(68 days)
Elekta Neuromag® with active shielding non-invasively measures the magnetoencephalographic (MEG) signals (and, optionally, electroencephalographic (EEG) signals) produced by electrically active tissue of the brain. These signals are recorded by a computerized data acquisition system, displayed and may then be interpreted by trained physicians to help localize these active areas. The locations may then be correlated with anatomical information of the brain. MEG is routinely used to identify the locations of visual, auditory, somatosensory, and motor cortex in the brain when used in conjunction with evoked response averaging devices. MEG is also used to non-invasively locate regions of epileptic activity within the brain. The localization information provided by MEG may be used, in conjunction with other diagnostic data, in neurosurgical planning.
This premarket notification represents modifications made to our current product. Internal active shielding has been added to enhance the signal to noise ratio. The internal active shielding system is a magnetic shielding technique intended to be an integrated, optional part of Elekta Neuromag® magnetoencephalograph. The internal active shielding system increases the dynamic range of the magnetometers. related external magnetic interferences, by internal feedback compensation that uses the sensor array of the biomagnetometer as a zero indicator and compensation coils placed inside the magnetically shielded room to deliver a cancellation field for attenuating the interference.
The provided 510(k) summary for the "Elekta Neuromag® with internal active shielding" does not contain the detailed information necessary to complete most of the requested fields regarding acceptance criteria and the comprehensive study design.
This submission focuses on demonstrating substantial equivalence to predicate devices (K041264 and K050035) based on modifications to an existing product (the addition of internal active shielding to enhance the signal-to-noise ratio). The "performance" section briefly states that "The results of laboratory, bench testing, clinical testing, and software validation activities show that the internal active shielding modification poses no new issues of safety or effectiveness, and is therefore substantially equivalent to our predicate devices." However, it does not elaborate on specific acceptance criteria, study methodologies, sample sizes, or ground truth establishment.
Here's a breakdown of what can be extracted and what is missing:
1. Table of acceptance criteria and the reported device performance
| Acceptance Criteria (Stated or Implied) | Reported Device Performance |
|---|---|
| Safety | No new issues of safety are identified due to the modification. |
| Effectiveness | No new issues of effectiveness are identified due to the modification. |
| Signal-to-Noise Ratio Enhancement | "Internal active shielding has been added to enhance the signal to noise ratio." (This is the primary technical modification and its intended benefit, implying an improvement over the non-shielded version, though no quantifiable metrics or targets are provided in this summary.) |
| Substantial Equivalence | The device is deemed substantially equivalent to predicate devices (K041264, K050035). |
| Dynamic Range Increase | "The internal active shielding system increases the dynamic range of the magnetometers." (Implied positive performance, but no specific values or targets given.) |
| Attenuating Interference | The system delivers a cancellation field for "attenuating the interference." (Implied effectiveness in reducing external magnetic interference.) |
2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not specified. The document mentions "clinical testing" but provides no details on participant numbers or types.
- Data Provenance: Not specified. No information about country of origin or whether the studies were retrospective or 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)
- Number of Experts & Qualifications: Not specified. The document states that MEG signals "may then be interpreted by trained physicians to help localize these active areas," but does not detail how ground truth was established for any specific test sets used to validate the device's performance.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
- Adjudication Method: Not specified.
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
- MRMC Study: Not applicable. This device is an electroencephalograph/magnetoencephalograph, not an AI-powered diagnostic tool. The submission does not discuss AI assistance or human reader improvement with AI.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance: Not applicable as this is a medical device for signal acquisition and display, not an AI algorithm. The device's output is "interpreted by a trained clinician."
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Type of Ground Truth: Not specified for any performance testing. The intended use describes that MEG helps "localize active areas" which "may then be correlated with anatomical information of the brain," and identifies "regions of epileptic activity" or "visual, auditory, somatosensory, and motor cortex." This suggests that the ground truth for localization would typically involve clinical correlation (e.g., with fMRI, intracranial EEG, surgical outcomes, or known functional areas), but the submission does not detail how this was applied in their specific "clinical testing."
8. The sample size for the training set
- Sample Size for Training Set: Not applicable. As this is not an AI/ML device, there would not be a "training set" in the conventional sense for algorithm development.
9. How the ground truth for the training set was established
- Ground Truth for Training Set: Not applicable. Same reason as above.
§ 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).