present a table of explicit acceptance criteria with reported device performance in the format requested. Instead, it describes general compliance with standards and internal testing to ensure safety, effectiveness, and performance.

Inferred Acceptance Criteria from Non-Clinical Testing:

While not explicitly listed as a table of "acceptance criteria," the non-clinical testing section implies the device needed to meet the following:

• Conformance to Applicable Requirements Specifications: The device must meet its defined functional and performance specifications.
• Hazard Safeguards Functioning Properly: Safety mechanisms must work as intended.
• Software Compliance: Adherence to FDA's "Content of Premarket Submissions for Device Software Functions" guidance, specifically for a "major" level of concern.
• Electrical Safety: Compliance with IEC 60601-1 standards.
• Electromagnetic Compatibility (EMC): Compliance with IEC 60601-1-2 standard.
• Quality Management System: Adherence to ISO 13485.
• Risk Management: Adherence to ISO 14971.
• No Unresolved Anomalies: No Discrepancy Reports (DRs) with "Safety Intolerable" or "Customer Intolerable" priority remaining.
• Performance at least as well as Predicate Device: The device performs comparably in terms of safety and effectiveness to the IDENTIFY (K230576).

Reported Device Performance:

The document states: "Test results showed conformance to applicable requirements specifications and assured hazard safeguards functioned properly." And "The outcome was that the product conformed to the defined user needs and intended uses and that there were no DRs (discrepancy reports/Unresolved Anomalies) remaining which had a priority of Safety Intolerable or Customer Intolerable (applicable to the US)."

Missing Information:

The document does not provide the following details that would be typically found in a clinical study report or a more detailed performance evaluation:

• A specific table of quantitative acceptance criteria and corresponding numerical performance results.
• Details on a specific "study" with a test set, sample sizes for test or training sets, data provenance, expert qualifications, or ground truth establishment methods for a clinical or performance evaluation.
• Information on MRMC studies or a human-in-the-loop effect size.
• Information on standalone algorithm performance.

Summary of Available Information from the Text:

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

   • Acceptance Criteria (Inferred): Conformance to requirements, proper functioning of hazard safeguards, compliance with specific software guidances (FDA Software Functions guidance, "major" level of concern), electrical safety (IEC 60601-1), EMC (IEC 60601-1-2), Quality Management (ISO 13485), Risk Management (ISO 14971), and absence of critical unresolved anomalies (Safety Intolerable or Customer Intolerable DRs). Performance at least as well as the predicate device.
   • Reported Device Performance: "Test results showed conformance to applicable requirements specifications and assured hazard safeguards functioned properly." "The outcome was that the product conformed to the defined user needs and intended uses and that there were no DRs (discrepancy reports/Unresolved Anomalies) remaining which had a priority of Safety Intolerable or Customer Intolerable (applicable to the US)."

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

   • Not provided. The document refers to "hardware and software verification and validation testing" but does not specify sample sizes for a test set of patient data or data provenance (e.g., country of origin, retrospective/prospective). This often implies bench testing and software verification without a dedicated clinical performance study.

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

   • Not provided. This information would be relevant for a clinical performance study using expert labels, which isn't detailed here.

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

   • Not provided.

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:

   • Not provided. The document focuses on the device's own performance and substantial equivalence, not an MRMC study with human readers.

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

   • The "Non-clinical Testing" section refers to "hardware and software verification and validation testing," implying performance of the device's functions, which would be "standalone" in nature. However, specific metrics or a dedicated "standalone study" in terms of clinical performance are not detailed. It's more about technical compliance.

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

   • Not specified as a formal ground truth for a clinical dataset. The "ground truth" for the non-clinical testing likely refers to engineering specifications, established safety standards, and validated software requirements.

8. The sample size for the training set:

   • Not provided. Training set information is relevant for AI/ML devices, but IDENTIFY is described as a "system for motion monitoring," not explicitly an AI/ML diagnostic or predictive device in the traditional sense that would require a large training dataset with labeled ground truth of patient outcomes.

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

   • Not applicable/Not provided. As above, a specific training set with associated ground truth is not detailed, as this appears to be a traditional medical device verification and validation rather than an AI/ML model for clinical decision support.

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