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MapRT is indicated for assisting with planning of radiation therapy by:

• Assessing which combinations of gantry/couch angle and isocentre may result in a collision and which are available to potentially enhance the dose distribution; and
• Predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures

MapRT is used by radiotherapy professionals during the CT simulation and treatment planning stages of radiotherapy for collision avoidance and facilitating dose optimisation.

MapRT uses two lateral wide-field cameras in simulation to deliver a full 3D model of patients and accessories. This model is then used to calculate a clearance map for every couch (x-axis) and gantry (y-axis) angles. Radiotherapy treatment plans can then be imported automatically to check beams, arcs, and the transition clearance.

The provided document is a 510(k) clearance letter for a software device called MapRT, which assists in radiation therapy planning by predicting collisions. However, the document explicitly states: "As with the predicate device, no clinical investigations were performed for MapRT. Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per 62366-1:2015/A1:2020. Verification and validation testing passed in all test cases."

This means the submission did not include a study design or performance data in the typical sense of a clinical trial or a multi-reader multi-case (MRMC) study to prove the device meets acceptance criteria related to clinical performance metrics like sensitivity, specificity, accuracy, or reader improvement. Instead, the clearance relies on:

1. Substantial Equivalence: The primary argument for clearance is that MapRT v1.2 is substantially equivalent to its predicate device (MapRT v1.0, K231185). The document highlights that the indications for use, functionality, technological characteristics, and intended users are the same as the predicate.
2. Verification and Validation (V&V) Testing: The document mentions that "Verification and validation testing passed in all test cases," indicating that the software meets its design specifications and functions as intended, primarily in terms of software functionality and accuracy of collision prediction within its defined operational parameters.

Given this information, it's not possible to fill out all aspects of your requested response, particularly those related to clinical studies, ground truth establishment, expert consensus, and MRMC studies, as they were explicitly not performed.

Here's an attempt to answer based on the provided document, noting where information is not available:

Device Acceptance Criteria and Study Performance for MapRT

The FDA 510(k) clearance for MapRT v1.2 is primarily based on demonstrating substantial equivalence to a legally marketed predicate device (MapRT v1.0, K231185) and successful completion of software verification and validation activities. The submission explicitly states that "no clinical investigations were performed for MapRT." Therefore, the acceptance criteria and performance proof are framed in the context of software verification and validation, and functional accuracy rather than clinical efficacy studies.

1. Acceptance Criteria and Reported Device Performance

The core functional acceptance criterion is the accuracy of collision prediction.

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

• Sample Size for Test Set: The document does not specify a "test set" in the context of patient data or clinical cases. The performance data mentioned refer to software verification and validation tests, which would involve a set of test cases designed to cover various scenarios and functional requirements. The specific number or nature of these test cases is not detailed.
• Data Provenance: Not applicable for a clinical test set, as no clinical investigations were performed. The V&V testing would likely involve simulated data, synthetic models, or potentially anonymized patient models used for testing collision detection scenarios. The provenance (country of origin, retrospective/prospective) of such test data is not provided.

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

Not applicable. Since no clinical investigations were performed, there was no clinical "ground truth" established by experts in the context of patient outcomes or image interpretation. The ground truth for functional testing of collision prediction would be derived from precise engineering specifications and physical measurements, likely validated internally by the manufacturer's engineering team.

4. Adjudication Method for the Test Set

Not applicable, as no clinical test set requiring expert adjudication was used.

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

No. The document explicitly states: "As with the predicate device, no clinical investigations were performed for MapRT." Therefore, no MRMC study was conducted to compare human reader performance with or without AI assistance.

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

Yes, in essence. The stated "accuracy of ± 2cm" for gantry clearance calculation and the passing of "all test cases" in verification and validation testing refer to the isolated performance of the MapRT algorithm in predicting collisions and calculating clearance. This implies an evaluation of the algorithm's functional accuracy independent of human interaction beyond inputting treatment plans. However, the details of how this accuracy was measured (e.g., against a gold standard derived from physical models or high-precision simulations) are not provided in this summary.

7. The Type of Ground Truth Used

For the accuracy of gantry clearance calculation (± 2cm), the ground truth would typically be established through:

• Precise engineering specifications and measurements of physical models of the treatment machine, patient, and support structures.
• High-fidelity simulation data where collision events and clearances can be precisely calculated geometrically.

It is not based on expert consensus, pathology, or outcomes data, as these are typically associated with clinical diagnostic or prognostic devices.

8. Sample Size for the Training Set

Not applicable. MapRT is a software device that simulates radiation treatment plans and predicts collisions based on geometric models and calculations. There is no indication that it is an AI/Machine Learning model that requires a "training set" of data in the conventional sense (e.g., for image classification or pattern recognition). Its "knowledge" of collision mechanics and geometries comes from programmed rules and pre-loaded models (e.g., LiDAR scans or 3D CAD models of equipment), not from learning from a dataset.

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

Not applicable, as there is no "training set" for an AI/ML model for MapRT based on the provided information.

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The AlignRT Plus system is indicated for:

• · Tracking respiratory motion throughout the simulation process to facilitate subsequent 4DCT reconstruction and coaching the patient in breathing techniques required for Deep-Inspiration Breath Hold (DIBH).
• · Verification of patient identity for their radiation treatment session.
• · Positioning and monitoring of patients during radiation delivery, relative to the setup isocenter and/or the prescribed treatment isocenter.
• · Withholding the beam automatically during radiation delivery, as well as gating the patient's respiratory motion.
• · Performing quality assurance on MV, kV imagers, room lasers, and the treatment couch.
• · Visualizing the Cherenkov signal associated with the radiation beam on entry and exit from the patient.
• · Passing and receiving information to/from other systems associated with the radiotherapy treatment.

The AlignRT Plus system (K212583) is a combination of the devices AlignRT InBore, AlignRT Offline, DoseRT, GateCT, GateRT and SimRT.

AlignRT Plus is a video-based three-dimensional (3D) surface imaging system used to monitor the patient's position in 3D before and during radiotherapy treatment. During each treatment session the patient's position is compared to the reference surface and offsets are displayed to the user. The system can be used to track pation during tumour localization in the CT scanner in order to facilitate subsequent 4D CT reconstruction. The system can be used to track the breath hold level consistency throughout the simulation process. The system can also be used to track patient motion during treatment delivery for radiation therapy procedures and hold the beam when the patient is not in position. Use of optional accessories allows the user to:

• monitor the patient's position inside bore-based linacs; and/or —
• to view the Cherenkov light emitted by the radiation beam as it enters and exits the patient's skin; and/or
• verify the patient's identity.

The system is non-invasive, does not require the use of body markers and produces no irradiation during the imaging process. The system mainly consists of advanced software. 3D cameras (≤6 cameras) and calibration tools. Each camera pod monitoring the pation will, however, project a pattern on the patient to acquire a 3D image of the patient.

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

• 1. Introduction of new software, version 7.3. This is an updated version of the existing cleared software, to support the:
  • a. New Cherenkov imaging feature, called DoseRT.
  • b. Updated respiratory gating feature, called Respiratory Module.
• 2. Introduction of new hardware:
  • a. DoseRT camera to enable Cherenkov imaging.
• 3. Update to indications for use to include the new Cherenkov imaging feature and clarify existing indications.

The provided document describes the AlignRT Plus 7.3 system, a surface-guided radiation therapy system. However, it does not contain detailed acceptance criteria and a study dedicated to proving the device meets those criteria in the format requested.

The document focuses on demonstrating substantial equivalence to a predicate device (AlignRT Plus K212583) and a reference device (BeamSite K212606) for new features, primarily Cherenkov imaging and an updated respiratory module. It mentions "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per IEC 62366-1:2015. Verification and validation testing passed in all test cases." but does not provide details of these tests, specific acceptance criteria, or the results.

Therefore, many of the requested fields cannot be filled from the provided text.

Here's a summary of the information that can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified for any of the performance claims. The document states "no clinical investigations were performed."
• Data Provenance: Not specified. It's likely internal testing data given the lack of clinical studies. Retrospective or prospective nature is not mentioned, nor is country of origin.

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

• Not specified. The document does not describe the use of experts to establish ground truth for testing.

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

• Not specified.

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:

• No MRMC comparative effectiveness study was done. The device is a patient positioning and monitoring system, not an AI-assisted diagnostic tool for human readers.

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

• The document implies that the device's technical performance characteristics (e.g., positioning accuracy, respiratory tracking) were evaluated as a standalone system against predefined specifications, as it mentions "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements." However, no specific details like algorithms, metrics, or detailed results are provided.

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

• For the positioning accuracy, the ground truth appears to be based on measurements using a "calibration phantom."
• For respiratory tracking, the ground truth for "relative respiratory position" is implied to be a measured value for comparison.
• For Cherenkov visualization, the ground truth is the actual presence and characteristics of the radiation beam.
• No expert consensus, pathology, or outcomes data is explicitly mentioned as ground truth for these technical performance tests.

8. The sample size for the training set:

• Not applicable/Not specified. The document describes a medical device system, not an AI model requiring a distinct training set in the typical sense of machine learning. The "advanced software" may incorporate algorithms, but details about training data, if any, are not present.

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

• Not applicable/Not specified (refer to point 8).

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MapRT is indicated for assisting with planning of radiation therapy by:

• Assessing which combinations of ganty/couch angle and isocentre may result in a collision and which are available to potentially enhance the dose distribution; and

• Predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures.

The MapRT module is intended for use by radiotherapy professionals during the CT simulation and treatment planning stages of radiotherapy for collision avoidance and facilitating dose optimisation.

MapRT is a system which uses advanced software and couch markers to deliver a full 3D model of the patient and accessories. This model is used to calculate a clearance map for all couch and gantry angles. Plans can be imported to check beams, arcs and transition clearance.

The provided FDA 510(k) summary for MapRT does not contain acceptance criteria or a detailed study description with the requested information. It only states that "Verification tests were performed to ensure that the module works as intended and pass/fail criteria were used to verify requirements. Validation testing was performed using summative evaluation techniques per IEC 62366-1:2015. Verification and validation testing passed in all test cases."

Therefore, I cannot provide the specific tables and details requested based on the input document. The document primarily focuses on establishing substantial equivalence to a predicate device (ClearCheck Model RADCC V2) based on technological characteristics and intended use, rather than presenting a detailed performance study with quantifiable acceptance criteria.

Information Not Found in the Document:

• A table of acceptance criteria and reported device performance.
• Sample size used for the test set and data provenance.
• Number of experts used to establish ground truth or their qualifications.
• Adjudication method for the test set.
• Whether a multi-reader multi-case (MRMC) comparative effectiveness study was done, or the effect size of human improvement with AI assistance.
• Whether standalone (algorithm only) performance was done.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.).
• The sample size for the training set.
• How the ground truth for the training set was established.

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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.

Ask a specific question about this device

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 (K193431) is a combination of the devices AlignRT, GateCT and GateRT. A special 510(K) K193431 was submitted by Vision RT Ltd. in December 2019 and this was cleared by FDA in January 2020 for the changes and improvements made in AlignRT.

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 matching 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 new optional InBore camera and a change in memory size for an existing FDA 510(k) cleared product "AlignRT Plus" (K193431).

The InBore camera is optional hardware for use with bore-based linear accelerators.

The increase in memory size from 32 to 64bit increases the system's processing speed, enabling a frame rate improvement.

The provided text is a 510(k) Premarket Notification for the AlignRT Plus device K203387, which describes modifications to an existing cleared device K193431. The document does not contain a detailed study that proves the device meets specific acceptance criteria with supporting data, an approach often seen for substantial equivalence claims where modifications are minor and performance remains unchanged from a previously cleared predicate. Instead, it relies on demonstrating that the modified device's performance and characteristics are the same as its predicate device.

Therefore, the following information is based on what is stated and what can be inferred from the provided text, primarily focusing on the comparison to the predicate device.

Acceptance Criteria and Reported Device Performance

The "Acceptance Criteria" for this submission are fundamentally defined by the performance of the predicate device (K193431). The "Reported Device Performance" for the modified device (K203387) is stated to be unchanged from that of the predicate.

Study Details (Based on provided text)

Since the document asserts that the system performance and accuracy have not changed since previous clearances, a new comprehensive performance study against acceptance criteria is not explicitly provided. The submission focuses on demonstrating substantial equivalence through a comparison of the modified device to its predicate, stating that the "changes made in subject device were test method and acceptance criteria as the predicate device and the subject device is substantially equivalent to the predication and/or validation demonstrate that the device is as safe, as effective, and performs as well as or better than the predicate device."

1. Sample size used for the test set and the data provenance: Not explicitly detailed in this document. The document states that "The system performance and accuracy have not changed since previous clearances, including with the additional optional hardware (InBore camera)." This implies that the performance characteristics were established in previous submissions (e.g., K193431) and are considered to apply to the current modified device. No new test set or data provenance is detailed for K203387 for these performance metrics.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not explicitly detailed. The ground truth for the performance metrics (positioning accuracy, respiratory tracking RMS errors) would likely have been established using physical phantoms and measurement references rather than human expert consensus for the quantitative metrics stated.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as no clinical test set requiring human adjudication for diagnostic outcomes is described for this submission. The performance metrics are technical measurements against a known reference.

4. 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: Not applicable. This device is a surface-guided radiation therapy system that primarily assists in patient positioning and monitoring, not in diagnostic interpretation by human readers. It does not involve AI in the context of improving human reader diagnostic performance.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The "System Performance and Accuracy" section indirectly refers to standalone performance:

   • "Positioning accuracy: Target registration errors (as measured using calibration phantom) < 1mm (0.5mm) for all couch angles." This is a measurement of the system's inherent accuracy using a physical phantom, which is a standalone assessment.
   • "Respiratory tracking: Tracks respiratory signal from imaged surface data... Surface displacements can be tracked with RMS errors < 0.5mm over 10 or more breathing cycles." This also describes the device's intrinsic capability to track surface displacements, tested against a measurable reference.
     The document states these performances "have not changed since previous clearances."

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For the performance characteristics mentioned, the ground truth is based on physical reference measurements using a calibration phantom. For instance, "Target registration errors (as measured using calibration phantom)" is directly specified.

7. The sample size for the training set: Not applicable based on the information provided. This device is a surface imaging and tracking system where performance is validated through precision measurements, not a machine learning model that requires a "training set" in the conventional sense for image classification or prediction tasks. The software changes mentioned are minor and related to functionality improvements (e.g., frame rate due to memory increase, new camera for bore-based linacs, user interface features), not a re-training of a core algorithmic performance.

8. How the ground truth for the training set was established: Not applicable, as there is no mention of a training set for machine learning.

Ask a specific question about this device

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.

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 noninvasive, 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 matching 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 Special 510(k) is requested only for software modification for an existing 510(k) cleared product "AlignRT Plus" (K181218). No hardware or material changes have been made since its last 510(k) clearance. The two key changes made in the existing AlignRT v6.0 software which are the subject of this Special 510(k) are listed below;

1. System Frame Rate improvement
2. Addition of Video Postural Setup Alignment feature

I am sorry, but I lack the ability to provide a response without the full context of the document. The request references information within the document that is not provided in a conversational format. If you can provide the specific details about the acceptance criteria and study, I would be happy to help describe them.

Ask a specific question about this device

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 (K123371) is a combination of the devices AlignRT, GateCT and GateRT. It 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 noninvasive, 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 matching 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.

The provided text describes the AlignRT Plus system, a video-based three-dimensional (3D) surface imaging system used for patient positioning and monitoring during radiotherapy.

Here's a breakdown of the acceptance criteria and study information:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions "Additional bench testing using improved measurement technique has been performed to substantiate improved claims" for both positioning accuracy and respiratory tracking. However, it does not specify the sample size used for the test set or the data provenance (e.g., country of origin, retrospective or prospective) for these tests. The testing appears to be conducted on a calibration phantom, not on human subjects.

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

This information is not provided in the document. The testing appears to be an objective measurement against a known physical standard (calibration phantom), rather than based on expert interpretation of medical images.

4. Adjudication method for the test set:

This information is not applicable/not provided. The performance evaluation is based on direct measurements against physical standards, not on subjective assessment by multiple reviewers.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs. without AI assistance:

A multi-reader multi-case (MRMC) comparative effectiveness study was not performed or described in this document. The AlignRT Plus is a patient positioning and monitoring system, not primarily an AI diagnostic tool for image interpretation that would involve human readers.

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

The performance metrics provided for Positioning Accuracy and Respiratory Tracking (target registration errors, RMS errors) likely represent standalone algorithm performance as measured against a physical phantom. The system's function is automated measurement and feedback.

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

The ground truth used for the performance testing appears to be objective physical measurements from a calibration phantom with known parameters (e.g., precise positions, controlled respiratory movements).

8. The sample size for the training set:

The document does not provide information on the sample size for the training set. As a vision-based system for physical tracking, much of its core functionality would be based on geometric algorithms rather than extensive machine learning training data in the traditional sense of medical image analysis. It's possible internal validation or calibration data was used, but details are not given.

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

This information is not provided in the document. Similar to the training set size, details about how any ground truth for potential internal calibration or training was established are not mentioned.

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