(38 days)
The Varian MultiLeaf Collimator (MLC) is provided to assist the radiation oncologist in the delivery of radiation to defined target volumes while sparing surrounding normal tissue and critical organs from excess radiation. In this the MLC performs the same function as customized shadow blocks. Employing the MLC Arc Therapy feature enables movement of individual leaves of the MLC according to a pre-existing schedule while the host Clinac® linear accelerator is performing arc therapy. In this modality the beam shape created by the MLC can correspond to a beam's eye view of the treatment volume at all times while the gantry is rotating in arc therapy.
The Varian MultiLeaf Collimator (MLC) is an x-ray collimator designed to be mounted on a Varian Clinac® radiation therapy linear accelerator beneath the standard field defining collimator jaws to provide complex beam shaping supplementary to the Clinac's rectangular fields. It contains either 52 or 80 collimator leaves (26 or 40 opposed pairs of leaves), each of which can be positioned individually in order to provide an irregularly shaped treatment field that corresponds closely with the volume intended to be irradiated. With the dynamic arc therapy feature, the leaves may be continuously repositioned as a function of the Clinac gantry position during rotational irradiation (arc therapy) in order to provide dynamic conformal therapy.
This submission is a 510(k) premarket notification for a medical device submitted in 1997. At that time, the FDA's requirements for demonstrating safety and effectiveness relied heavily on substantial equivalence to predicate devices, rather than extensive clinical studies with detailed acceptance criteria and performance metrics as are common today for novel AI/ML devices. Therefore, much of the information typically requested for AI/ML device studies (e.g., sample sizes for training/test sets, expert qualifications, MRMC studies, specific performance metrics beyond functional equivalence) is not present in this document.
The document focuses on establishing substantial equivalence to existing devices and describing the device's intended use and technological considerations.
Here's an analysis based on the provided text, highlighting what can be extracted and what information is not available:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Inferred from Substantial Equivalence Basis) | Reported Device Performance (Inferred from Substantial Equivalence) |
|---|---|
| Device performs the same function as customized shadow blocks for radiation delivery. | The Varian MultiLeaf Collimator (MLC) performs the same function as customized shadow blocks. |
| The MLC with dynamic arc therapy feature enables continuous repositioning of leaves during rotational irradiation (arc therapy) according to a pre-existing schedule. | The MLC Arc Therapy feature enables movement of individual leaves of the MLC according to a pre-existing schedule while the host Clinac linear accelerator is performing arc therapy. The beam shape can correspond to a beam's eye view of the treatment volume at all times while the gantry is rotating. |
| Hardware is identical to previously cleared MLCs. | The MLC version is, from a hardware standpoint, identical to the MLCs reported in prior 510(k)'s (K926449 and K943224). |
| Software provides dynamic arc therapy capability. | The software to be provided contains the capability to provide dynamic arc therapy. |
Explanation of "Acceptance Criteria" for this 1997 510(k): For a 510(k) premarket notification, the primary "acceptance criterion" is demonstrating substantial equivalence to a predicate device already legally marketed in interstate commerce. This means the new device is as safe and effective as the predicate. The "performance" reported is primarily a description of the device's function and how it aligns with the predicate, rather than quantitative performance metrics from a formal study.
2. Sample size used for the test set and the data provenance
- Not Provided. This document does not describe a "test set" in the modern sense of a dataset used to evaluate an AI/ML algorithm. The submission is for a hardware/software device primarily relying on functional equivalence.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not Applicable/Not Provided. Ground truth establishment for a test set is not part of this type of 510(k) submission for a hardware/software device like an MLC. The "ground truth" for the device's function would be its ability to physically shape the radiation beam as intended, which is typically verified through engineering tests and quality control, not clinical expert consensus on a dataset.
4. Adjudication method for the test set
- Not Applicable/Not Provided. Adjudication methods are relevant for studies involving human interpretation or uncertain diagnoses, which is not the nature of this device's submission.
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 Applicable/Not Provided. This device is an MLC, a physical component of a radiation therapy system, not an AI/ML diagnostic or assistive tool for human interpretation. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this submission.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
- Not Applicable/Not Provided. The device itself is the "standalone" component of the radiation delivery system. The "algorithm" here refers to the software controlling the MLC. Its performance is inherent in the device's function to shape the beam according to a pre-existing schedule. No separate "standalone performance" study of an algorithm only in the context of an AI/ML device is described or implied.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not Applicable/Not Provided as a formal ground truth for a clinical study. For this device, the "ground truth" concerning its function relates to engineering specifications and physical accuracy of beam shaping. For instance, whether the leaves move to the commanded positions, and whether the resulting field shape matches the planned shape. This is typically verified through phantom measurements and quality assurance procedures rather than clinical ground truth types like pathology or outcomes data for diagnostic algorithms.
8. The sample size for the training set
- Not Provided. This document does not describe an AI/ML training set. The software for the dynamic arc therapy feature would have been developed through conventional software engineering practices, not machine learning model training.
9. How the ground truth for the training set was established
- Not Applicable. Since there's no mention of an AI/ML training set, the concept of establishing ground truth for it does not apply to this submission.
§ 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.