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The AlignRT Plus system is indicated for use to position and monitor patients relative to the prescribed treatment isocentre, and to withhold the beam automatically during radiation delivery.

For cranial treatments, a manual head adjuster is included which can be used in concert with AlignRT Plus to provide fine corrections for pitch, roll and yaw rotations.

AlignRT Plus is also used to track the patient's respiratory pattern for respiratory synchronized image acquisition, and radiation therapy treatment.

Patient contour data can be extracted and exported from the data acquired for the purpose of treatment planning.

AlignRT Plus can be calibrated directly to the treatment beam isocentre and in turn assists in performing quality assurance on MV, kV imagers, room lasers and the treatment couch.

AlignRT Plus is indicated for use during simulation, setup and stereotactic radiosurgery and precision radiotherapy for lesions, tumors and conditions anywhere in the body where radiation is indicated.

The AlignRT Plus system (K203387) is a combination of the devices AlignRT, GateCT and GateRT.

AlignRT Plus is a video-based three-dimensional (3D) surface imaging system, which is used to image the skin surface of a patient in 3D before and during radiotherapy treatment. The system consists of advanced software, a computer workstation, and one, two or three 3D camera units (each camera unit comprising a stereo pair of sensors to allow 3D surface reconstruction). The system is non-invasive, does not require the use of body markers and produces no ionizing irradiation during the imaging process.

AlignRT Plus is also able to perform both respiratory synchronised CT imaging and treatment delivery. In both instances, the system acquires a gated 3D surface model of the patient. User selected points are then tracked in real time in order to provide gating and position monitoring signals.

Real-time imaging and surface matchinq of the patient is possible during both setup and the treatment delivery to determine any patient movement. During treatment delivery, AlignRT Plus is also able to withhold the beam automatically, should the patient move outside user-defined tolerances.

Patient contour data may be extracted from surface data acquired by the system and exported for the purpose of treatment planning by radiotherapy professionals.

AlignRT Plus may be calibrated directly to the treatment beam isocentre using an optional custom designed calibration phantom and image processing software. It can analyse MV and kV digital imaging data acquired by other cleared devices. This in turn assists the user in performing quality assurance on MV, kV imagers, room lasers and the treatment couch.

The AlignRT Plus system includes the optional Head Adjuster for cranial treatments to allow for the manual, fine correction of pitch, roll and yaw in the patient's head position.

Precise isocenter calibration and the optional Head Adjuster provide improved frameless Stereotactic Radiosurgery (SRS). This is provided with the brand name "AlignRT SRS module".

The AlignRT Plus system is also provided under the brand OSMS (Optical Surface Monitoring System). This product is identical to AlignRT.

This 510(k) is requested for a modifications to FDA 510(k) cleared product "AlignRT Plus" (K203387).

This 510(k) is to obtain clearance for the following changes to the cleared device:

• Introduction of new software, SimRT 7.2. This is an updated version of the cleared software, GateCT, with a new user interface similar to the cleared AlignRT 6.2/6.3/6.4 software;
• 2. Introduction of new camera pods (hardware). These function in the same way as the currently cleared hardware but are aesthetically different and have upgraded capabilities to support future product development;
• 3. Improve the product's accuracy claim for Source-Surface Distancing (SSD) from <2.0mm to <0.2mm.

The provided text is a 510(k) Premarket Notification for the AlignRT Plus system. It details modifications to an already cleared device. The key information regarding acceptance criteria and device performance is found under the "System Performance and Accuracy" section within the "Summary of the Technological Characteristics" table.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions that the changes were tested with "test method and acceptance criteria as the predicate device," but it does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective study). The study appears to be a technical verification and validation of changes to functionality and hardware.

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

The document does not mention the use of experts to establish ground truth for the test set. The performance metrics appear to be based on physical measurements using calibration phantoms and internal system testing.

4. Adjudication Method for the Test Set:

The document does not describe an adjudication method for the test set, as the testing appears to be highly technical and objective (measurements against known standards/phantoms) rather than subjective expert review.

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

The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was done. The device is an objective measurement system for patient positioning and monitoring, not an image interpretation or diagnostic aid that would typically involve human readers. Therefore, an effect size of human readers improving with AI assistance is not applicable in this context.

6. Standalone (Algorithm Only) Performance:

The provided information focuses on the integrated system's performance, as the system consists of hardware (cameras) and software working together to deliver the stated functionalities. The performance metrics (positioning accuracy, surface displacement, SSD accuracy) inherently describe the algorithm's capability within the system context. However, it's not explicitly presented as a separate "algorithm-only" study with distinct metrics from the integrated device.

7. Type of Ground Truth Used:

The ground truth for the performance evaluations (positioning accuracy, surface displacements) appears to be based on physical measurements using a custom-designed calibration phantom. For respiratory tracking, it's based on the system's ability to track "user selected points" and real-time 3D surface models. For the improved SSD accuracy, it's also likely a technical measurement against a known standard.

8. Sample Size for the Training Set:

The document does not specify a training set sample size. The nature of the device (surface imaging and tracking) suggests it may rely on established physics and geometric principles rather than a large, data-driven machine learning model that requires explicit training sets in the same manner as a diagnostic imaging AI. The "software" updates mentioned (SimRT 7.2) are described as an updated version with a new user interface, not necessarily a re-trained AI model from a new dataset.

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

As no explicit training set or AI model requiring such a set is detailed, the document does not provide information on how ground truth for a training set was established.

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