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510(k) Data Aggregation
(141 days)
RT Elements (4.0)
The device is intended for radiation treatment planning for use in stereotactic, conformal, computer planned, Linac based radiation treatment and indicated for cranial, head and neck and extracranial lesions.
RT Elements are computed-based software applications for radiation therapy treatment planning and dose optimization for linac-based conformal radiation treatments, i.e. stereotactic radiosurgery (SRS), fractionated stereotactic radiotherapy (SRT) or stereotactic ablative radiotherapy (SABR), also known as stereotactic body radiation therapy (SBRT) for use in stereotactic, conformal, computer planned, Linac based radiation treatment of cranial, head and neck, and extracranial lesions.
The following applications are included in RT Elements 4.0:
- -Multiple Brain Mets SRS
- -Cranial SRS
- -Spine SRS
- Cranial SRS w/ Cones -
- -RT QA
- -Dose Review
- -Retreatment Review
The given FDA 510(k) summary for Brainlab AG's RT Elements 4.0 provides a general overview of the device and its equivalence to a predicate device, but it lacks specific details regarding quantitative acceptance criteria and a structured study to prove these criteria were met.
The document focuses on substantiating equivalence by comparing features and functionality with the predicate device (RT Elements 3.0 K203681). While it mentions "Software Verification," "Bench Testing," "Usability Evaluation," and "Clinical Evaluation," it does not provide the detailed results of these studies in a format that directly addresses specific acceptance criteria with reported device performance metrics.
Therefore, many of the requested fields cannot be directly extracted from the provided text.
Here's an attempt to answer the questions based on the available information:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state quantitative acceptance criteria in a table format with corresponding reported performance for the new specific features. It mentions "Dose Calculation Accuracy" as existing criteria from the predicate device that remains the same.
| Acceptance Criteria (from Predicate/Existing) | Reported Device Performance (for RT Elements 4.0) |
|---|---|
| Dose Calculation Accuracy: Pencil Beam/Monte Carlo: better than 3% | Pencil Beam/Monte Carlo: better than 3% (Stated as "the same as in the Predicate Device") |
| Dose Calculation Accuracy: Circular Cone: 1%/1mm | Circular Cone: 1%/1mm (Stated as "the same as in the Predicate Device") |
| Software requirements met | Verified through integration tests and unit tests. Incremental test strategies applied for changes with limited scope. |
| Safety and performance requirements met | Concluded from validation process. |
| Interoperability for newly added components | Interoperability tests carried out. |
| Usability for new Retreatment Review Element | Summative and Formative Usability Evaluation carried out. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document does not specify the sample size for any test sets used in the verification or validation activities. It also does not mention the data provenance (country of origin, retrospective/prospective).
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 provided in the document.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
The document does not mention any adjudication method.
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
The document does not indicate that an MRMC comparative effectiveness study was conducted. The "Clinical Evaluation" is mentioned, but no details of such a study are provided, nor is there any mention of "AI assistance" or its effect size on human readers. The new "Treatment Time Bar" feature is described as "supports the user in decision making" and "gives the user a better overview of different treatment data," but this is not framed as an AI-assisted improvement study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The document does not explicitly describe a standalone algorithm-only performance study. The focus is on the integrated software system for treatment planning.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The document does not specify the type of ground truth used for any of the evaluations. For "Dose Calculation Accuracy," the ground truth would typically be a highly accurate physical measurement or a reference dose calculation from a gold-standard system, but this is not explicitly stated.
8. The sample size for the training set
The document does not provide any details about a training set, as this is a software update and verification rather than a de novo AI model development described in typical machine learning submissions. The dose calculation models are well-established.
9. How the ground truth for the training set was established
Not applicable based on the available information (no training set mentioned).
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