(107 days)
The Neuromag-122 system is intended for use as a magneto encephalographic (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.
This device integrates 122 SQUID planar gradiometers with medical super-computers and data intracelly long in order to measure the differences in the magnetic signals generated by the intracellular dendritic currents. These detectors are positioned in a helmet shaped array which gives the user the ability to record the electrical activity of the entire surface of the brain simultaneously without having to move the position of the probe.
The provided document is a 510(k) summary for the Neuromag-122 device, establishing its substantial equivalence to a predicate device (Biomagnetic Technologies Magnes Single, K901215A), rather than demonstrating direct evidence of meeting specific acceptance criteria through a clinical study. Therefore, a direct response to some of the questions, such as detailed acceptance criteria and a study proving they are met, cannot be fully provided from the given text.
However, based on the information provided, here's what can be extracted and inferred:
1. Table of acceptance criteria and the reported device performance
The document does not define explicit "acceptance criteria" in the format of specific thresholds for performance metrics. Instead, it argues for "substantial equivalence" based on comparative parameters between the Neuromag-122 and the predicate device. The implicit acceptance criterion is that the Neuromag-122 performs at least as well as, or is sufficiently similar in its technical characteristics and intended use to, the predicate device to be considered safe and effective.
| Parameter | Neuromag-122 Performance | Predicate Device (Magnes Single) Performance |
|---|---|---|
| No. of SQUID detectors / channels for MEG data | 122 | 37 |
| No. of auxiliary channels for other types of data (e.g EEG) | 166 (typically use 32 for EEG) | 51 |
| Gradiometer | Two orthogonal planar-first-order gradiometers per location | First order axial gradiometer |
| Intersensor spacing | 43-44 mm | 20 mm |
| Gradiometer placement | Sixty-one locations distributed across helmet-shaped lower tip of dewar. Radius of curvature of helmet is 83 mm (front-portion) and 91 mm (back-portion). | Positioned in a circular array (diameter 14.4 cm) over a concave spherical surface with a 12.2 cm radius of curvature. |
| Cryogen Used | Liquid Helium | Liquid Helium |
| Coverage | One acquisition to cover entire head | Six to ten acquisitions to cover entire head. |
| Gantry | Floor mounted, standard gantry tilts up to 30°. Optional gantry tilts to 45°. | Suspended from ceiling, gantry can tilt up to 45°. |
| Patient Position | Seated or Supine. Optional chair insert for children. | Seated or Lying on back or side. |
| Head Position Indicator | Available | Available |
| Computer | Hewlett Packard workstation with UNIX environment. | SUN workstation with the UNIX environment |
| Networking Capabilities | Ethernet connections to other workstations available | Ethernet connections to other workstations available |
| Magnetic Shielded Room Accessories | Video monitor and two-way intercom for monitoring patients. | Interior DC lights, video cameras, and two-way intercom for monitoring patients |
| Intended Use | Non-invasively detects and displays biomagnetic signals produced by electrically active nerve tissue in the brain. Data enhances diagnostic capability by providing useful information about the location relative to brain anatomy of active nerve tissue responsible for critical brain functions. | Non-invasively detects small biomagnetic signals produced by the brain and provides information about the location of electrically active nerve tissue responsible for producing these signals. Data presented to physicians in an MEG image from which they may draw information about the location of critical brain functions relevant to brain anatomy. |
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 describe a test set or clinical study with a specific sample size. The substantial equivalence argument relies on comparing the technical specifications and intended use of the Neuromag-122 to a legally marketed predicate device. No patient data, therefore, is mentioned for any "test set".
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)
Not applicable. As noted above, no clinical "test set" and corresponding ground truth establishment are described in this document. The "ground truth" for the device's function is the established performance and safety of the predicate device.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. No clinical test set or adjudication method 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
Not applicable. This document is for a medical device (MEG system) and not an AI or imaging diagnostic software that would typically undergo an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. The Neuromag-122 is a hardware system for detecting biomagnetic signals, not a standalone algorithm. Its intended use explicitly states that the data needs to be "interpreted by a trained clinician."
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The document implicitly uses the established safety and effectiveness of the predicate device (Biomagnetic Technologies Magnes Single, K901215A) as its "ground truth" or standard for comparison. The regulatory review for substantial equivalence primarily relies on a comparison of technological characteristics, intended use, and existing performance data of the predicate device.
8. The sample size for the training set
Not applicable. This document does not describe a machine learning algorithm that would require a training set.
9. How the ground truth for the training set was established
Not applicable. As above, no training set or its ground truth establishment is mentioned.
§ 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).