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The RT Elements are applications for radiation treatment planning for use in stereotactic, conformal, computer planned, Linac based radiation treatment of cranial, head and neck, and extracranial lesions.

The "Dose Review" application as one RT Element contains features for review of isodose lines, review of DVHs, dose comparison and dose summation.

The "Multiple Brain Mets SRS" application as one RT Element provides optimized planning and display for cranial multimetastases radiation treatment planning.

The "Adaptive Hybrid Surgery Analysis" application as one RT Element simulates an automated tadiation treatment plan. The simulated plan is intented for treatment evaluation for example in tumor board meetings or operating rooms.

The "Cranial SRS" application as one RT Element provides optimized planning and display for cranial radiation treatment planning.

The "Spine SRS" application as one RT Element provides optimized planning and display for single spine metastases.

"RT QA" is an accessory to the RT Elements and contains features for patient specific quality assurance.

Use "RT QA" to recalculate patient treatment plans on a phantom to verify that the patient treatment plan fulfills the planning requirements.

The Dose Review application as one RT Element contains features for review of isodose lines, review of DVHs, dose comparison and dose summation.

The Multiple Brain Mets SRS application as one RT Element provides optimized planning and display for cranial multi-metastases radiation treatment planning.

The Adaptive Hybrid Surgery Analysis application as one RT Element simulates an automated template-based radiation treatment plan. The simulated plan is intended for treatment evaluation for example in tumor board meetings or operating rooms.

The Cranial SRS application as one RT Element provides optimized planning and display for radiation treatment planning for single lesions in the cranium. Cranial SRS 1.0 provides single lesion planning using a Volumetric Modulated Arc Therapy (VMAT) optimization, thus allowing dose modulation with both the MLC leaf positions and the dose rate or gantry speed. It particularly offers planning for lesions in the brain which benefit from dose modulation like large tumors close to organs at risk with a complex geometry. These indications include, but are not limited to Vestibular Schwannomas, Pituitary Adenomas, Meningiomas and Gliomas. Cranial SRS 1.0 can also be used for treating vascular anomalies like arteriovenous malformations (AVMs).

The Spine SRS application as one RT Element provides optimized planning and display for single spine metastases.

RT QA is an accessory to the RT Elements and contains features for patient specific quality assurance.

Use RT QA to recalculate patient treatment plans on a phantom to verify that the patient treatment plan fulfills the planning requirements.

The provided text is a 510(k) Summary for the Brainlab RT Elements device. It describes the device, its intended use, and argues for its substantial equivalence to predicate devices. However, this document does not contain specific acceptance criteria and the detailed study results that prove the device meets these criteria in the format requested.

The document states:

• "All test reports were rated as successful according to the acceptance criteria."
• "The verification was done according to verification plans to demonstrate that the design specifications are met."
• "The validation was done according to the validation plans containing usability tests which ensure that workflows or user interface are suitable for radiotherapy treatment planning. Furthermore clinical experts evaluated the clinical suitability of radiation therapy planning using the Cranial SRS and Spine SRS workflows. The acceptance and deliverability of VMAT treatment plans was successfully validated."

This indicates that acceptance criteria and study data exist internally at Brainlab and were submitted to the FDA, but they are not detailed in this public summary. The summary focuses on comparing technological characteristics to predicate devices (K170355 Raystation 6, K142108 RT Elements, K103246 iPlan RT) to demonstrate substantial equivalence, rather than providing the performance metrics of a specific clinical study with granular acceptance criteria.

Therefore, I cannot populate the requested table and fully answer the questions as the specific details of the acceptance criteria and the study that proves them are not present in the provided text.

Here's a breakdown of what can be inferred or stated based on the text, and what cannot:

What Can Be Inferred/Stated:

• Study Type: The "Validation" section mentions "usability tests" and clinical experts evaluating "clinical suitability." This suggests a form of human-in-the-loop evaluation and verification that the software functions as intended for its radiotherapy planning purpose. It also mentions "acceptance and deliverability of VMAT treatment plans was successfully validated," implying a technical performance assessment for this specific planning type.
• Ground Truth (for calculation accuracy): For the dose calculation algorithms (Pencil Beam and Monte Carlo), it states: "The accuracy of both algorithms is tested according to IAEA-TECDOC-1540 to be better than 3%." This implies that a ground truth for dose calculation is established by the IAEA-TECDOC-1540 standard, which could involve physical measurements or highly accurate simulations.
• Experts: "Clinical experts evaluated the clinical suitability of radiation therapy planning." No number or specific qualifications are given.
• Data Provenance: Not specified, but generally, medical device validation data for such systems would involve imaging and treatment planning data, likely from various clinical cases.
• Training Set: Not mentioned, as this document describes a 510(k) for a radiation treatment planning system, not an AI/ML device that requires explicit training data. The "acceptance criteria" discussed here are more about the software's functional performance and suitability for its intended use, rather than a diagnostic AI model's precision/recall.

What Cannot Be Provided from the Text:

1. A table of acceptance criteria and the reported device performance: This detailed information is not present.
2. Sample sizes used for the test set: Not specified.
3. Country of origin of data, retrospective/prospective: Not specified.
4. Number of experts used: Not specified.
5. Qualifications of experts: Only "clinical experts" is mentioned, no specific qualifications or years of experience.
6. Adjudication method for the test set: Not specified.
7. If a multi-reader multi-case (MRMC) comparative effectiveness study was done: Not specified, nor is an effect size provided for human readers with/without AI assistance (as this is a planning system, not a diagnostic AI).
8. If a standalone (algorithm only) performance was done: The document mentions "verification" and "validation" against design specifications and usability, but doesn't detail standalone performance for AI-like metrics. The dose calculation accuracy (better than 3% to IAEA-TECDOC-1540) is a standalone algorithm performance metric.
9. The type of ground truth used (expert consensus, pathology, outcomes data, etc.) for the overarching "validation": Beyond the dose calculation accuracy, the "ground truth" for clinical suitability would likely be expert judgment and successful plan generation/deliverability.
10. The sample size for the training set: Not applicable/not provided as this is not an AI/ML training context.
11. How the ground truth for the training set was established: Not applicable.

Conclusion:

The provided 510(k) Summary serves its purpose of establishing substantial equivalence for regulatory approval. It mentions that tests were conducted per acceptance criteria but does not disclose those criteria or the detailed results of those tests. To answer your question thoroughly, one would need access to the full "verification plans," "validation plans," and "test reports" referenced in the document, which are typically proprietary and submitted directly to the FDA.

Summary Table (based on available information):

Additional Information (from text):

• Sample size for test set: Not specified.
• Data provenance: Not specified.
• Number of experts used: Not specified (only "clinical experts").
• Qualifications of experts: Not specified.
• Adjudication method: Not specified.
• MRMC comparative effectiveness study: Not specified (not applicable for this type of device).
• Standalone performance: Dose calculation accuracy is a standalone algorithm performance metric.
• Type of ground truth: IAEA-TECDOC-1540 for dose calculation accuracy. Expert judgment for suitability/usability.
• Training set sample size: Not applicable.
• Training set ground truth: Not applicable.

Ask a specific question about this device

RayStation is a software system designed for treatment planning and analysis of radiation therapy. The treatment plans provide treatment unit set-up parameters and estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by the intended user.

The system functionality can be configured based on user needs.

The intended users of RayStation shall be clinically qualified radiation therapy staff trained in using the system.

RayStation 2.5 is a treatment planning system, i.e. a software program for planning and analysis of radiation therapy plans. Typically, a treatment plan is created by importing patient images obtained from a CT scanner, defining regions of interest either manually or semi-automatically, deciding on a treatment setup and objectives, optimizing the treatment parameters, comparing rival plans to find the best compromise, computing the clinical dose distribution, approving the plan and exporting it.

The provided text describes a 510(k) submission for RayStation 2.5, a radiation treatment planning system. However, it does not contain the specific details required to complete your request for acceptance criteria and a study proving device performance.

The document states that the testing performed for RayStation 2.5 is a "further developed version of the test specification of RayStation 1.0" and that "The test results verify the requirements for dose tracking and thereby support a determination of substantial equivalence." This is a general statement about verification and validation but does not provide specific acceptance criteria, performance metrics, or study details.

Below is a breakdown of why each section of your request cannot be fully addressed based on the provided text:

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

The document states that "The test results verify the requirements for dose tracking" and lists the functionality verified:

• computing dose on CBCT
• deforming a fraction dose to the planning image given an approved deformable registration
• comparing planned dose, delivered dose and accumulated dose on planned or fraction images

However, it does not provide specific numerical acceptance criteria (e.g., dose calculation accuracy within X%, deformable registration accuracy within Y mm) nor does it report the actual device performance against any such criteria.

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

This information is not present in the provided document. The text refers to "verification performed for dose tracking" but does not specify the sample size of the test data or its origin.

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)

This information is not present in the provided document.

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

This information is not present in the provided document.

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

This information is not present in the provided document. The device is a and treatment planning system and the study mentioned is focused on verifying the dose tracking functionality, not a comparative effectiveness study with human readers assisted by AI.

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

The document mentions "verification performed for dose tracking" which implies testing the algorithm's performance for this specific function. However, details of the standalone performance (e.g., metrics, results) are not provided. The overall device is a software system for planning and analysis, where humans are always "in-the-loop" for review and approval.

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

The document mentions "verifies the requirements for dose tracking" but does not specify the type of ground truth used for this verification. For dose tracking, this would typically involve phantom measurements or highly accurate validated simulation tools, but this is not explicitly stated.

8. The sample size for the training set

This information is not present in the provided document. The document describes a "verification" of the system's functionality, not training of a machine learning model.

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

This information is not present in the provided document, as no training set is mentioned.

In summary, the provided 510(k) summary focuses on the substantial equivalence of RayStation 2.5 to its predicate devices, discussing its functionality and verification activities in general terms. It does not delve into the specific details of a performance study with acceptance criteria and results as requested.

Ask a specific question about this device