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The Image Guidance System for Radiotherapy is intended to be used in combination with the radiotherapy device, for image-guided positioning verification and real-time tracking of target motion for patient radiation therapy. The Image Guidance System for Radiotherapy sends the positioning data or real-time tracking data to the radiotherapy device but does not control any part of the radiotherapy device.

The product is a medical electrical device which is composed of hardware and software, and is jointly used with the radiation therapy device. Image Guidance System for Radiotherapy is intended to be used in combination with the radiotherapy device, for image-guided positioning verification and real-time tracking of target motion for patient radiation therapy.

The provided text describes several bench tests conducted to demonstrate the substantial equivalence of the "Image Guidance System for Radiotherapy" to a predicate device. This submission does not include clinical studies.

Here's an analysis of the acceptance criteria and performance based on the non-clinical tests:

1. Table of Acceptance Criteria and Reported Device Performance

Device Name: Image Guidance System for Radiotherapy (Models: IGTS, IGPS)

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

The document does not explicitly state the specific sample sizes (number of cases/patients/phantoms) used for each individual bench test. It mentions using an "anthropomorphic target phantom" and "anthropomorphic head phantom and a thoracic spine phantom" for system accuracy tests, and a "phantom used for this test provides respiratory waveforms collected from clinical patient data" for tracking accuracy.

The data provenance is from bench testing conducted by the manufacturer, Jiangsu Rayer Medical Technology Co., Ltd., in Wuxi, Jiangsu, CHINA. The data is non-clinical.

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

Not applicable. These were non-clinical bench tests using phantoms and controlled setups, not human-annotated data with expert ground truth in the traditional sense. The "ground truth" for the tests was established by physical movements and measurements from the treatment couch or optical tracking systems during the experiments against known values.

4. Adjudication Method for the Test Set

Not applicable. As these were bench tests with physical measurements against known references (e.g., treatment couch movements, optical tracking systems), there was no need for expert adjudication of results.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study is included in this submission." The studies were bench tests demonstrating the device's performance alone and its compatibility with existing radiotherapy systems, not a comparison of human reader performance with and without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, standalone performance was assessed through various bench tests. The tests evaluate the intrinsic accuracy and performance characteristics of the "Image Guidance System for Radiotherapy" itself, in terms of positioning and tracking accuracy, mechanical accuracy, and compatibility with other radiotherapy devices. These tests do not involve human-in-the-loop performance evaluation in the context of diagnostic interpretation or decision-making.

7. The Type of Ground Truth Used

The ground truth used for these bench tests was based on:

• Physical measurements and known displacements: For positioning and tracking accuracy, the ground truth was provided by precise movements of a treatment couch acting as a reference, or known positions/displacements of inserts within phantoms.
• Optical tracking systems: For optical guided tracking accuracy, the ground truth was likely established by a highly accurate optical tracking system (e.g., NDI unit itself or a reference system) against which the device's tracking capabilities were validated.
• Design specifications and established standards: The acceptance criteria themselves are the ground truth, derived from engineering specifications and industry standards for medical devices, particularly in radiation therapy.

8. The Sample Size for the Training Set

The document does not mention a training set. This suggests that the device, or at least the specific aspects being tested for this submission, may not rely on a machine learning model that requires a distinct training dataset, or if it does, the details of the training set are not included in this summary. The tests focus on the physical and algorithmic performance of the system rather than the learning capabilities of a model.

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

Not applicable, as no training set information is provided or implied by the tests described.

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The Varian High Energy Linear Accelerator is intended to provide stereotactic radiosurgery and precision radiotherapy for lesions, tumors and conditions anywhere in the body when radiation treatment is indicated.

The Varian High Energy Linear Accelerator is indicated for stereotactic radiosurgery and precision radiotherapy for lesions, tumors and conditions anywhere in the body when radiation treatment is indicated.

The Varian High Energy Linear Accelerator models provide various selections among the features, specifications, and accessories that have been most recently cleared as Trilogy Radiotherapy Delivery System (K081188, K072916).

The 8.0 release of the C-Series control software provides additional features, safety improvements, and usability improvements.

All other features of the Varian High Energy Linear Accelerator models remain as cleared by K081188, K072916.

This document is a 510(k) summary for the Varian High Energy Linear Accelerator. It is a submission to the FDA to demonstrate substantial equivalence to a predicate device. This type of submission focuses on comparing the new device to an existing legally marketed device and typically doesn't involve clinical studies with acceptance criteria in the same way a novel device might.

Here's a breakdown of the requested information based on the provided text:

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

The provided text does not contain explicit acceptance criteria or reported device performance in the context of a clinical study. This document is a 510(k) summary, which aims to prove substantial equivalence to a predicate device (Varian Trilogy Radiotherapy System: K081188, K072916). Substantial equivalence is typically demonstrated through:

• Comparison of technological characteristics: Showing the new device has the same intended use and similar technological characteristics, or that any differences do not raise new questions of safety and effectiveness.
• Performance testing (bench, non-clinical): Demonstrating that engineering specifications and safety requirements are met. This is usually detailed in the full 510(k) submission, not typically summarized with explicit "acceptance criteria" tables in the public summary.

Therefore, since no clinical study results with acceptance criteria are presented in the provided text, this table cannot be populated as requested.

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

Not applicable. No test set for a clinical study is described. The 510(k) summary indicates that the Varian High Energy Linear Accelerator models provide various selections among features, specifications, and accessories that have been most recently cleared as the Trilogy Radiotherapy Delivery System. The 8.0 release of the C-Series control software provides additional features, safety improvements, and usability improvements. The assessment is likely based on engineering and software validation rather than a clinical efficacy study with a patient test set.

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)

Not applicable. As no clinical study with a test set is described, there's no mention of experts establishing ground truth for such a set.

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

Not applicable. No test set is described for a clinical study requiring adjudication.

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 applicable. The Varian High Energy Linear Accelerator is a medical device for radiation therapy delivery, not an AI-assisted diagnostic tool involving human readers. Therefore, an MRMC study comparing human reader performance with and without AI assistance is irrelevant to this device.

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

Not applicable. This device is a linear accelerator, a hardware system for delivering radiation therapy, not a standalone algorithm.

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

Not applicable. No ground truth collection for a clinical study is described. The "ground truth" for a device like this would likely pertain to its technical specifications, calibration accuracy, dose delivery precision, and safety mechanisms, which are verified through engineering tests and validation, not clinical ground truth in the diagnostic sense.

8. The sample size for the training set

Not applicable. As this is not an AI/machine learning diagnostic or prognostic algorithm, there is no "training set" in the context of data used to train a model. Software development and hardware testing would involve various forms of internal testing and validation, but these are not referred to as "training sets."

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

Not applicable. As there is no training set mentioned, there is no ground truth established for it in the context of this 510(k) summary.

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