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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 System is intended to support, supplement and/or augment the performance of the Siemens Magnetom Skyra, Siemens Magnetom Prisma, Philips Achieva and GE Signa Premier scanners.

The TCL3 Motion Tracking System monitors the patient's head for 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 TCL3 Motion Tracking System is an accessory to a Magnetic Resonance Imaging (MRI) scanner that uses markerless sensor-based technology to track patient movement during an MRI session. It provides the current position of the patient in real-time to the MRI scanner.

Here's an analysis based on the provided document:

1. Acceptance Criteria and Reported Device Performance

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

The document does not explicitly state a sample size for a "test set" in the context of clinical studies on human subjects. The performance evaluations described are primarily bench testing and technical verifications/validations.

The document mentions that "Clinical data was not required for this type of device." This implies that the performance data does not originate from a clinical trial with a traditional patient test set.

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

Since "Clinical data was not required" and the testing primarily involved bench tests and technical verifications, the concept of "ground truth" as established by medical experts for a diagnostic performance study does not directly apply here. Instead, ground truth would refer to established engineering specifications and measurements. The document does not specify the number or qualifications of engineers or technicians who performed the bench testing and verified the technical specifications.

4. Adjudication Method for the Test Set

Given the nature of the testing (bench testing, technical verification, and validation) and the statement that "Clinical data was not required," there was no adjudication method described for a clinical test set, as no such clinical test set was used.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

No MRMC comparative effectiveness study was done or reported. The document explicitly states, "Clinical data was not required for this type of device." Therefore, there is no information about the effect size of how much human readers improve with AI vs without AI assistance.

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

The device is described as an "accessory to a Magnetic Resonance Imaging (MRI) scanner" that "provides the current position of the patient in real-time to the MRI scanner." This implies that the device is continually active and providing data to the MRI system itself during a scan, rather than acting as a standalone diagnostic tool that a human would then interpret.

The performance data focuses on the accuracy and reliability of the motion tracking algorithm itself (e.g., translational accuracy, rotational accuracy, recording rate), as measured through bench testing. This can be interpreted as a form of standalone performance evaluation for its core function (motion tracking and data provision to the scanner), but not in the context of a diagnostic standalone performance where an algorithm generates a finding for human review.

7. The Type of Ground Truth Used

For the technical performance metrics (translational accuracy, rotational accuracy, recording rate, MR compatibility, etc.), the ground truth would have been established through calibrated measurement instruments and established engineering standards in a bench testing environment. The document implies that these were objectively measurable parameters against which the device's output was compared.

8. The Sample Size for the Training Set

The document does not mention a training set in the context of machine learning. The TCL3 Motion Tracking System uses "markerless sensor-based technology" and "structured light technique," which suggests an algorithmic approach. However, there's no information provided about any machine learning training data or its size.

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

Since no training set for machine learning is mentioned, there is no information provided on how ground truth for a training set was established.

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