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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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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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The Motion Tracking and Compensation Feature is an option within the indications for use of the Radixact Treatment Delivery System. The Radixact Treatment Delivery System is indicated for the delivery of radiation therapy, stereotactic radiotherapy or stereotactic radiosurgery to tumors or other targeted tissues anywhere in the body under the direction of a licensed medical practitioner.

The Motion Tracking and Compensation Feature is designed for use with the predicate Radixact Treatment Delivery System last cleared on K161146. The Motion Tracking and Compensation Feature measures tumor location and motion using images provided by a kV imaging subsystem and predicts tumor location based upon a respiration amplitude measurement device. The Radixact Treatment Delivery System then compensates for tumor motion by making real-time adjustments.

The Radixact Treatment Delivery System is a radiation therapy delivery system that provides Image Guided Radiation Therapy (IGRT) using integral megavoltage CT imaging capabilities and delivers helical (rotational) and fixed-angle (non-rotational) radiation therapy to tumors and other targeted tissues.

The provided text describes a 510(k) premarket notification for a new feature (Motion Tracking and Compensation Feature) for an existing device (Radixact Treatment Delivery System). The core of the submission is to demonstrate substantial equivalence to the predicate device, not necessarily to provide specific performance metrics against pre-defined acceptance criteria in the way one might for a diagnostic AI device.

Therefore, the response below will focus on what is available in the text regarding "acceptance criteria" (more accurately, the claims of substantial equivalence) and the "study" (the verification and validation testing) that supports these claims, rather than a typical AI performance table.

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

For a substantial equivalence submission, the "acceptance criteria" are typically demonstrating that the new device feature does not raise new questions of safety or effectiveness compared to a predicate device, and performs as well as the predicate for its intended use. The table below summarizes the claims of substantial equivalence for various characteristics.

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To provide an option to the CyberKnife System which will enable dynamic image guided stereotactic radiosurgery and precision radiotherapy of lesions, tumors and conditions that move under the influence of respiration.

Presently, irradiation of lesions that move during breathing, such as those located in the lung or near the diaphragm, would typically be performed during patient breath-holds. The Motion Tracking System option to the CyberKnife® System is designed to treat lesions while they are moving during the respiratory cycle. This offers the ability to reduce normal tissue exposure by using smaller irradiation margins, shorten treatments, increase accuracy and provide more comfort for the patient.

During motion tracking operation, a correspondence between surface (e.g. thorax/abdomen) movements and movement of the target lesion is developed prior to the start of treatment and is regularly updated during treatment each time the CyberKnife system acquires a new pair of x-ray images. This correspondence is then used to estimate lesion position in real time by monitoring surface movement during treatment.

Motion Tracking provides the CyberKnife system with the capability to monitor the patient's respiration and command the robot manipulator to compensate for the treatment target motion within the body, in real-time, while the radiation is being delivered.

The Motion Tracking System includes a sensor assembly, tracking targets, a cable junction box, and a controller.

The provided text does not contain detailed information about the acceptance criteria and the study that proves the device meets those criteria. The document is a 510(k) summary for a "Motion Tracking System", focusing on its intended use, device description, and a letter of substantial equivalence from the FDA.

Therefore, I cannot populate the table or provide the requested details about the study, sample sizes, ground truth, or expert involvement as this information is not present in the provided text.

Based on the information provided, here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

Missing Information: The document heavily focuses on the regulatory aspects and technical description of the device's function, but it does not detail specific acceptance criteria (e.g., accuracy thresholds, precision targets, latency limits) or the quantitative results of performance testing against such criteria.

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: Not specified.
• Data Provenance (e.g., country of origin of the data, retrospective or prospective): Not specified.

Missing Information: There is no mention of a test set, its size, or the nature/origin of data used for any performance evaluation.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

Missing Information: The document doesn't describe any expert-established ground truth or the involvement of experts in evaluating the device's performance.

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

• Adjudication Method: Not specified.

Missing Information: No details on adjudication methods are provided.

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 mentioned or implied.

Missing Information: The device is a "Motion Tracking System" for radiation therapy, which implies it's a technical accessory for precise delivery, not a diagnostic AI tool that would typically involve human readers. Therefore, an MRMC study comparing human reader performance with/without AI assistance would likely not be applicable or expected for this type of device.

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

• Standalone Performance: While the description implies the system operates in real-time to compensate for motion, the document does not explicitly detail a standalone performance study with specific metrics. It describes the functionality of estimating lesion position and commanding the robot, rather than reporting on a formal standalone performance evaluation.

Missing Information: Specific studies dedicated to standalone performance with quantitative results are not mentioned.

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

• Type of Ground Truth: Not specified.

Missing Information: There is no description of how ground truth was established for any performance evaluation.

8. The sample size for the training set:

• Sample Size for Training Set: Not specified.

Missing Information: No mention of a training set or its size.

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

• Ground Truth for Training Set: Not specified.

Missing Information: No details on how ground truth was established for a training set.

Summary of what is available from the text:

• Device Name: Motion Tracking System (option to the CyberKnife® System)
• Intended Use: To enable dynamic image-guided stereotactic radiosurgery and precision radiotherapy of lesions, tumors, and conditions that move under the influence of respiration.
• Mechanism: Develops a correspondence between surface movements and target lesion movement, estimates lesion position in real-time by monitoring surface movement, and commands the robot manipulator to compensate for target motion.
• Regulatory Status: Received 510(k) clearance (K020294) indicating substantial equivalence to predicate devices (Accuray CyberKnife® System, K011024 and Varian Medical Systems RPM Respiratory Gating System, K983629).

The provided text serves primarily as a regulatory submission summary, detailing the device's purpose and regulatory pathway rather than a detailed scientific study report.

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