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The PROBEAT-CR is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other conditions susceptible to treatment by radiation.

The PROBEAT-CR is a proton beam irradiation system. which provides a therapeutic proton beam for clinical treatment. It is designed to deliver a proton beam with the prescribed dose. dose distribution and directed to the prescribed patient treatment site. The PROBEAT-CR has two main subsystems: (1) equipment necessary to generate the proton beam and direct it to the beam delivery system for patient treatment, and (2) a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered. The PROBEAT-CR comprises the following components and subsystems: Beam production system (Accelerator system (LINAC. Synchrotron), Beam transport system (Low/High Energy Beam Transport systems)), Beam delivery system in 4 separate treatment rooms. Each of 3 rooms will have a rotating gantry and 1 room will have a fixed beam. (Gantry Room (Scanning Nozzle, Rotating Gantry, Patient Positioning System, Orthogonal X-ray system, Cone Beam CT), Fixed Beam Room (Patient Positioning System, Orthogonal X-ray system, Treatment Control and Safety System)). The subject PROBEAT-CR is a modification to the cleared PROBEAT-CR to include the incorporation of the previously cleared Real Time Image Gating System for Proton Beam Therapy Systems ("RGS" or "RGPT") (K171049) for tracking implanted fiducials to qate the delivery of the proton beam, and the addition of an optional patient couch top extension as an accessory to allow for different patient positioning configurations.

The provided document is a 510(k) summary for a medical device (PROBEAT-CR Proton Beam Therapy System) seeking substantial equivalence to a predicate device. It does not contain the detailed information required to answer the specific questions about acceptance criteria, clinical study design, and ground truth establishment for an AI/ML powered device.

Based on the provided text, the device is a proton beam irradiation system, and the submission is for a modification to an already cleared device. The modifications include:

1. Incorporation of a previously cleared Real Time Image Gating System (RGS or RGPT) for tracking implanted fiducials.
2. Addition of an optional patient couch top extension.

The document explicitly states: "The following testing was performed to validate the modifications to the device: Design verification and validation testing for the addition of the optional top couch extension. Software verification and validation for the updated RGS (RGPT) software."

This implies that the testing was primarily focused on engineering validation of the new components and software, rather than a clinical effectiveness study of an AI/ML algorithm's diagnostic or prognostic performance. The document doesn't mention any AI/ML components performing tasks like image analysis or disease detection/classification, which would necessitate the detailed study information requested.

Therefore, I cannot provide the requested information about acceptance criteria, study design, sample sizes, expert qualifications, or ground truth for an AI/ML device because:

• The document does not describe an AI/ML powered device with new functionality that would require such studies. The Real Time Image Gating System (RGS) is mentioned as previously cleared (K171049) and the current submission is for an "updated RGS (RGPT) software." It's likely this update pertains to changes in its existing functionality, not the introduction of new AI-driven diagnostic capabilities.
• The document does not specify acceptance criteria in the context of clinical performance metrics (e.g., sensitivity, specificity, AUC) for an AI/ML algorithm. The "performance data" section is very brief and refers to design and software verification and validation, which are typical for any medical device modification, not necessarily for an AI/ML component's effectiveness.
• No clinical study to evaluate AI/ML performance compared to human readers or standalone AI performance is described.

In summary, the provided text does not contain the detailed information necessary to answer the questions about acceptance criteria, study design, and ground truth for an AI/ML powered device. The submission focuses on device modifications and internal verification/validation, not on the clinical performance evaluation of a new AI-driven diagnostic or prognostic capability.

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The PROBEAT-CR is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other conditions susceptible to treatment by radiation.

The PROBEAT-CR is a proton beam irradiation system, which provides a therapeutic proton beam for clinical treatment. It is designed to deliver a proton beam with the prescribed dose, dose distribution and directed to the prescribed patient treatment site. The PROBEAT-CR is a modification to the cleared PROBEAT-V system, for installation at a different clinical site.

The PROBEAT-CR has two main subsystems: (1) equipment necessary to generate the proton beam and direct it to the beam delivery system for patient treatment, and (2) a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered. The PROBEAT-CR comprises the following components and subsystems:

• Beam production system
  • Accelerator system (LINAC, Synchrotron).
  • Beam transport system (Low/High Energy Beam Transport systems).
• Beam delivery system in 4 separate treatment rooms. Each of 3 rooms will have a rotating gantry and 1 room will have a fixed beam.
  • Gantry Room
    • Scanning Nozzle
    • Rotating Gantry
    • Patient Positioning System
    • Orthogonal X-ray system
    • Cone Beam CT
  • Fixed Beam Room
    • Patient Positioning System .
    • Orthogonal X-ray system .
• Treatment Control and Safety System

The provided text is a 510(k) summary for the PROBEAT-CR Proton Beam Therapy System. It describes the device, its intended use, and a comparison to predicate devices, but it does not contain information regarding software performance, acceptance criteria for an AI/algorithm, or a study that specifically proves the device meets such criteria.

The document primarily focuses on demonstrating the substantial equivalence of the PROBEAT-CR to its predicate devices (PROBEAT-V systems K151132 and K152592) in terms of hardware components, technological characteristics, and overall function as a proton beam therapy system.

The "Performance Data" section discusses:

• Mechanical performance of the rotating gantry and patient couch.
• Beam performance testing (dose shape and dose).
• Safety interface testing (beam stop control, dose monitor, area safety, mechanical interlocks).
• Electrical safety and electromagnetic compatibility (IEC 60601-1 and IEC 60601-1-2).

It states: "In all instances, the PROBEAT-CR functioned as intended and met its specifications. Testing demonstrated substantial equivalence to the predicates." However, it does not specify what those "specifications" or "acceptance criteria" were, nor does it detail the study design, sample sizes, or ground truth for any algorithmic performance evaluation.

Therefore, I cannot provide the requested information about acceptance criteria and a study proving an AI/algorithm meets those criteria based solely on the provided text. The document describes a physical medical device (proton beam therapy system), not an AI or algorithm with associated performance metrics.

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The PROBEAT-V is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other conditions susceptible to treatment by radiation.

The PROBEAT-V is a proton beam irradiation system, which provides a therapeutic proton beam for clinical treatment. It is designed to deliver a proton beam with the prescribed dose, dose distribution and directed to the prescribed patient site. The equipment to perform the above work is composed of two main components: (1) a beam delivery system properly delivered and (2) equipment necessary to generate the proton beam and direct it to the beam delivery system for patient treatment.

The beam delivery system is composed of the following components

• Gantry Room o
• . Rotating Gantry
• Scanning Nozzle .
• . Patient Positioning System
• Cone Beam CT / X-ray Imaging System .
• Fixed Beam Room o
• . Scanning Nozzle
• Patient Positioning System 트
• . Cone Beam CT / X-ray Imaging System

The beam production system is composed of the following components

• Accelerator system (LINAC, Synchrotron) o
• O Beam transport system (Low/High Energy Beam Transport systems)

The system incorporates several optional features and accessories, namely:

• The Mini Ridge Filter ("mRF") is an optional accessory to modify the beam of the o PROBEAT-V system. The mRF is installed manually and may be used in conjunction with the range shifters inside the nozzle or extended range shifter. The mRF can be added to the cleared PROBEAT-V nozzle to spread out the Bragg peak along the axis of the beam in order to reduce the amount of beam energy in the delivery of proton radiation to defined target volumes.
• Beam gating function allowing for interface with cleared external gating systems to o control the beam delivery for treatment such as to synchronize irradiation with respiration. Although the overall treatment time tends to be longer than the treatment time without gating, the extension of the treatment time will not affect irradiation performance to the target treatment site. Instead, the gating functionality may limit radiation exposure to regions outside of the target treatment volume.
• Allows for use of fluoroscopy during proton irradiation at the physician's discretion. o Fluoroscopy may be used for observation of treatment site during treatment, which could be used for interruption of the treatment or analysis for treatment planning.

The provided text describes a 510(k) premarket notification for a medical device called PROBEAT-V, a proton beam therapy system. It outlines additional optional features and the performance data for these features.

However, the document does not contain the following information typically found in a comprehensive acceptance criteria and study report:

• A table of acceptance criteria and reported device performance: While it states "All tests were successful and confirmed the performance of these additional optional features," it does not specify quantitative acceptance criteria or the numerical performance metrics.
• Sample size used for the test set and data provenance.
• Number of experts used to establish the ground truth for the test set and their qualifications.
• Adjudication method for the test set.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, or the effect size of human readers improve with AI vs without AI assistance. (This is not an AI device, so an MRMC study related to AI assistance would not be applicable here).
• If a standalone performance study (algorithm only without human-in-the-loop performance) was done. (Again, not an AI device).
• The type of ground truth used.
• The sample size for the training set. (Not an AI/machine learning device that typically requires a training set in that context).
• How the ground truth for the training set was established. (Not an AI/machine learning device).

Summary of available information regarding acceptance criteria and study:

The device's additional optional features are the Mini Ridge Filter (mRF), an external beam gating function, and the ability to use fluoroscopy during proton irradiation.

1. Acceptance Criteria and Reported Device Performance:

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

• Not specified. The document mentions "testing" but does not detail the number of tests performed or the data used.

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

• Not applicable / not specified. For a physical device like a proton therapy system, "ground truth" relates to physical measurements and engineering specifications, not expert interpretation of outputs in the same way it would for diagnostic imaging devices.

4. Adjudication method for the test set:

• Not applicable / 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. This is not an AI-assisted device, so an MRMC study for AI assistance is not relevant.

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

• Yes (for the device's functions). The "Performance Data" section describes testing conducted on the device's features (mRF, gating, fluoroscopy) to confirm their intended function. This is a standalone performance evaluation of the device itself rather than an AI algorithm.

7. The type of ground truth used:

• Physical measurements and engineering specifications. For a proton therapy system, "ground truth" would be established through calibrated instruments measuring beam properties (range, dose falloff, spot size) and system responses to ensure they meet pre-defined engineering tolerances and physical laws.

8. The sample size for the training set:

• Not applicable. This device is not an AI/machine learning system that requires a "training set" in the conventional sense. Its functionality is based on established physics and engineering.

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

• Not applicable. As above, no training set in the context of machine learning.

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The SANGRAY is an x-ray irradiation system intended for use in the irradiation of blood products packaged in transfusion bags to inactivate lymphocytes for the prevention of graft versus host disease (GVHD).

The X-ray irradiation system SANGRAY consists of a power supply (high-voltage generation unit), controller panel (console), and a shielded protection unit which contains two vertically opposed X-ray tube assemblies that generate X-ray beams. Blood products are placed into a tray and irradiated with the X-rays in a sample chamber. The system has a built-in dosimeter which measures the exposure dose in real time and ensures that the X-ray irradiation is stopped automatically when the preset dose is reached. If the power supply fails during the X-ray irradiation, the dosimeter keeps the integral dose value in memory, which allows the operator to continue the X-ray irradiation after power is recovered.

The provided text describes a 510(k) submission for the SANGRAY X-ray irradiation system. The document focuses on demonstrating substantial equivalence to predicate devices for regulatory clearance, rather than presenting a clinical study to prove the device meets specific performance criteria through a traditional clinical trial or AI algorithm validation study. Therefore, most of the requested information regarding acceptance criteria and studies proving the device meets them, especially in the context of AI, cannot be extracted from this document.

Here's what can be gathered, addressing your points where possible:

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

The document does not explicitly state acceptance criteria in the format of a clinical study or AI performance metrics. Instead, it presents a comparison of technological characteristics between the SANGRAY and two predicate devices (Rad Source X-ray Blood Irradiator, Model RS-3400 and Raycell X-ray Blood Irradiator). These characteristics serve as points of comparison to demonstrate substantial equivalence, rather than strict performance acceptance thresholds for a new, independent claim.

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 explicitly states: "6.8 Clinical Performance Test Summary: None." This indicates that no clinical performance study was conducted or presented in this submission. The "test set" in this context refers to non-clinical performance and safety tests, not a clinical data set for evaluating an AI algorithm or human reader performance. The provenance of such non-clinical test data is not detailed beyond compliance with specified safety standards.

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. As no clinical performance study was conducted, there were no experts used to establish ground truth for a clinical test set.

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

Not applicable. No clinical performance study was conducted.

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 SANGRAY is an X-ray irradiation system, not an AI-powered diagnostic or assistive tool for human readers. No MRMC study was conducted.

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

Not applicable. SANGRAY is a medical device for irradiating blood, not an AI algorithm.

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

For the non-clinical performance tests mentioned (Section 6.7), the "ground truth" would be established by physical measurements and engineering standards, comparing the device's output (e.g., dose, dose rate, leakage) against pre-defined specifications and regulatory limits. For example, radiation leakage is compared against a specified maximum (e.g., less than 1 µSv/h). There's no clinical ground truth in the sense of disease diagnosis or outcomes.

8. The sample size for the training set

Not applicable. SANGRAY is not an AI algorithm that requires a training set.

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

Not applicable. SANGRAY is not an AI algorithm.

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