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The PROBEAT-FR 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-FR 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-FR 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 performance data presented in the 510(k) summary focuses on demonstrating that the PROBEAT-FR functions as intended and meets its specifications for various aspects, thus establishing substantial equivalence to its predicate device, the PROBEAT-CR.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, 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 provided text does not specify a sample size for a test set in the context of patients or cases. The performance data described refers to engineering and system-level testing rather than clinical trials with patient data.

• Sample Size: Not applicable in the context of clinical patient data for this submission. The tests performed are on the device itself and its components.
• Data Provenance: Not applicable in the context of clinical patient data. The tests are system-level and engineering evaluations.

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

The provided text does not mention the use of expert radiologists or other medical professionals to establish ground truth for a test set in the context of a diagnostic or therapeutic performance evaluation involving medical images or patient outcomes. The testing described is focused on the technical performance and safety of the proton beam therapy system.

4. Adjudication Method for the Test Set

Since there is no mention of a test set involving human interpretation or decision-making on patient data, an adjudication method (like 2+1 or 3+1) is not applicable to the described performance tests.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not mentioned in the provided text. The submission focuses on demonstrating substantial equivalence based on the technical performance and safety of the device's features, not on improved human reader performance with AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

The provided text does not describe a standalone algorithm-only performance study. The device is a proton beam therapy system, not an AI-driven diagnostic or image analysis algorithm that would typically undergo such a study. While it contains "Real Time Image Gating System software" and a "Positioning Image Analysis System (PIAS)," the performance testing described is at the total system level, not specifically isolating the performance of these software components as standalone algorithms.

7. Type of Ground Truth Used

The "ground truth" for the tests described is based on the engineering specifications and design requirements of the PROBEBEAT-FR system, as well as compliance with relevant international standards (e.g., IEC 60601-1, IEC 60601-1-2). For instance:

• For mechanical performance, "ground truth" would be the specified movement ranges, precision, and stability.
• For beam performance, "ground truth" would be the specified dose accuracy, beam shape, and energy.
• For safety interlocks, "ground truth" would be the successful triggering of safety mechanisms under defined conditions.

8. Sample Size for the Training Set

The provided text does not mention a training set size. This type of information would typically be relevant for machine learning or AI-driven devices that learn from data. The PROBEAT-FR is a hardware-intensive proton beam therapy system with integrated control software, not an AI model that undergoes a "training set" in the conventional sense.

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

Since there is no mention of a "training set" for an AI or machine learning model, the method for establishing its ground truth is not applicable.

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The Small Field Applicator is an accessory to the PROBEAT-V system that is intended to assist the radiation oncologist in the delivery of proton radiation to defined target volumes while sparing surrounding normal tissue and critical organs from excess radiation.

Small Field Applicator is an optional accessory to the proton beam therapy system which can be added to the nozzle configuration of the cleared PROBEAT-V system to make the lateral penumbra sharp, as needed. The Small Field Applicator may be used in place of the optional removable Applicator having an aperture (collimator) that has been cleared as part of the PROBEAT-V system.

The Small Field Applicator is composed of a cylinder part with touch sensors, a 4-legged table, and a plate part. The Small Field Applicator is inserted at the end of the nozzle to obtain a sharp lateral penumbra in the lateral dose distribution, and it can reduce the dose to the surrounding normal tissue than the case in which the Small Field Applicator is not used.

The provided FDA 510(k) summary for the "Small Field Applicator" does not contain the information requested regarding acceptance criteria, study details, and ground truth establishment typically found in AI/ML device submissions.

This document describes a physical accessory for a radiation therapy system, not a software-based AI/ML device that requires extensive performance studies against clinical ground truth. The "Performance Data" section briefly mentions mechanical testing, interface evaluation, dose distribution, end-to-end testing, and radiation safety, but these are engineering and physics validations for a physical medical device, not a performance study for an AI algorithm as typically requested in your prompt.

Therefore, I cannot extract the requested information points from this document. The prompt asks for details pertinent to an AI/ML device "study that proves the device meets the acceptance criteria," which is not applicable to this physical accessory.

If you have a different document describing an AI/ML device, please provide that, and I will be happy to attempt to answer your questions.

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The Real Time Image Gating System for Proton Beam Therapy Systems is intended for use with compatible Hitachi proton beam therapy systems and is designed to generate gating signals to deliver a proton beam when the position of a fiducial marker, which is implanted near a tumor and tracked by use of X-ray fluoroscopy, is within a given tolerance from its planned position.

The Real-time Image Gating System for proton beam therapy (RGS) is a gating signal generator accessory to proton beam therapy systems (PBTS) and used to track an implanted fiducial and to control the proton beam. The RGS is installed on the PBTS workstation and receives information from the PBTS imaging systems, processes the images, and sends timing signals to the PBTS irradiation controller. This RGS system recognizes the position of a fiducial marker in the human body at a regular frame rate using the X-ray imaging systems. The marker is implanted near the tumor using image guided implantation. Using two diagnostic X-ray sources and two X-ray FPDs configured around the treatment isocenter, the imaging data are combined to obtain precise 3D trajectories in the RGS. The RGS tracks the implanted marker on the image, and this chosen marker's position viewed in 3 dimensions. Using X-ray fluoroscopy devices in two distinct planes, the location of marker on the fluoroscopic image is automatically extracted using the pattern recognition technology of the RGS and the spatial position of the marker is calculated and monitored throughout the treatment. Synchronized irradiation of the tumor with gating control occurs only when the marker is within a given tolerance from its planned coordinates relative to the beam isocenter. This synchronized irradiation is performed at high speed which enables accurate irradiation of a tumor whose position may move inside the body, e.g., due to respiration.

The provided text describes a 510(k) premarket notification for a Medical Device, the "Real Time Image Gating System for Proton Beam Therapy Systems." While the document outlines performance tests conducted, it does not provide detailed acceptance criteria or the specific results of these tests in a quantitative manner that would allow for a complete table of acceptance criteria and reported performance.

The document primarily focuses on establishing substantial equivalence to predicate devices based on intended use, technological characteristics, and general safety/effectiveness. It lists the types of performance tests performed but lacks the specific metrics (e.g., "accuracy > 95%") and the outcome of those metrics.

Therefore, for aspects requested in the prompt that are not explicitly present in the provided text (e.g., exact acceptance criteria values, specific performance metrics, sample sizes for test/training sets, detailed ground truth establishment for training, number of experts, adjudication methods, MRMC study details), the answer will state that the information is not provided in the source document.

Here is a summary of the information available and what is missing based on your request:

Overview of Device Performance and Equivalence Study

The Real Time Image Gating System for Proton Beam Therapy Systems is designed to generate gating signals to deliver a proton beam when the position of an implanted fiducial marker (tracked by X-ray fluoroscopy) is within a given tolerance from its planned position. The system uses pattern recognition technology to automatically extract the marker's location and calculates its spatial position in 3D throughout treatment.

The performance data presented in the 510(k) summary aims to establish substantial equivalence to predicate devices (MedCom GmbH's Verisuite and Elekta Ltd.'s XVI R5.0). The study was conducted by Hitachi, Ltd. Healthcare.

1. Table of Acceptance Criteria and Reported Device Performance

As stated above, the document does not explicitly list quantitative acceptance criteria or specific reported device performance values for the tests conducted. It only lists the types of tests performed.

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

• Sample Size for Test Set: The document does not specify the sample size used for any of the performance tests (e.g., number of images, number of instances of fiducial tracking, or number of patients/phantoms).
• Data Provenance (e.g., country of origin, retrospective/prospective): The document does not explicitly state the country of origin for the data used in the performance tests. The submitter is Hitachi Ltd. Healthcare in Japan. It also does not specify if the data was retrospective or prospective.

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

The document does not specify if human experts were involved in establishing ground truth for the performance tests, nor does it mention the number or qualifications of any such experts. The system uses "pattern recognition technology" to automatically extract marker positions.

4. Adjudication Method for the Test Set

As there is no mention of human expert involvement in ground truth establishment for the test set, an adjudication method (e.g., 2+1, 3+1) is not applicable or not described in the provided text.

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

An MRMC study was not conducted or described in this 510(k) submission. The performance tests appear to be focused on the device's technical specifications and functionality, not a comparison of human reader performance with and without AI assistance. Therefore, an effect size of human reader improvement with AI assistance cannot be determined from this document.

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

The performance tests described (Recognition accuracy of a static fiducial marker, System latency, Tracking of moving marker, etc.) appear to be standalone assessments of the device's technical capabilities, without human intervention as part of the primary performance evaluation. The device is described as an "accessory" that processes images and sends timing signals automatically.

7. The Type of Ground Truth Used

The document implies that the ground truth for "recognition accuracy of a static fiducial marker" and "tracking of moving marker" would be based on the known, controlled, or planned positions of the fiducial markers (e.g., in a phantom or controlled experimental setup). It does not mention expert consensus, pathology, or outcomes data as sources for ground truth in these specific performance tests. The system itself "recognizes the position" and "tracks the implanted marker," suggesting a comparison against a known physical position.

8. The Sample Size for the Training Set

The document does not provide any information regarding a training set or its sample size. This type of detail is typically not required for a 510(k) submission focused on substantial equivalence where the device's core technology (pattern recognition) is presumed to be developed prior to the specific product's submission.

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

Since no information about a training set is provided, how its ground truth was established is also not described in the document.

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ARIETTA Prologue is intended for use by trained personnel (doctor, sonographer, etc.) for the diagnostic ultrasound evaluation of following clinical applications: FETAL; ABDOMINAL - (Includes imaging for guidance of percutaneous biopsy of abdominal organs and structures (including amniocentesis)); INTRA-OPERATIVE (SPEC.)-(Includes imaging of organs and structures exposed during surgery (excluding neurosurgery and laparoscopic procedures)); INTRA-OPERATIVE (NEURO); LAPAROSCOPIC; PEDIATRIC; SMALL ORGAN (SPEC.)-(Includes thyroid, parathyroid, breast, scrotum, penis and imaging for guidance of biopsy): NEONATAL CEPHALIC: ADULT CEPHALIC; TRANS-RECTAL - (Includes imaging for guidance of trans-rectal biopsy); TRANS-VAGIAL -(Includes imaging for guidance of trans-vaginal biopsy); TRANS-ESOPHAGEAL (NON-CARDIAC & CARDIAC) -ADULT/PEDIATRIC; MUSCULOSKELETAL (CONVENT./SUPERFIC.); Other (spec.) -WOUND (Includes imaging for Cavernous/Non-Cavernous wounds); Other (spec) - GYNECOLOGICAL; CARDIAC: ADULT/ PEDIATRIC and PERIPHERAL VESSEL.

An ultrasound diagnostic system with the following features:

• Ultrasound transducer(s) to generate the transmitted ultrasound energy and detect the reflected echoes
• Ultrasound transducer accessories (standard and optional) to maximize functional usage of transducer(s) in various modes of operation
• A computer system to control the transducer and analyze the signals resulting from the reflected echoes
• A video monitor with optional image recorder to display the computed image or derived Doppler data

The provided text is a 510(k) Premarket Notification for the ARIETTA Prologue Diagnostic Ultrasound System and Transducers. It focuses on demonstrating substantial equivalence to a predicate device (Noblus K142368, and K134016 for some indications) and does not contain detailed information about specific performance acceptance criteria or a dedicated study proving performance against such criteria in the way a clinical trial for an AI/CADe device would.

Instead, the document asserts substantial equivalence based on similarities in intended use, clinical applications, modes of operation, technology, and adherence to safety standards. The "study that proves the device meets the acceptance criteria" in this context refers to the non-clinical testing performed to ensure the device is safe and effective as per FDA regulations for ultrasound devices, rather than a clinical performance study with specific quantifiable metrics.

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

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

The document does not specify quantitative performance acceptance criteria (e.g., sensitivity, specificity, accuracy) for an AI/CADe component, as it is a diagnostic ultrasound system, not an AI/CADe device with specific diagnostic algorithms being validated. The acceptance criteria described are broadly related to safety and effectiveness compared to a predicate device.

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 describe a test set or data provenance in the context of a performance study for an AI/CADe device. The evaluations conducted were non-clinical tests (acoustic output, biocompatibility, EMC, electrical/mechanical safety) which typically involve testing the physical device and its components according to engineering standards, rather than analyzing clinical 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, as this is not a study for an AI/CADe device requiring expert-established ground truth from clinical data. The "ground truth" for the non-clinical tests would be the established engineering standards and specifications.

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

Not applicable. No clinical data test set or adjudication method is 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 document describes a diagnostic ultrasound system, not an AI-assisted diagnostic tool subject to MRMC studies comparing human readers with and without AI assistance.

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

Not applicable. This is a diagnostic ultrasound system, not a standalone algorithm.

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

For the non-clinical testing, the "ground truth" would be engineering specifications, applicable safety standards (e.g., IEC 60601-1, IEC 62304, ISO 10993-1), and FDA guidance documents. There is no mention of clinical ground truth (like pathology or outcomes data) being used for performance evaluation in this 510(k) submission.

8. The sample size for the training set

Not applicable. This is not an AI/CADe device, and no training set for an algorithm is mentioned.

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

Not applicable, as there is no training set mentioned for an AI/CADe algorithm.

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ALOKA LISENDO 880 is intended for use by trained personnel (doctor, sonographer, etc.) for the diagnostic ultrasound evaluation of Fetal, Abdominal, Pediatric, Small Organ (Spec.), Intra-operative (Spec.), Neonatal Cephalic, Musculo-skel. (Convent./Superfic.), Peripheral vessel, Cardiac Adult, Cardiac Pediatric, Trans-esophageal (card), Adult Cephalic clinical applications.

The Modes of Operation are B mode, PW mode (Pulsed Wave Doppler), CW mode (Continuous Wave Doppler), Color Doppler, Power Doppler (Color Flow Angiography), TDI (Tissue Doppler Imaging), 3D Imaging, 4D Imaging.

An ultrasound diagnostic system with the following features:

• Ultrasound transducer(s) to generate the transmitted ultrasound energy and detect the reflected echoes
• Ultrasound transducer accessories (standard and optional) to maximize functional usage of transducer(s) in various modes of operation
• A computer system - to control the transducer and analyze the signals resulting from the reflected echoes
• A video monitor with optional image recorder to display the computed image or derived Doppler data

The provided text is a 510(k) Pre-Market Notification for the ALOKA LISENDO 880 ultrasound system. It outlines the device's indications for use and compares it to a predicate device (ARIETTA 70, K134016) to establish substantial equivalence.

Here's an analysis of the acceptance criteria and supporting studies as presented in the document:

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

The document does not provide a table with specific, quantitative acceptance criteria (e.g., minimum sensitivity or specificity values, specific performance metrics) and corresponding reported performance metrics for the ALOKA LISENDO 880. Instead, it relies on a qualitative comparison to a predicate device.

The "Comparison to predicate device" section (Page 20) implicitly defines the acceptance criterion as being "substantially equivalent" to the ARIETTA 70 (K134016) in terms of:

• Indication for Use: The ALOKA LISENDO 880's indications for use are listed and shown to broadly align with those of the ARIETTA 70.
• Modes of Operation: Both devices are stated to have the same core modes of operation (B mode, M mode, PW mode, CW mode, Color Doppler, Power Doppler, TDI, 3D Imaging, 4D Imaging, and combinations).
• Probe Types: Both support Convex, Linear, Sector, and other probe types.
• Applicable Software Features: A long list of software features (e.g., DICOM, Freehand 3D, Real-time Doppler Auto Trace, Spatial Compound) are listed as being present in both the subject and predicate devices with "YES" for both, implying functional equivalence.

The "Conclusions" section (Page 21) summarizes these points, stating that the ALOKA LISENDO 880 is substantially equivalent in safety and effectiveness based on:

• Same indications for diagnostic ultrasound imaging and fluid flow analysis.
• Same gray scale and Doppler capabilities.
• Same essential technology for imaging, Doppler functions, and signal processing.
• Acoustic level below Track 3 FDA limits.
• Manufactured in accordance with FDA 21 CFR 820 Quality System Regulations.
• Designed and manufactured to the same electrical and physical safety standards.
• Materials tested in accordance with ISO 10993-1.
• Reusable probes with instructions for cleaning, disinfection, and sterilization.

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 under "2. Clinical testing:" that "None required." This indicates that no separate clinical test set was used to establish performance for the ALOKA LISENDO 880 for the purpose of this 510(k) submission. The FDA allows clearance of devices through the 510(k) pathway if they are shown to be substantially equivalent to a legally marketed predicate device, often without new clinical studies if the technological characteristics are similar.

Therefore, there is no information on sample size, data provenance, or whether data was retrospective or prospective, as no new clinical testing was conducted.

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)

Since no clinical testing was performed for the subject device as part of this 510(k) submission, there is no mention of experts being used to establish a ground truth for a test set specifically for the ALOKA LISENDO 880. The substantial equivalence argument relies on the predicate device's established safety and effectiveness.

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

As no clinical testing was conducted for the subject device to evaluate its performance against a ground truth, there is no information on adjudication methods for a test set.

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

The document does not mention any multi-reader multi-case (MRMC) comparative effectiveness study, nor does it refer to AI assistance. The ALOKA LISENDO 880 is described as a diagnostic ultrasound system, and the submission focuses on its equivalence to a predicate ultrasound system rather than advanced AI-driven interpretation or assisted diagnostics.

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

This submission is for a diagnostic ultrasound system, not an algorithm. Therefore, "standalone" algorithm performance is not applicable or discussed. The device is intended for use by "trained personnel (doctor, sonographer, etc.)", indicating human-in-the-loop operation.

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

No new ground truth data was generated or used for the ALOKA LISENDO 880's clearance as "no clinical testing" was required. The "ground truth" for the predicate device would have been established during its own clearance process, but that information is not detailed here.

8. The sample size for the training set

The document does not discuss any training sets, as it's not describing an AI/machine learning device. The clearance is based on the device's technical specifications and substantial equivalence to a predicate, not on a machine learning model's performance.

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

As there is no mention of a training set or machine learning components, this information is not provided.

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The PROBEAT-V with X-ray Limiting Accessory 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 with X-ray Limiting Accessory 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 equipment to perform the above work is composed of two main components: (1) a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered and (2) equipment necessary to generate the proton beam and direct it to the beam delivery system for patient treatment.

The X-ray Beam Limiting accessory for use in conjunction with the cleared PROBEAT-V system is designed to limit the patient's X-ray exposure during for patient positioning with the Cone Beam CT (CBCT). The device has 4 motorized leaves which are controlled by the PROBEAT-V imaging software to position the leaves in order to limit the patient's radiation exposure during patient positioning.

The provided text describes a 510(k) premarket notification for the PROBEAT-V Proton Beam Therapy System with X-ray Limiting Accessory. The document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report with specific acceptance criteria and detailed performance data on the X-ray Limiting Accessory itself.

Based on the provided information, I can extract the following:

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

The document does not provide a specific table of acceptance criteria with numerical targets. Instead, it states that "In all cases, the device performed as intended and met all pre-specified success criteria." The performance evaluation focused on the integration of the X-ray Beam Limiting Device with the PROBEAT-V system.

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

The document does not provide details on sample sizes for the test set or data provenance (country of origin, retrospective/prospective). The testing appears to be a validation of the integrated system in an engineering and performance testing context rather than a clinical study with 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. The testing described appears to be technical performance testing of the device itself (e.g., accuracy, resolution, safety) and not a diagnostic or therapeutic output requiring interpretation by medical experts to establish ground truth.

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

Not applicable. The testing described appears to be technical performance testing of the device itself and not a diagnostic or therapeutic output requiring adjudication.

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. This document describes a proton beam therapy system with an X-ray limiting accessory, not an AI-based diagnostic or therapeutic assistance system.

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

This refers to the performance of the device's X-ray limiting accessory and its integration with the PROBEAT-V system. The "Performance Data" section describes this standalone performance testing for the integrated system, including slice pitch accuracy, spatial accuracy, spatial resolution, isocenter accuracy, and performance with the proton beam therapy positioning system, as well as electrical safety and electromagnetic compatibility. The device performed as intended and met all pre-specified success criteria in these tests.

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

For the technical performance tests mentioned (slice pitch accuracy, spatial accuracy, etc.), the "ground truth" would be established by validated measurement standards and reference devices used in engineering and quality control, rather than clinical ground truth like pathology or expert consensus. For electrical safety and electromagnetic compatibility, the ground truth would be compliance with relevant international and national standards.

8. The sample size for the training set

Not applicable for this type of device and submission. This is not an AI/machine learning device requiring a training set.

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

Not applicable for this type of device and submission. This is not an AI/machine learning device requiring a training set.

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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 includes optional accessories to assist the radiation oncologist in the delivery of proton radiation to defined target volumes while sparing surrounding normal tissue and critical organs from excess 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 treatment site. The equipment to perform the above work is composed of two main components: (1) a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered and (2) equipment necessary to generate the proton beam and direct it to the beam delivery system for patient treatment.

This document describes the PROBEAT-V and its accessories, focusing on modifications to the minimum MU and the introduction of a high-accuracy camera system for patient positioning. The document states that testing was conducted to confirm the device meets pre-defined acceptance criteria. However, it does not provide specific details about the acceptance criteria or the study that proves the device meets them.

Therefore, I cannot answer your request based on the provided text. The document states that "All the tests were successfully conducted and confirmed that the device meets the pre-defined acceptance criteria," but it does not elaborate on:

1. A table of acceptance criteria and the reported device performance: No table or specific performance metrics are provided.
2. Sample size used for the test set and the data provenance: No information on sample size or data origin is given.
3. Number of experts and their qualifications: No details about experts are mentioned.
4. Adjudication method: Not described.
5. MRMC comparative effectiveness study: No indication of such a study.
6. Standalone performance: Not explicitly addressed in terms of a separate study.
7. Type of ground truth: Not specified.
8. Sample size for the training set: Not applicable as this is not a description of an AI/ML algorithm development.
9. How ground truth for the training set was established: Not applicable.

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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 whose primary responsibility is to ensure that the desired prescription parameters are 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
  • Rotating Gantry
  • Scanning Nozzle
  • Patient Positioning System
  • Cone Beam CT / X-ray Imaging System
• Fixed Beam Room
  • Scanning Nozzle
  • Patient Positioning System
  • Cone Beam CT

The beam production system is composed of the following components:

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

The provided text is a 510(k) summary for the PROBEAT-V proton beam therapy system. It describes the device, its intended use, and performance data. However, it does not contain the detailed information required to answer all the questions about specific acceptance criteria and a study proving the device meets those criteria, particularly regarding AI performance, expert ground truth, sample sizes for training/test sets, and adjudication methods, as this is neither an AI device nor does it have relevant information about AI device testing.

Here's a breakdown of what can be extracted from the document:

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

The document provides a general statement about performance testing without specific quantitative acceptance criteria. It broadly states that the device "functioned as intended and met its specifications."

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

This information is not provided in the document. The document describes general performance testing but does not specify sample sizes or data provenance.

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/provided. The PROBEAT-V is a therapeutic device (proton beam therapy system), not a diagnostic or AI-driven decision support system that typically requires expert-established ground truth for image interpretation or diagnosis. The performance testing focuses on the physical and functional aspects of the hardware and beam delivery.

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

This information is not applicable/provided for the same reasons as the previous point. Adjudication methods are typically used in studies involving subjective assessments or classifications by human readers, which is not the nature of the described performance testing for a proton beam therapy system.

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

There is no indication that an MRMC comparative effectiveness study was done, nor is AI assistance mentioned. The device is a proton beam therapy system, not an AI-driven image analysis or decision support tool.

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

This information is not applicable/provided. The PROBEAT-V is a physical medical device for radiation therapy, not an algorithm. Its performance testing relates to its mechanical, electrical, and beam delivery functionalities.

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

The concept of "ground truth" as typically applied to diagnostic studies (e.g., pathology for a tumor diagnosis) is not directly applicable here. The performance testing described (mechanical, beam, safety interfaces, electrical safety, EMC) likely uses objective, measurable physical parameters and engineering standards as its "ground truth" or reference for meeting specifications. For example, a "beam dose shape" would be compared against a pre-defined expected profile, or electrical safety against a standard like IEC 60601-1.

8. The sample size for the training set

This information is not applicable/provided. The PROBEAT-V is a hardware medical device; it does not involve a "training set" in the context of machine learning. Its design and manufacturing are based on engineering principles and established medical device standards.

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

This information is not applicable/provided for the same reasons as the previous point.

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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"

• o Gantry Room
  • · Rotating Gantry
  • . Scanning Nozzle
  • . Patient Couch (or Patient Positioning System)
  • . X-ray Imaging System
• o Fixed Beam Room
  • Scanning Nozzle .
  • . Patient Couch (or Patient Positioning System)
  • . X-ray Imaging System

The beam production system is composed of the following components"

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

The provided text describes the 510(k) premarket notification for the Hitachi PROBEAT-V, a medical charged-particle radiation therapy system. It outlines performance data but does not contain information about specific acceptance criteria, study methodologies, or AI performance metrics as requested.

Therefore, I cannot provide a table of acceptance criteria and reported device performance or information about sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, or training set details as these are not present in the provided document.

The document indicates that Hitachi performed validation testing to evaluate:

• Mechanical performance: Specifically for the rotating gantry and patient couch.
• Beam performance: To assess beam dose shape and beam dose.
• Safety interface testing: To evaluate beam stop control, dose monitor, area safety, and mechanical interlocks.
• Electrical safety and electromagnetic compatibility: In accordance with IEC 60601-1 and IEC 60601-1-2.

The conclusion of these tests was that "In all instances, the PROBEAT-V functioned as intended and met its specifications." This statement broadly implies that the device met its internal acceptance criteria for these functional and safety aspects, but the specific numerical or qualitative criteria for "met its specifications" are not detailed.

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Hitachi's PROBEAT with DSSS 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 with DSSS 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 PBTS is designed to be safe and reliable. The equipment to perform the above work is comprised of two main components. One is a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered. The other is the equipment necessary to generate the proton beam and direct it to the beam delivery system.

The provided text describes a Special 510(k) submission for the PROBEAT with DSSS, a modification to an existing proton beam therapy system. This type of submission is used for devices that are substantially equivalent to a predicate device and have only minor modifications that do not raise new questions of safety or effectiveness. As such, the submission primarily focuses on demonstrating substantial equivalence rather than presenting extensive new performance data or clinical studies like those for novel devices.

Therefore, many of the typical acceptance criteria and study details you requested for AI/software-based medical devices are not explicitly mentioned in this document. The document states that performance testing was conducted, but it does not detail specific acceptance criteria in terms of quantitative metrics, sample sizes, or expert involvement as one would expect for an AI algorithm.

Here's an attempt to answer your questions based on the provided text, indicating where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

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

Not applicable in the context of this 510(k) summary for a hardware modification to an existing proton therapy system. The "test set" would likely refer to engineering and system validation tests rather than a clinical dataset in the AI sense. The document does not specify details of these tests, their sample sizes, or data provenance.

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

Not applicable. This information is not provided. Ground truth in this context would likely be based on physical measurements and engineering specifications, not expert interpretation of data.

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

Not applicable. This information is not provided.

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

Not applicable. This is a hardware modification for a proton beam therapy system, not an AI-based diagnostic or assistive device that would involve human readers.

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

Not applicable. This refers to the performance of the overall Proton Beam Therapy System with the added DSSS component, which is a physical beam delivery system, not an algorithm.

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

Not explicitly stated. For a proton beam therapy system, ground truth for performance testing would typically involve:

• Physical measurements: Verifying beam parameters (dose, energy, shape, position) using phantoms, dosimeters, and other radiation detectors.
• Engineering specifications: Comparing actual performance against designed specifications.
• Pre-clinical verification: Potentially using biological samples or animal models to assess beam effects (though not explicitly mentioned here for this modification).

8. The sample size for the training set

Not applicable. This is a hardware modification to an existing proton therapy system. The concept of a "training set" is relevant for machine learning algorithms, which is not the primary subject of this 510(k) summary.

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

Not applicable for the same reasons as above.

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