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The Neural Navigator is a neuronavigation system indicated for accurate positioning of the treatment coil of the CloudTMS Therapy System with respect to target brain regions based on data obtained from MRI measurements. Specifically, the Neural Navigator is indicated for use with the following CloudTMS Therapy System coils manufactured by Neurosoft Ltd: AFEC-02-100 and AFEC-02-100-C.

The Neural Navigator combines MRI-based, 3-D localization of cortical motor areas of the brain with non-invasive TMS and simultaneous EMG measurement to locate areas of the brain that are capable of evoking muscle responses when stimulated, and to locate the target area for depression therapy. The Neural Navigator software is used to import a patient's MR image slices through standard DICOM communication protocols, and automatically generates an accurate 3-D model of the patient's head, and a custom automatic tissue segmentation routine to reveal anatomical structures of the brain surface in 3D.

The provided text describes the 510(k) premarket notification for the Neural Navigator device. While it asserts substantial equivalence based on performance testing, it does not explicitly define "acceptance criteria" in a quantitative table with specific thresholds as would be typical for a detailed study report. However, it implicitly presents performance metrics and their comparison to predicate devices, which serve as the basis for acceptance.

Here's an attempt to extract and rephrase the information to fit the requested format, acknowledging the limitations of the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not present explicit acceptance criteria with defined pass/fail thresholds. Instead, it compares the Neural Navigator's performance to its predicate devices, implying that performance comparable to or better than the predicate is considered acceptable.

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

• Clinical Study for Coil Compatibility Validation and System Accuracy: 10 healthy volunteers.
• Data Provenance: The document does not specify the country of origin for the clinical study data or if it was retrospective or prospective. Given it is a 510(k) submission, it is likely prospective testing specifically for this submission.
• Monte Carlo Simulations: 10,000 runs for both mapping algorithm and ensuing navigation. The provenance for this is computational simulation.

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

The document does not explicitly state the number of experts used or their specific qualifications for establishing ground truth. The clinical study involved "MEP mapping," which typically involves expert neurophysiology interpretation. However, details on the adjudicators or their qualifications are not provided.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for the clinical test set. The ground truth seems to be implicitly derived from the MEP mapping procedure itself, which is a physiological measurement, rather than subjective interpretation requiring multiple readings.

5. Was a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Done?

No, an MRMC comparative effectiveness study with human readers assisting AI versus without AI assistance was not performed or reported. This device is a neuronavigation system for coil placement, not an AI-assisted diagnostic imaging tool where such a study would typically be conducted. The study is focused on the accuracy of the navigation system itself.

6. Was a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Done?

Yes, the document reports on elements of standalone performance:

• Tracking System Accuracy: Tested independently by NDI (the tracking system manufacturer).
• System Accuracy (simulations): 10,000 Monte Carlo simulations were run, representing an algorithm-only evaluation of accuracy under various noise conditions.
• Clinical Study: While it involves humans (volunteers), the focus is on the accuracy of the device's navigation in placing the TMS coil, which is a direct measure of the algorithm's performance in guiding coil placement, rather than human interpretation aided by the algorithm. The "human-in-the-loop" is the operator using the device, but the performance metric is the device's ability to accurately guide.

7. The Type of Ground Truth Used

• System Accuracy (Clinical Study): The ground truth for the clinical study measuring system accuracy via MEP mapping is based on a physiological response (Motor Evoked Potentials - MEPs). The assumption is that successful MEPs indicate accurate targeting of the motor cortex.
• Tracking System Accuracy: Ground truth is established by the independent testing of the tracking system by its manufacturer, likely using known spatial measurements.
• System Accuracy (Simulations): Ground truth is an ideal or expected outcome defined within the simulation model.

8. The Sample Size for the Training Set

The document does not provide any information regarding a training set size or methodology. This type of device, which is based on established physics and medical imaging principles (e.g., MRI-based 3D localization, tissue segmentation), may not involve a "training set" in the sense of a machine learning model where data is used to optimize algorithms. The algorithms are likely engineered based on physiological and anatomical models.

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

As no "training set" is mentioned for a machine learning context, the method for establishing its ground truth is not applicable or described in the provided text. The foundational principles and calibrations for the device's operations (e.g., MRI space to patient space registration, calibrated electric field maximum) are inherent to its design and validated through the performance tests mentioned above.

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