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The TCL3 Motion Tracking System is an accessory to a Magnetic Resonance Imaging (MRI) scanner. The system uses a markerless sensor based technology for tracking of patient movement during an MRI session. It provides the current position of the patient in real-time to the MRI scanner. The TCL3 Motion Tracking System is intended to support, supplement, and/or augment the performance of MRI scanners that have been validated for compatibility.

The TCL3 Motion Tracking System monitors the patient's head for the duration of the scan. It can be turned off between patient scans. While running, the TCL3 Motion Tracking System continuously scans the surface of the patient's head, producing high-resolution 3D surfaces consisting of thousands of individual points. A structured light technique is utilized, using the combination of a camera and an infrared light modulator to reconstruct 3D surfaces of the patient's head. Each second, 30 surfaces are created. Each of these surfaces is used for geometric alignment relative to an initial reference position obtained at the beginning of the scan. From these alignments, motion data can be calculated in real-time. The system is intended for use with performance tested scanners. The modified device includes a revised indications for use and an update to the system components and system software.

The provided text describes the regulatory clearance of the TracInnovations TCL3 Motion Tracking System (K221785) as substantially equivalent to its predicate device (K203451). However, the document does not contain the specific details required to answer all parts of your request, particularly regarding acceptance criteria tied to detailed performance metrics beyond general accuracy values, and the setup of specific clinical or comparative effectiveness studies.

The information provided indicates that the device is a Motion Tracking System accessory for MRI scanners. Its primary function is to track patient movement in real-time, specifically the head, in 6 degrees of freedom.

Here's an attempt to answer your questions based only on the provided text, highlighting what is present and what is absent:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists "Translational accuracy" and "Rotational accuracy" as technological characteristics, which can be inferred as performance metrics. The specific "acceptance criteria" are not explicitly stated as target values, but the reported performance values from the predicate device are listed as "identical" for the subject device.

Limitations: The text refers to "predetermined acceptance criteria were met" for verification and validation testing, but these criteria are not explicitly detailed with numerical thresholds beyond the above technological characteristics.

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

The document states: "Clinical data was not required for this type of device."
Therefore, there is no information provided on:

• Sample size used for a clinical test set.
• Data provenance (e.g., country of origin, retrospective/prospective).

The performance data mentioned pertains to "bench testing."

3. Number of Experts Used to Establish Ground Truth and Qualifications

Since "Clinical data was not required," there is no information provided on experts used to establish ground truth from clinical cases. The ground truth for bench testing would typically be established by calibrated instruments.

4. Adjudication Method for the Test Set

As no clinical test set requiring expert interpretation is described, there is no information provided on an adjudication method.

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

The document states: "Clinical data was not required for this type of device." Therefore, no MRMC comparative effectiveness study was performed or described in this document. The device is an accessory that feeds data to the MRI scanner, intending to "support, supplement, and/or augment" its performance, rather than an AI-assisted diagnostic tool for human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The device itself is a motion tracking system. Bench testing was performed for "tracking quality and accuracy," which represents the standalone performance of the algorithm and hardware in detecting motion.

The reported standalone performance (from the table above) for the motion tracking accuracy is:

• Translational Accuracy: 200 μm
• Rotational Accuracy: 0.2 degrees
• Recording Rate: 30 frames per second

7. Type of Ground Truth Used

For the bench testing of tracking quality and accuracy (as clinical data was not required), the ground truth would have been established using calibrated physical measurements and reference systems designed to simulate and quantify motion, rather than expert consensus, pathology, or outcomes data from human subjects.

8. Sample Size for the Training Set

The document does not provide information on the training set or its sample size. This is a 510(k) submission for a medical device accessory, not a detailed AI/ML model submission that typically requires such information. The device uses "structured light technique" and "geometric alignment" for motion tracking, implying a more traditional signal processing or computer vision approach rather than a complex trainable deep learning model in the typical sense that would have a large, specific training set.

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

As no training set details are provided, no information is available on how ground truth for a training set was established.

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