(134 days)
The RT Elements are applications for radiation treatment planning for use in stereotactic, conformal, 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 "Brain Metastases" 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 "Dose Review" application as one RT Element contains features for review of isodose lines, review of DVHs, dose comparison and dose summation.
The "Brain Metastases" 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 document provided is a 510(k) premarket notification for the "RT Elements" software, which is used for radiation treatment planning. It states that the device is substantially equivalent to a predicate device, iPlan RT (K103246). However, the document does not contain specific acceptance criteria, detailed study results, or the other requested information (sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or ground truth details). The provided text describes the general verification and validation process but lacks the quantitative data needed to answer the questions comprehensively.
Therefore, many of the requested fields cannot be filled from the provided text.
Here's a breakdown of what can and cannot be answered based on the document:
1. Table of acceptance criteria and reported device performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Not specified in the provided document. | The verification was done according to the verification plan to demonstrate that the design specifications are met. All test reports were finally rated as successful according to their acceptance criteria. |
| Not specified in the provided document. | Usability tests were performed to ensure workflows and user interface result in a useful interface. |
2. Sample size used for the test set and data provenance:
- Sample size: Not specified.
- Data provenance: Not specified (e.g., country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and their qualifications:
- Number of experts: Not specified.
- Qualifications: Not specified.
4. Adjudication method for the test set:
- Not specified.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance:
- Not specified. The document describes software for treatment planning, not an AI-assisted diagnostic tool that would typically involve human readers.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- The document implies standalone testing as part of "verification" where "design specifications are met." However, no specific performance metrics or studies are detailed. The "Adaptive Hybrid Surgery Analysis" application "simulates an automated template-based radiation treatment plan," which suggests algorithmic processing.
7. The type of ground truth used:
- Not specified. The document generically refers to "design specifications" and "verification plan" being met. For a radiation treatment planning system, ground truth would likely involve clinically validated treatment plans, phantom measurements, or expert-defined anatomical structures and dose distributions.
8. The sample size for the training set:
- Not applicable/Not specified. This is a software for treatment planning, not a machine learning model that typically undergoes a distinct "training" phase with a specific dataset in the way a diagnostic AI would. The "Adaptive Hybrid Surgery Analysis" application is template-based, not described as a deep learning model requiring a training set.
9. How the ground truth for the training set was established:
- Not applicable/Not specified, for the reasons outlined in point 8.
§ 892.5050 Medical charged-particle radiation therapy system.
(a)
Identification. A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.(b)
Classification. Class II. When intended for use as a quality control system, the film dosimetry system (film scanning system) included as an accessory to the device described in paragraph (a) of this section, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.