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The Elekta Neuromag® with MaxFilter 2.1 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.

Elekta Neuromag® with MaxFilter™ 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. The present device differs from the predicate device, K050035, Elekta Neuromag® with Maxwell Filter only in the following areas of functionality: Spatiotemporal interference elimination, Graphical user interface; and Offline averager. The modification also adds compatibility with internal active shielding, an interference removal method described in K081430. MaxFilter™ is intended to be used with Elekta Neuromag® MEG products in reducing measurement artifacts.

Here's a breakdown of the acceptance criteria and study information for the Elekta Neuromag® with MaxFilter 2.1, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The 510(k) summary focuses on demonstrating substantial equivalence to the predicate device, K050035. The "acceptance criteria" for the new features are primarily that they provide enhanced functionality without negatively impacting the existing performance, and for the core function of MEG measurement, the new device maintains accuracy substantially equivalent to the predicate.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not explicitly stated. The document mentions "clinical study" but does not detail the number of subjects or cases.
• Data Provenance: Not explicitly stated. Given that Elekta Oy is based in Helsinki, Finland, and the 510(k) is for the US FDA, the clinical study could involve data from various countries. The document does not specify if it was retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• This information is not provided in the summary. The "clinical study" is mentioned for measurement accuracy with non-moving heads, but details about ground truth establishment by experts for localization or diagnostic capabilities are absent. The intended use states data "may then be interpreted by trained physicians," implying expert interpretation, but doesn't specify how ground truth for the study was established.

4. Adjudication Method for the Test Set

• This information is not provided in the summary.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• A MRMC study comparing human readers with and without AI assistance is not mentioned in the summary. The study focuses on the device's technical performance and substantial equivalence.

6. Standalone (Algorithm Only) Performance Study

• A standalone performance study was implicitly done for the technical accuracy of the MaxFilter 2.1 algorithm. The document states "Performance testing consisted of software validation, phantom testing and clinical testing." The "within 2 mm accuracy of the source in a phantom" refers to the algorithm's performance in a controlled environment. However, this is not a "standalone performance" in terms of diagnostic effectiveness without human interpretation, as the device is intended for use by trained clinicians.

7. Type of Ground Truth Used

• For phantom testing: The ground truth would be the known, precisely controlled source location within the phantom, allowing for direct comparison of the device's localization output to this known truth.
• For clinical testing: The document states "provided substantially equivalent measurement accuracy in a clinical study with non-moving heads." This suggests that the ground truth for "measurement accuracy" in a clinical setting likely referred to established and accepted methods for assessing MEG signal quality and source localization, potentially compared against the predicate device's output or other established neurophysiological markers. However, specific details of how this clinical ground truth was established are not provided. It is not explicitly stated if pathology, expert consensus on clinical finding, or outcomes data were used as ground truth for clinical diagnostic performance.

8. Sample Size for the Training Set

• The document does not explicitly mention a training set or its sample size. MaxFilter 2.1 is described as a modification to an existing product (K050035) with new algorithms (tSSS). The development of these algorithms would involve theoretical work and potentially internal data sets for optimization, but these are not referred to as a "training set" in a machine learning context within this 510(k) summary.

9. How the Ground Truth for the Training Set Was Established

• As a training set is not explicitly referred to, the method for establishing its ground truth is not provided. The development of the tSSS algorithm would rely on established physics and signal processing principles for MEG data, rather than a "ground truth" derived from patient data in the way a machine learning model would.

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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

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.

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The Elekta Neuromag® with Maxwell Filter 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.

The Elekta Neuromag with Maxwell Filter adds support for separating brain signals from external disturbances and reducing mcasurements artifacts.

The provided text does not contain a study that proves the device meets specific acceptance criteria. Instead, it is a 510(k) summary for the Elekta Neuromag® with Maxwell Filter, seeking substantial equivalence to a predicate device. This document describes the device, its intended use, and indications for use, but not a clinical or performance study with defined acceptance criteria and results.

Therefore, I cannot populate the table or answer most of the questions as the requested information (performance data, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not present in the provided text.

The document focuses on demonstrating that the new device has "similar fundamental technical characteristics" to the predicate device to establish substantial equivalence.

Here's what can be extracted based on the document's content:

1. A table of acceptance criteria and the reported device performance

The provided document does not contain specific acceptance criteria or reported device performance metrics from a study. It is a 510(k) summary for substantial equivalence, not a performance study report.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not provided in the document.

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 provided in the document.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not provided in the document.

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 mentioned or described in the document. The device is a MEG system, not an AI-assisted diagnostic tool for human readers in the context of an MRMC study.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This is not applicable in the context of this device as described. The Elekta Neuromag® with Maxwell Filter is a diagnostic device that measures MEG/EEG signals to be interpreted by trained physicians. It's not an algorithm operating in a standalone capacity.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Not provided in the document.

8. The sample size for the training set

Not applicable/provided. This document is not describing a machine learning or AI algorithm with a training set.

9. How the ground truth for the training set was established

Not applicable/provided. This document is not describing a machine learning or AI algorithm with a training set.

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The Elekta Neuromag 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.

The Elekta Neuromag™ is an upgraded version of the currently available Neuromag Vectorview (K984401). The Elekta Neuromag™ does not change the intended use or the fundamental scientific technology of the Neuromag Vectorview.

The Elekta Neuromag™ integrates 306 sensor elements, including planar gradiometers and and magnetometers, with computers and data acquisition and data analysis software 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 that 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 measuring device.

The provided document is a 510(k) summary for the Elekta Neuromag™ device, which describes its substantial equivalence to a predicate device, rather than presenting a performance study against specific acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, study details, and performance metrics cannot be found in this document.

The document states that the Elekta Neuromag™ is an upgraded version of the currently available Neuromag Vectorview (K984401) and that it does not change the intended use or the fundamental scientific technology of the Neuromag Vectorview. It also asserts that the Elekta Neuromag™ is substantially equivalent to its predicate device the Omega Whole-Cortex MEG System (K030737) in safety and effectiveness.

Here's a breakdown of what can and cannot be extracted from the provided text:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. This document is a 510(k) summary focused on substantial equivalence to a predicate device, not a performance study report with specific acceptance criteria and detailed device performance metrics. The demonstration of "safety and effectiveness" for a 510(k) is typically done by showing equivalence to a legally marketed predicate device, rather than fulfilling explicit, predefined performance criteria from a new clinical study.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be provided. The document does not describe a performance study with a test set. The claim of substantial equivalence is based on the device's technical characteristics being similar to the predicate device.

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)

• Cannot be provided. No ground truth establishment is described as there is no specific performance study against a test set in this document.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Cannot be provided. No adjudication method is mentioned as there is no performance study 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

• Cannot be provided. The Elekta Neuromag™ is a magnetoencephalographic (MEG) device, not an AI-powered diagnostic tool. No MRMC study is mentioned, nor is there any AI component described.

6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done

• Cannot be provided. This is not an algorithmic device in the context of an "algorithm only" performance study. It's a medical device for measuring brain signals.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Cannot be provided. No specific ground truth is mentioned. The device's use is to help localize active areas which are "interpreted by trained physicians," suggesting that clinical interpretation and correlation with other diagnostic data form the basis of its utility, not a single, predefined "ground truth" used for a direct performance assessment in this 510(k) submission.

8. The sample size for the training set

• Cannot be provided. This document does not describe a machine learning algorithm or a training set.

9. How the ground truth for the training set was established

• Cannot be provided. As above, no training set or ground truth for it is mentioned.

Summary of Device and Equivalence:

The Elekta Neuromag™ is a magnetoencephalographic (MEG) device that measures brain signals. It is an upgraded version of a previously cleared device (Neuromag Vectorview K984401) and claims substantial equivalence to another legally marketed predicate device, the Omega Whole-Cortex MEG System (K030737). The basis for this equivalence is that the Elekta Neuromag™ does not change the intended use or fundamental scientific technology of the predicate, and its fundamental technical characteristics are similar. The document explicitly states that the device is substantially equivalent in safety and effectiveness to its predicate.

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