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PT2 Varian Proton Therapy System, provides protons for precision radiotherapy of lesions, tumors, and conditions anywhere in the body where radiation treatmont is indicated.

PT2 Varian Proton Therapy System is a proton radiation therapy system which delivers therapeutic radiation in accordance with a physician's prescription. The system consists of four major components, 1) Cyclotron required to generate the photon beam 2) Beam line - transports beam from the cyclotron to the required treatment room 3) Up to 4 radiation treatment rooms 4) Treatment Control room

The provided text is a 510(k) Premarket Notification summary for the PT2 Varian Proton Therapy System. This document, like many 510(k) submissions for medical devices, particularly for well-established technologies, does not typically contain the detailed performance study information you are requesting for an AI/ML device.

Here's why the requested information cannot be fully provided from this specific document:

• Type of Device: The PT2 Varian Proton Therapy System is a physical medical device (a proton radiation therapy system), not an AI/ML software device. For such devices, acceptance criteria and performance studies focus on mechanical accuracy, dose delivery precision, safety, and functional equivalence to a predicate device, rather than metrics like sensitivity, specificity, or reader studies common for AI/ML.
• Nature of 510(k) Submissions: 510(k)s aim to demonstrate substantial equivalence to a legally marketed predicate device. While they include summaries of verification and validation, they often do not delve into the granular details of all tests conducted, particularly not in a format relevant to AI/ML performance evaluation.
• Date of Submission: This document is from 2010, preceding the significant rise and regulatory guidance for AI/ML in medical devices.

Therefore, for your specific points:

1. A table of acceptance criteria and the reported device performance: This document states: "Results of verification and validation testing demonstrate that the PT2 Varian Proton Therapy System satisfies the intended use as described above." However, it does not provide a table with specific quantitative acceptance criteria (e.g., beam energy deviation tolerance, beam positioning accuracy tolerance) and their corresponding reported performance values. The "Technological Characteristics" table compares features with a predicate device, but these are not acceptance criteria in the sense of a performance study.

2. Sample size used for the test set and the data provenance: Not applicable. This is not a study involving patient data in the context of an AI/ML algorithm. Performance testing would have involved physical measurements and engineering validation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable for a physical proton therapy system. Ground truth typically refers to clinical diagnosis or pathology in AI/ML image analysis. Here, ground truth would be established by physical measurement standards and engineering specifications.

4. Adjudication method for the test set: Not applicable for a physical proton therapy system.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done: No. This is a framework for evaluating AI/ML impact on human interpretation, which is not relevant for a proton therapy delivery system.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. Performance testing for this device would be its ability to deliver a proton beam according to specifications, not an algorithm's diagnostic output.

7. The type of ground truth used: For a physical device like this, ground truth would be against established physics principles, engineering specifications, and validated measurement techniques (e.g., dosimetry, beam profiling). The document does not specify these in detail beyond stating "verification and validation testing."

8. The sample size for the training set: Not applicable. This is not an AI/ML algorithm that is trained on data.

9. How the ground truth for the training set was established: Not applicable.

In summary, while the document confirms that verification and validation were performed and the device meets its intended use, it does not provide the detailed performance study information requested, as it is for a physical medical device and not an AI/ML product.

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