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The Leo Cancer Care Patient Positioning Subsystem is indicated for precise positioning of human patients to facilitate delivery of external beam radiation when integrated with a separate beam therapy treatment delivery device.

The Leo Cancer Care (LCC) Patient Positioning Subsystem (EVE) is designed to deliver precise positioning of a patient when combined with an external Beam Therapy device, to provide the intended treatment therapy prescribed for patients requiring radiation treatments.

The Patient Positioning System has 6 degrees of freedom to provide full alignment capability for a patient treatment session, with the patient being located in an upright position. The Eve Patient Positioning Subsystem is held in a static position for the duration of the external Beam Therapy System radiation exposure. After the beam delivery has been completed, the patient positiong subsystem is then aligned to the next patient position required by the treatment system and the process repeated for the required series of different beam placements to achieve the full prescribed treatment delivery for the patient.

The provided text is an FDA 510(k) summary for the "Leo Cancer Care Eve Patient Positioner System." It describes a medical device used for patient positioning in radiation therapy.

However, this document DOES NOT describe an AI/ML powered device, nor does it contain information about acceptance criteria or a study that proves a device meets acceptance criteria related to AI/ML performance.

Instead, the document outlines the substantial equivalence of the Eve Patient Positioner System to a predicate device (LEONI Orion System K160518) based on non-clinical performance testing for device functionality and safety. The document states:

• "No animal or clinical tests were performed to establish substantial equivalence with the predicate device." Therefore, there's no clinical study involving human readers or expert consensus for ground truth as would be relevant for an AI/ML device.
• The performance testing focuses on mechanical and electrical performance (e.g., accuracy of positioning, speed, patient load, motion axes, and compliance with general medical device and software life-cycle standards like ISO 14971, IEC 60601-1, IEC 62304).

Therefore, it is impossible to extract the requested information regarding AI/ML acceptance criteria, study details, human reader performance, or ground truth establishment relevant to an AI/ML algorithm from this document.

If you have a document describing an AI/ML powered medical device, please provide that.

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The Z-Robot™ Patient Positioning System is an electro-mechanical robotic arm for patient positioning in radiotherapy and medical imaging. It is designed for positioning a patient with a high degree of accuracy and repeatability.

The Z-Robot™ Patient Positioning System (hereinafter referred to as Z-Robot™) is an electro-mechanical robotic arm with the motion capability in six degrees of freedom. These axes allow the couch to be precisely positioned translationally and rotationally within the specified movement limits. Therefore, Z-Robot™ could be used to accurately position patient in radiotherapy and medical imaging.

The requested information is contained within the provided text. The device in question is the "Z-Robot™ Patient Positioning System", which is an electro-mechanical robotic arm for patient positioning in radiotherapy and medical imaging. The acceptance criteria and the study that proves the device meets these criteria are primarily based on non-clinical testing.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly provide a "table of acceptance criteria and reported device performance" for all tests. However, it lists the performance parameters tested and indicates that "All test results were acceptable per the acceptance criteria detailed in the corresponding protocol and test report." It also provides a direct comparison to the predicate device for several key performance metrics, implying these are the relevant acceptance criteria for substantial equivalence.

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The patient positioning system is a SCARA designed to position a patient for medical procedures prescribed by oncologists and others that require a high degree of accuracy and repeatability.

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This document is a 510(k) premarket notification decision letter from the FDA for a device called "Patient Positioning System" by Forte Automation Systems, Inc. It does not contain information about acceptance criteria, device performance, study details, or ground truth establishment.

Therefore, I cannot provide a response to your request, as the necessary information is not present in the provided text.

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The LEONI Orion System in an electro-mechanical robotic arm for patient positioning in radiotherapy and medical imaging. It is designed for positioning a patient with a high degree of accuracy and repeatability.

The LEONI ORION System is an electro-mechanical robotic arm capable of motion in six degrees of freedom. The purpose of the device is to position a patient during radiotherapy, radiology and other medical applications with a high degree of accuracy and repeatability.
The LEONI ORION System consists of the electro-mechanical unit that is a 6 axes robot which supports a standard radiotherapy table couch or other approved patient support device, and a Control Unit that includes computers and application software. The robot is linked to the Control Unit by cables.

The provided text is a 510(k) summary for the LEONI ORION System, an electro-mechanical robotic arm for patient positioning in radiotherapy and medical imaging. It focuses on demonstrating substantial equivalence to a predicate device, rather than a clinical study evaluating diagnostic performance. Therefore, many of the requested items related to AI device evaluation (like MRMC studies, ground truth establishment for training data, and expert qualifications) are not applicable or cannot be extracted from this document.

Here's an analysis based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

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The Protura Couch Software is intended to interface between record and verify systems, linear accelerator (Linac) software systems, Linac safeguard systems, and/or image guidance systems and the Protura Couch. The Protura Couch Software is also capable of operating the Protura Couch (6 Degree Axis Couch).

The proposed device, the Protura Couch Software 1.3.0 (Part No. MT6XSM1.3.0), is patient positioning software used in radiation treatments in conjunction with an Image Guided Radiation Therapy (IGRT) system. The Protura Couch Software interfaces with the Couch Hardware (K031866) and is intended to position the patient after diagnostic decisions have been made based on results from an IGRT system. The Protura Couch Software allows the user to control patient positioning with six degrees of freedom from outside of the treatment room. The Protura Couch Software also includes the ability to interface with record and verify systems, Linac software systems, Linac safeguard systems, and/or image guidance systems.

The provided document is a 510(k) summary for the Protura Couch Software 1.3.0, a patient positioning software used in radiation treatments. It states that non-clinical performance testing was conducted, but no clinical testing was performed. Therefore, it does not contain the specific information required to complete a table of acceptance criteria and reported device performance based on a study, nor does it provide details about patient data, expert reviews, or comparative effectiveness studies.

However, based on the information provided, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

The document lists "Non-Clinical Performance Data" areas tested and states "All testing confirmed that the Protura Couch Software 1.3.0 is safe and effective for its intended use." However, it does not provide specific acceptance criteria (e.g., numerical thresholds, error limits) or quantitative results of the device's performance against such criteria.

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

• Sample Size: Not applicable. No clinical testing with patient data was performed. The testing described is non-clinical performance testing of the software and hardware interfaces.
• Data Provenance: Not applicable, as no patient data was used.

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

• Number of Experts: Not applicable. No clinical testing or expert review of patient data was conducted.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. No clinical testing or expert review requiring adjudication was conducted.

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

• MRMC Study: No. The document explicitly states: "No clinical testing was performed in the evaluation of this medical device." Therefore, no MRMC study, human reader improvement analysis, or AI assistance effect size was reported.

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

• Standalone Performance: The non-clinical performance testing focused on the device's functionality, interfacing, and mechanical aspects. While this could be considered a form of "standalone" testing for the software's operational characteristics, it's not in the context of diagnostic or interpretive performance where "standalone" typically refers to an AI algorithm's accuracy in analysis without human input. The document describes testing of the software's technical operation (e.g., couch movement, interfacing), not its interpretation of data.

7. The Type of Ground Truth Used:

• Ground Truth: For the non-clinical performance tests, the "ground truth" would have been established by engineering specifications, calibration standards, and expected operational parameters for the couch movement, interface communication, and alignment accuracy. For example, for "Movement of the Protura Couch," the ground truth would be the programmed movement patterns and expected physical responses of the couch hardware. For "Couch Pedestal and Isocenter Alignment," it would be the precise physical alignment specifications.

8. The Sample Size for the Training Set:

• Sample Size: Not applicable. This device is software that controls a medical device (a radiation therapy couch). It is not an AI/ML algorithm that requires a training set in the typical sense (i.e., for learning from data to perform a diagnostic or predictive task). The software is programmed based on engineering principles and specifications, not trained on a dataset of patient cases.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" in the context of an AI/ML algorithm for this device. The software functions based on its coded logic and interface protocols, not on learned patterns from a dataset.

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The patient positioning system is a SCARA designed robotic arm designed to position a patient for medical procedures prescribed by oncologists and others that require a high degree of accuracy and repeatability.

The patient positioning system is a SCARA designed robotic arm allowing six degrees of freedom.

The provided 510(k) summary for the Forte Automation Systems Patient Positioning System (K122413) does not contain information about acceptance criteria and a study proving the device meets those criteria in the context of clinical performance or diagnostic accuracy.

This 510(k) pertains to a patient positioning system, which is a robotic arm for positioning patients during medical procedures. The submission focuses on non-clinical testing to demonstrate substantial equivalence to a predicate device. Clinical efficacy or diagnostic performance, which would typically involve acceptance criteria related to accuracy, sensitivity, specificity, and a clinical study to prove them, are not applicable to this type of device submission.

Here's a breakdown of the available information based on your requested points, highlighting why some are not present for this specific device:

1. Table of Acceptance Criteria and Reported Device Performance

It's crucial to understand that these are engineering/safety performance criteria, not clinical performance criteria in the context of diagnostic devices. The document states, "The submitted device does not impart energies into a patient. Therefore no clinical testing was needed." This confirms that the 510(k) submission relies on non-clinical engineering and safety performance to demonstrate substantial equivalence.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. The tests conducted were non-clinical engineering tests (e.g., electromagnetic compatibility, vibration, speed, accuracy, collision detection) on the device itself, not on a patient population. There is no "test set" of patient data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. Ground truth, in the context of clinical or diagnostic performance, is established by experts (e.g., radiologists, pathologists). Since no clinical testing was performed and no patient data was analyzed, this information is not relevant to this 510(k) submission.

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

Not applicable. Adjudication methods are used to resolve discrepancies in expert interpretations of clinical or diagnostic data. This was not part of the non-clinical testing performed.

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

Not applicable. MRMC studies are used to assess the clinical effectiveness of diagnostic devices and often involve human readers interpreting medical images. This device is a patient positioning system, not an imaging or diagnostic device with AI assistance.

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

Not applicable. Standalone performance refers to the diagnostic accuracy of an algorithm without human intervention. This is not a diagnostic algorithm. The "performance" discussed for this device relates to its mechanical and electrical functions.

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

For the non-clinical tests, the "ground truth" was established by engineering specifications, industry standards, and the physical properties of the device. For example, the accuracy tests would compare the device's measured positioning to its programmed target position, with "ground truth" being the theoretically correct position based on the design.

8. The sample size for the training set

Not applicable. This device is not an AI/ML algorithm that requires a "training set" for model development.

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

Not applicable, as there is no training set for this device.

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The Protura Couch Software is interface between a record and verify system, linear accelerator (Linac) software, Linac safeguard systems, and/or image guidance systems and the Protura Couch. The Protura Couch Software is also capable of operating the Protura Couch (6 Degree Axis Couch).

The proposed device, the Protura Couch Software (MT6XSMEU), is patient positioning software used in radiation treatments in conjunction with an Image Guided Radiation Therapy (IGRT) system. The Protura Couch Software interfaces with the Protura Couch Hardware (K031866) and is intended to position the patient after diagnostic decisions have been made based on results from an IGRT system. The Protura Couch Software allows the user to control patient positioning with six degrees of freedom from outside of the treatment room. The Protura Couch Software also includes the ability to interface with a record and verify system, Linac software, Linac safeguard systems, and/or image guidance systems.

The provided text describes a 510(k) summary for the Protura Couch Software (device name: MT6XSMEU) by MED-TEC, Inc. d/b/a CIVCO Medical Solutions. This software is designed for patient positioning in radiation therapy.

Here's an analysis of the acceptance criteria and study information, based solely on the provided document:

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

The document does not explicitly state quantitative acceptance criteria in a table format. Instead, it describes performance testing conducted. The reported device performance is that "All testing confirmed that the Protura Couch Software is safe and effective for its intended use" and that it is "substantially equivalent to the predicate device in regards to safety, effectiveness, and performance."

The characteristics tested include:

• Movement of the Protura Couch
• Interfacing with External Systems
• Couch Pedestal and Isocenter Alignment
• Patient Record Handling

Without specific numerical targets for these characteristics, a precise table of acceptance criteria and reported performance cannot be generated. The document indicates these tests were performed and passed.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

The document does not specify a sample size for the test set. It mentions "non-clinical performance testing" but does not detail the number of test cases, simulated patients, or data points used. Data provenance is also not mentioned, as no clinical data or data from human subjects was used for testing.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not applicable and hence not provided. As the testing was "non-clinical" and involved evaluating software functionality and interface, there was no need for experts to establish ground truth in the context of medical image interpretation or patient outcomes.

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

This information is not applicable and hence not provided. The non-clinical performance data described does not involve expert adjudication as it pertains to software functionality and system interfaces, not diagnostic or prognostic outcomes requiring consensus.

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 study was performed or is mentioned. The device is software for controlling a radiation therapy couch, not an AI for image interpretation or diagnosis that would typically be evaluated with human readers.

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

Yes, based on the description, the performance testing appears to be a standalone evaluation of the software's functionality and its ability to interface with other systems and control the couch. The "non-clinical performance data" section describes testing conducted on the software itself and its interactions, without human-in-the-loop performance being a primary evaluation point for its safety and effectiveness.

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

The concept of "ground truth" as typically applied in AI/clinical studies (e.g., expert consensus for diagnosis, pathological findings) is not relevant here. For this device (software controlling a medical couch), the "ground truth" would be the expected functional behavior and precise physical movements of the couch, as defined by engineering specifications and safety standards. The testing verified that the software met these operational specifications.

8. The sample size for the training set

This information is not applicable and not provided. The Protura Couch Software is described as an interface and control system, programmed in C#. It is not an AI/machine learning model that typically requires a distinct "training set" in the sense of labeled data for learning.

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

This information is not applicable and not provided, for the same reasons as in point 8.

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The Qfix Radiotherapy Chair is designed as a support and fixation device for patients undergoing radiotherapy treatment(s). Its design includes multiple adjustments on the device to accommodate patients of varying sizes.

It is designed to interface with a robotic multi-axis arm by way of standard (off the shelf) robotic tooling changers. It incorporates the use of a kVue IGRT couchtop insert (K060671 The device includes a Ofix One Touch™ mechanism for kVue Couchtop Insert insertion and for the ability to use other inserts for various treatment and fixation styles.

The Qfix Radiotherapy Chair will also be able to accommodate the use of the Qfix Accubite TM hite block stabilization system along with an array of WFR/Aquaplast masks (K935067) to assist in the fixation of the pationt during said treatment(s).

The Qfix Radiotherapy Chair is designed as a support and fixation device for patients undergoing radiotherapy treatment(s). Its design includes multiple adjustments on the device to accommodate patients of varying sizes.

It is designed to interface with a robotic multi-axis arm by way of standard (off the shelf) robotic tooling changers. It incorporates the use of a kVue IGRT couchtop insert (K060671 The device includes a Ofix One Touch™ mechanism for kVue Couchtop Insert insertion and for the ability to use other inserts for various treatment and fixation styles.

The Qfix Radiotherapy Chair will also be able to accommodate the use of the Qfix Accubite TM hite block stabilization system along with an array of WFR/Aquaplast masks (K935067) to assist in the fixation of the pationt during said treatment(s).

The provided document is an FDA 510(k) clearance letter for the "Qfix Radiotherapy Chair". It does not contain information about the acceptance criteria and study proving device performance as typically expected for software or AI/ML devices. This document is a regulatory approval for a physical medical device, not a software algorithm.

Therefore, I cannot answer your specific questions about acceptance criteria, sample sizes, ground truth establishment, or human-in-the-loop performance, as this information is not present in the provided text. The document primarily focuses on FDA's determination of substantial equivalence for a physical radiotherapy support and fixation device.

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The intended use of the device is to support and aid in positioning a patient during radiation therapy.

The HexaPOD evo consists of two platforms, which are connected by six length adjustable elements which are powered. By appropriate coordinative adjustment of these elements, the system is able to move the upper platform relative to the lower one. The movement can occur in all three dimensions in space. Additionally the upper platform can rotate around these three axes which results in a tilt or a rotation of the upper platform relative to the lower one. Finally an accurate positioning within all six degrees of freedom (6DOF) can be provided. The HexaPOD consists of a controller unit which is directed by a cable connected hand control. Additionally it can be directed via an external graphics user interface (GUI) which is installed on a PC.

The provided text is a 510(k) summary for the HexaPOD™ evo RT Couch Top, which is a powered radiation therapy patient support assembly. It describes the device, its intended use, and its substantial equivalence to a predicate device.

However, the document explicitly states: "No performance data is required for this Class II device nor requested by the Food and Drug Administration (Office of Device Evaluation)."

Therefore, I cannot provide a table of acceptance criteria and reported device performance or information about a study proving the device meets acceptance criteria, as such data was not required or provided in this 510(k) submission.

Here's a breakdown of why the specific questions cannot be answered based on the input:

• 1. A table of acceptance criteria and the reported device performance: Not applicable. The document states no performance data was required or requested.
• 2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable. No performance data or testing on a test set was mentioned.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience): Not applicable. No performance data or ground truth establishment was mentioned.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. No performance data or adjudication was mentioned.
• 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: Not applicable. The device is a physical patient support assembly, not an AI or imaging interpretation device. MRMC studies are not relevant.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a physical patient support assembly, not an algorithm.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. No performance data or ground truth establishment was mentioned.
• 8. The sample size for the training set: Not applicable. As no performance data from a study was required, there's no mention of a training set.
• 9. How the ground truth for the training set was established: Not applicable. No training set or ground truth establishment was mentioned.

In summary, the 510(k) submission for the HexaPOD™ evo RT Couch Top focuses on its substantial equivalence to a predicate device due to minor hardware changes, and explicitly states that no performance data was required or requested.

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The intended use of the device is to support and aid in positioning a patient during radiation therapy.

The HexaPOD consists of two platforms, which are connected by six linear, rigid but length adjustable elements which are powered. By appropriate coordinative adjustment of these elements, the system is able to move the upper platform relative to the lower one. The movement can occur in all three dimensions in space. Additionally the upper platform can rotate around these three axes which results in a tilt or a rotation of the upper platform relative to the lower one. Finally an accurate positioning within all six degrees of freedom (6DOF) can be provided. The HexaPOD consists of a controller unit which is directed by a cable connected hand control. Additionally it can be directed via an external graphics user interface (GUI) which is installed on a PC.

Here's a breakdown of the acceptance criteria and study information for the HexaPOD RT Couch Top device, based on the provided document:

Acceptance Criteria and Device Performance

Important Note: The document explicitly states: "No performance data is required for this Class II device nor requested by the Food and Drug Administration (Office of Device Evaluation)." Therefore, detailed quantitative performance metrics or specific studies demonstrating device acceptance criteria are not provided in this document. The acceptance is based on demonstrating substantial equivalence to a predicate device, and the modifications being benign in terms of safety and effectiveness.

Study Information

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

   • Not Applicable. The document states that "No performance data is required..." and therefore no specific test set data is presented. The submission relies on demonstrating substantial equivalence to a predicate device.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

   • Not Applicable. As no specific performance studies or test sets were mandated or performed for this submission, there's no mention of experts establishing ground truth for a test set.

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

   • Not Applicable. No test set or independent performance study was conducted or presented.

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 mechanical patient support system, not an AI-assisted diagnostic or therapeutic tool. Therefore, MRMC studies or AI assistance are not relevant.

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

   • Not Applicable. This device is a mechanical patient support system, not an algorithm.

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

   • Not Applicable. Since no performance data or test sets were required or presented, no specific ground truth was established for the device itself in this submission. The "ground truth" for its acceptance is its demonstrated substantial equivalence to the predicate device, which implies the predicate device's performance characteristics are the standard.

7. The sample size for the training set

   • Not Applicable. This device is a mechanical patient support system, not an AI or machine learning model that would require a training set.

8. How the ground truth for the training set was established

   • Not Applicable. No training set was used.

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