(72 days)
The MEGvision is intended for use as a magnetoencephalographic (MEG) device which non-invasively detects and displays biomagnetic signals produced by electrically active nerve tissue in the brain. When interpreted by a trained clinician, the data enhances the diagnostic capability by providing useful information about the location relative to brain anatomy of active nerve tissue responsible for critical brain functions.
The MEGvision integrates up to 320 dc-SQUID axial gradiometer with PCs and data acquisition software in order to measure the magnetic signals generated by the intercellular dendritic currents. These detectors positioned in a helmet shaped array give the user the ability to record the electrical activity of the entire surface of the brain cortex simultaneously without having to move the position of the sensor array.
Here's an analysis of the provided text regarding the acceptance criteria and study for the MEGvision EQ1000C Series device:
Important Note: The provided 510(k) summary focuses almost entirely on establishing substantial equivalence to predicate devices based on technological characteristics and intended use. It does not contain specific acceptance criteria for device performance (e.g., accuracy, sensitivity, specificity) derived from a clinical or analytical study, nor does it describe a study specifically designed to prove such performance criteria were met. The core of this submission is a comparison of technical specifications.
Therefore, the following information is extracted and inferred based on the document's content. Many sections will indicate that the information is "Not provided" because the document doesn't detail performance-based testing against acceptance criteria in the way a clinical performance study would.
Acceptance Criteria and Device Performance
Since the submission is primarily focused on demonstrating substantial equivalence through technological comparison, there are no explicit performance "acceptance criteria" presented in the traditional sense (e.g., a specific sensitivity or specificity threshold). Instead, the "acceptance" is implied by the similarity of the new device's technological characteristics and intended use to those of the legally marketed predicate devices.
The "reported device performance" is essentially the device's technological specifications, which are implicitly accepted as equivalent if they fall within comparable ranges or offer similar functionality to the predicates.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Implied by Predicate Comparison) | Reported Device Performance (MEGvision EQ1000C Series) |
|---|---|
| Number of SQUID detectors/channels for MEG data: Comparable to predicate devices (64-200 for CTF, 122 for Neuromag). | 64 to 320 (Higher range than predicates but includes predicate ranges) |
| Operating Principle: Superconducting flux transformer coupled with dc-SQUID. | Superconducting flux transformer coupled with dc-SQUID driven by digitally controlled analog flux locked loop circuit (Similar to CTF's digital flux-locked loop and Neuromag's analog flux-locked loop) |
| Number of auxiliary channels for other types of data: Comparable to predicate devices (88 for CTF, 166 for Neuromag). | 166 (Matches Neuromag, higher than CTF) |
| Gradiometer Type: Similar to predicate devices (axial first order for CTF, orthogonal planar first order for Neuromag). | 1 axial first order gradiometer per location (Matches CTF Systems) |
| Intersensor Spacing: Comparable to predicate devices (32 mm for CTF, 43-44 mm for Neuromag). | 20mm to 25mm (160 sensor configuration) (Provides denser coverage than predicates) |
| Gradiometer Placement: Locations distributed across a helmet-shaped lower tip of a dewar for entire head coverage. | 64 to 320 location distributed across the helmet shaped lower tip of a dewar (Similar principle to predicates) |
| Cryogen Used: Liquid helium. | Liquid helium (Matches predicates) |
| Coverage: One acquisition to cover the entire head. | One acquisition to cover entire head (Matches predicates) |
| Gantry Type: Floor mounted. | Floor mounted fixed gantry. (Similar to predicates, but predicates offer tilting options) |
| Patient Position: Lying on back or seated. | Lying on back (More restricted than predicates, which offer seated/supine options) |
| Head Position Indicator: Included. | Included (Matches predicates) |
| Computer System: A computer system capable of processing MEG data. | Personal Computer with Windows (Differs from predicates' HP workstation with UNIX, but implies equivalent processing capability) |
| Networking Capabilities: Ethernet connections. | Ethernet connections to other network system available (Matches predicates) |
| Magnetically Shielded Room Accessories: Basic amenities for patient monitoring (lights, camera, intercom). | Interior DC lights, video camera and two-way intercom for patients (Similar to predicates) |
| Intended Use: Non-invasively detects and displays biomagnetic signals from electrically active nerve tissue in the brain, interpreted by clinicians for localization relative to brain anatomy, enhancing diagnostic capability. | The MEGvision is intended for use as a magnetoencephalographic (MEG) device which non-invasively detects and displays biomagnetic signals produced by electrically active nerve tissue in the brain. When interpreted by a trained clinician, the data enhances the diagnostic capability by providing useful information about the location relative to brain anatomy of active nerve tissue responsible for critical brain functions. (Identical wording to both predicate devices) |
Study Details:
As noted, the provided 510(k) summary does not describe a performance effectiveness study as might be expected for an AI or imaging diagnostic device. The basis for substantial equivalence is primarily a technological comparison to predicate devices, where the MEGvision EQ1000C Series demonstrates comparable or superior technological characteristics for the same intended use.
Here's a breakdown of the specific points based on the available text:
2. Sample size used for the test set and the data provenance
- Not provided. The document describes the technological characteristics of the device and compares them to predicate devices. It does not mention a specific test set of patient data or any clinical studies to evaluate performance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable / Not provided. Since no specific test set or clinical study is described for performance evaluation, there is no mention of experts or ground truth establishment in this context. The intended use states the data is to be "interpreted by trained clinicians," implying human experts will always be in the loop.
4. Adjudication method for the test set
- Not applicable / Not provided. No test set or performance evaluation study is described.
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
- No, a MRMC comparative effectiveness study was not done based on this document. This device is a direct measurement instrument (MEG device), not an AI-assisted diagnostic tool that would typically involve improving human reader performance. The document focuses on the device's technical specifications.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable / No. The device is a measurement system; it's explicitly stated that the data should be "interpreted by a trained clinician." There's no AI algorithm that operates standalone described in this document.
7. The type of ground truth used
- Not provided. As there's no described performance study, there's no mention of the type of ground truth used. The device's output is intended to provide "information about the location relative to brain anatomy of active nerve tissue," which would historically be correlated with other clinical findings, electrophysiology, or anatomical imaging.
8. The sample size for the training set
- Not provided. This device is hardware for signal acquisition; it does not involve a training set as a machine learning model would.
9. How the ground truth for the training set was established
- Not applicable. No training set is involved for this type of device.
In summary, this 510(k) submission establishes substantial equivalence primarily through a detailed comparison of the new device's technical specifications and intended use against those of legally marketed predicate MEG devices. It does not contain information about a clinical performance study with acceptance criteria, test sets, or ground truth establishment, which would typically be seen for devices that perform an analytical or diagnostic function independent of human interpretation or that incorporate AI/machine learning.
§ 882.1400 Electroencephalograph.
(a)
Identification. An electroencephalograph is a device used to measure and record the electrical activity of the patient's brain obtained by placing two or more electrodes on the head.(b)
Classification. Class II (performance standards).