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The CyberKnife® Robotic Radiosurgery System is intended to provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions and conditions anywhere in the body when radiation treatment is indicated.

The CyberKnife Robotic Radiosurgery System is a computer controlled medical system for planning and performing minimally invasive stereotactic radiosurgery and precision radiotherapy using a treatment radiation generator, linear accelerator, manipulator (robot), and a target locating subsystem to accurately deliver radiation to the treatment target. The CyberKnife System uses skull tracking, fiducial tracking, Xsight™ Spine Tracking, Xsight" Lung Tracking, and Synchrony" Respiratory Tracking for dynamic positioning and pointing of the linear accelerator.

This 510(k) summary (K091146) from Accuray Incorporated for the CyberKnife® Robotic Radiosurgery System does not contain the detailed acceptance criteria and study information typically found in a clinical performance study. The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a new clinical study.

Therefore, for almost all of your requested information, the answer is that the document does not provide this information.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Response: This information is not provided in the 510(k) summary. 510(k) submissions for substantial equivalence often rely on technical comparison and predicate device performance rather than new clinical trials with acceptance criteria.

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

• Response: This information is not provided. No specific test set or data provenance from a study proving performance against acceptance criteria is mentioned.

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)

• Response: This information is not provided. No test set requiring expert-established ground truth is described.

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

• Response: This information is not provided. There is no mention of a test set or adjudication process.

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

• Response: This information is not provided, and such a study would not typically be applicable to a robotic radiosurgery system like the CyberKnife, which is a treatment delivery device rather than an AI-assisted diagnostic tool for human readers.

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

• Response: This information is not provided. The CyberKnife is a system performing treatment delivery, not a standalone algorithm in the sense of an AI diagnostic tool. Its performance is inherent to its mechanical and software precision.

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

• Response: This information is not provided. If any "ground truth" were relevant, it would likely relate to the accuracy of radiation dose delivery and patient positioning, which are engineering and physics measurements, not typically clinical "ground truth" as you'd find in diagnostic imaging.

8. The sample size for the training set

• Response: This information is not provided. As this is not a machine learning diagnostic device, the concept of a "training set" for an algorithm in this context is not directly applicable in the way it would be for an AI-driven image analysis tool. The CyberKnife uses advanced algorithms for tracking and radiation delivery, but these are typically developed through engineering and physics principles rather than statistical training on a large dataset of "cases."

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

• Response: This information is not provided, as a training set in the typical AI sense is not described.

Summary of the CyberKnife System as per the 510(k) Summary:

• Trade Name: CyberKnife® Robotic Radiosurgery System
• Device Description: Computer-controlled medical system for planning and performing minimally invasive stereotactic radiosurgery and precision radiotherapy. It uses a linear accelerator, manipulator (robot), and a target locating subsystem (including skull tracking, fiducial tracking, Xsight™ Spine Tracking, Xsight™ Lung Tracking, and Synchrony™ Respiratory Tracking) to accurately deliver radiation.
• Intended Use: To provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions, and conditions anywhere in the body when radiation treatment is indicated.
• Substantial Equivalence: The document states the device is substantially equivalent to a predicate device, with the same or equivalent intended use, principles of operation, technological characteristics, and labeling. This implies that the safety and effectiveness are established by comparison to an already cleared device, rather than through a new, detailed clinical performance study with acceptance criteria.

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The CyberKnife® Robotic Radiosurgery System is intended to provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions and conditions anywhere in the body when radiation treatment is indicated.

The CyberKnife Robotic Radiosurgery System is a computer controlled medical system for planning and performing stereotactic radiosurgery and precision radiotherapy using a linear accelerator, manipulator (robot), and a target locating subsystem to accurately deliver radiation to the treatment target. The CyberKnife System uses skull tracking, fiducial tracking, Xsight™ Spine Tracking, Xsight™ Lung Tracking, and Synchrony™ Respiratory Tracking for dynamic positioning and pointing of the linear accelerator.

1. Acceptance Criteria and Reported Device Performance

The provided 510(k) summary (K071531) for the CyberKnife® Robotic Radiosurgery System does not explicitly list specific acceptance criteria or quantitative performance metrics within the document itself. Instead, it states that the device is "substantially equivalent" to a predicate device, implying that its performance is implicitly accepted as meeting the same standards as the predicate.

The summary highlights the system's capabilities, which implicitly define its expected performance:

• Intended Use: "to provide treatment planning and image-guided stereotactic radiosurgery and precision radiotherapy for tumors, lesions and conditions anywhere in the body when radiation treatment is indicated."
• Key Technological Features for Performance: "The CyberKnife System uses skull tracking, fiducial tracking, Xsight™ Spine Tracking, Xsight™ Lung Tracking, and Synchrony™ Respiratory Tracking for dynamic positioning and pointing of the linear accelerator."

Therefore, based on the provided document, a table of explicit acceptance criteria and corresponding reported device performance cannot be generated. The acceptance is based on substantial equivalence to a predicate device, meaning its performance characteristics are presumed to be comparable.

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

The provided 510(k) summary does not contain information regarding a specific test set, its sample size, or its data provenance (e.g., country of origin, retrospective/prospective). This document focuses on the general description of the device and its intended use, and the declaration of substantial equivalence. Typically, detailed study information, including test set specifics, would be found in the full 510(k) submission, not necessarily in the publicly available summary.

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

The provided 510(k) summary does not mention any clinical studies involving expert observers to establish ground truth for a test set. As such, the number and qualifications of experts are not specified.

4. Adjudication Method for the Test Set

Since no specific test set or clinical study involving ground truth establishment by experts is detailed in the provided summary, there is no information about any adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided 510(k) summary does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study, nor does it discuss human reader improvement with or without AI assistance. The CyberKnife system is a robotic radiosurgery system, not an AI-assisted diagnostic or interpretation tool for human readers in the traditional sense of MRMC studies. Its "AI" functionality, if any, would be embedded in its autonomous tracking and positioning capabilities.

6. Standalone Performance Study

The 510(k) summary does not detail a standalone performance study in terms of specific quantitative outcomes. The declaration of "substantial equivalence" implies that the device's standalone performance is comparable to an existing, legally marketed predicate device. The functional description of its tracking capabilities (skull tracking, fiducial tracking, Xsight™ Spine Tracking, Xsight™ Lung Tracking, and Synchrony™ Respiratory Tracking) highlights the system's autonomous operation to achieve precise radiation delivery.

7. Type of Ground Truth Used

The provided 510(k) summary does not specify the type of ground truth used for performance validation. Given that it is a radiosurgery system, the "ground truth" for its accuracy and efficacy would typically involve phantoms and/or clinical outcomes data, rather than expert consensus on diagnostic images or pathology. However, this level of detail is not present in the summary.

8. Sample Size for the Training Set

The provided 510(k) summary does not mention any training set or its sample size. The description indicates a mature, computer-controlled medical system, suggesting engineering and validation processes rather than a machine learning model that requires a "training set" in the common sense of AI development.

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

Since no training set is mentioned, there is no information on how its ground truth was established.

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