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The EmpNia eMotus system is used to measure and record the patient's respiratory waveform to aid with respiratory-synchronized image acquisition or reconstruction during CT diagnostic imaging or radiation treatment planning procedures, where there is a risk of respiratory motion compromising the resulting image.

The EmpNia eMotus system is used to derive and communicate a Gate signal to aid with organ position verification for radiation therapy treatment using CT or Xray imaging by monitoring the patient's respiratory waveform during the image acquisition, where there is a risk of respiratory motion compromising the resulting image.

The EmpNia eMotus system is used to derive and communicate a Gate signal to aid with radiation therapy treatment, where there is a risk of respiratory motion compromising the resulting treatment accuracy.

The eMotus Respiratory Motion Management System ("eMotus system") is designed to monitor patient respiratory motion and to provide information about this respiratory motion to an external medical device system, such as a radiation therapy delivery device (TDD) or a diagnostic imaging device (DX). The main components of the eMotus system include:

• Sensor pad with optical fiber sensors,
• Optical fiber cables,
• Optical transceiver,
• Data acquisition computer with eMotus software application,
• Communication modules for compatible external systems, and
• Cables to allow data transmission between the components.

The sensor pad is a single-use, disposable component with an adhesive backing that is placed directly on the patient's thorax or abdomen. The sensor pad is attached to optical fiber cables that connect to the optical transceiver, which collects optical signal data based on deflection of the sensors in response to respiratory motion. The transceiver digitizes the data and transmits it to the eMotus computer, which visualizes the data as a waveform that can be highlighted when the waveform amplitude reaches a user-specified threshold or the patient's respiratory cycle reaches a user-specified phase. The user can utilize the respiratory threshold and phase information to manually control an external TDD or DX system.

When connected to an external TDD or DX, the eMotus system supports the following functions (as applicable given the functions of the external system):

• Threshold-gated therapy delivery: Automatic gating (turning on / off) of the radiation treatment beam based on user-set parameters for the amplitude of the respiratory waveform.
• Phase-gated therapy delivery: Automatic gating (turning on / off) of the radiation treatment beam based on user-set parameters for the phase of the respiratory waveform cycle.
• Retrospective four-dimensional planning scan: Delivery of the respiratory waveform to an imaging device to synchronize the waveform data with the scan data, enabling retrospective four-dimensional reconstruction of the imaging session for use in treatment planning.
• Prospective four-dimensional planning scan: Automatic patient's respiratory waveform are within preset limits, which is used to disable the radiation beam automatically.

The eMotus device is an ancillary device and does not provide stand-alone therapy or diagnostic information.

Unfortunately, the provided text does not contain the detailed study information required to answer many of your questions. The 510(k) summary focuses on demonstrating "substantial equivalence" to a predicate device, and while it mentions "bench performance," it lacks the specific methodology, sample sizes, and expert involvement that would typically be present in a comprehensive clinical or standalone performance study report.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document mentions "Bench performance" testing but does not explicitly state formal acceptance criteria in a quantitative sense, nor does it provide specific numerical performance metrics beyond "nearly identical signals" and "stable dynamics."

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

• Sample Size for Test Set: Not specified. The text mentions "infant and adult phantoms" and "multiple sensors" but does not give specific numbers.
• Data Provenance: The study described as "bench performance" clearly implies a laboratory/simulated environment rather than clinical data from human patients. Therefore, information about country of origin, retrospective or prospective data, is not applicable or provided.

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 specified. Given it was "bench performance" with phantoms and a comparison to a predicate device, it's unlikely human experts were establishing ground truth in the traditional sense. The "ground truth" was likely derived from the known simulated respiratory patterns and the output of the predicate device.

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

Not applicable/Not specified. Adjudication methods are typically used when human reviewers are involved in assessing complex outputs. This was a bench performance study comparing waveforms and functionality.

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, an MRMC comparative effectiveness study was not explicitly done or described. The device is a "Respiratory Motion Management System," which aids in synchronizing image acquisition or radiation treatment – it's not an AI diagnostic tool that human readers would directly interpret to improve diagnostic accuracy in the way an MRMC study typically assesses. Therefore, the effect size for human reader improvement is not applicable to the information provided.

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

Yes, the "bench performance" described primarily represents a standalone evaluation of the eMotus system's technical capabilities in a controlled environment, comparing its output directly to known inputs and the predicate device's output. The "human factors" testing mentioned separately focuses on usability, but the core performance data is standalone.

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

The "ground truth" for the bench performance testing appears to be based on:

• Known simulated respiratory patterns (for assessing stable dynamics, peak frequency, irregular breathing alerts).
• Output of the predicate device (for comparing respiratory waveforms).

8. The sample size for the training set

The document does not mention any training set size, which suggests that the device, being a physiological signal monitoring and gating system, likely does not involve machine learning or AI that requires a labeled training set in the conventional sense for its core functionality. Its "software functions" are verified and validated, indicating traditional software engineering practices.

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

Not applicable/Not specified, as no training set is mentioned in the provided text.

In summary, the provided FDA 510(k) clearance letter and summary are designed to demonstrate substantial equivalence, not to provide a detailed clinical or standalone performance study report with the specific metrics you've requested beyond what's inferable from the "bench performance" section.

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

When the patient is in the seated position using the chair, the System is indicated for treatment of patients with localized tumors and other conditions susceptible to treatment by radiation in the head, neck and thorax.

The P-CURE Proton Therapy System (PPTS) is comprised of four main subsystems that function in tandem to generate the desired dose level and distribution at the target site:

• Beam production system (Synchrotron based accelerator)

  • Injector – produces and delivers protons to the synchrotron
  • Synchrotron ring – accelerates the proton beam in circular orbit (within the ring) to the desired energy level
  • Extraction system - extracts the beam from the ring to the beam delivery subsystem

• Beam delivery system for a single fixed beam treatment room. Steers and monitors the extracted proton pencil beam from the synchrotron to the desired treatment location (Nozzle).

• Patient Positioning System (P-ARTIS). Mechanically orients the patient (seated or on supine); provides independent means of patient registration using CT (3D) and X-ray (2D)

  • CT system (P-ARTIS CT)
  • Robotic arm and chair/couch (6 Degree of freedom Couch) (P-ARTIS PPS)
  • X-ray system (P-ARTIS XR)
  • Positioning Software (P-ART)

• Control and Safety Systems

  • Control Subsystem (TSM). Synchronizes the various subsystem actions and connects with hospital oncology information systems and PACS.
  • Safety Subsystem. Includes hardware and software means to ensure safe system operation for patient and personnel. It includes subsystem interlocks, treatment beam parameters monitoring, and others.

The provided FDA 510(k) clearance letter for the P-Cure Proton Therapy System (PPTS) does not contain specific acceptance criteria or a detailed study description with performance metrics that would allow for a comprehensive table and answer to all the questions. This document is a clearance letter, which summarizes the outcome of a review, rather than providing the full technical details of the submission.

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

1. Table of Acceptance Criteria and Reported Device Performance

The clearance letter does not list specific numerical acceptance criteria (e.g., minimum accuracy percentages, maximum error values) or direct quantitative performance results in a table format. It states that:

• "In all instances, the PTTS functioned as intended and met its specifications."
• "Testing demonstrated substantial equivalence in terms of performance and safety to the predicate."

To construct a table, we would need the actual specifications and the measured performance against those specifications, which are typically found in the full 510(k) submission, not the clearance letter.

Inferred Performance Claims (from "Performance Data" section):

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

The document does not provide details on the "sample size" in terms of patient data or case numbers for the performance testing. The testing described is primarily technical and engineering verification and validation of the system's components and functions (mechanical, beam, safety, software integration, repeatability). It does not mention clinical studies with patient data.

• Sample Size for Test Set: Not specified for clinical cases. The testing appears to be system-level verification and validation, not patient-based clinical performance data.
• Data Provenance: Not applicable as no patient data (e.g., country of origin, retrospective/prospective) is referenced for the performance testing cited. The submitter, P-Cure, Ltd., is located in Israel, but this pertains to the company, not necessarily the origin of any clinical data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not mention any "ground truth" established by experts in the context of clinical performance, as it focuses on the technical verification and validation of the device's physical and software functions. Therefore, this question is not applicable based on the provided text.

4. Adjudication Method for the Test Set

As no expert review or clinical case evaluation is mentioned, there is no adjudication method described. This question is not applicable based on the provided text.

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

No MRMC study is mentioned. The clearance letter details technical and engineering performance testing, not studies comparing human reader performance with or without AI assistance. This question is not applicable based on the provided text.

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

The device described is a physical medical device (Proton Therapy System), not an AI algorithm to be used standalone or with human-in-the-loop for diagnostic or prognostic purposes. While the system has software, its "performance" refers to the entire system's ability to produce and deliver a proton beam accurately and safely. This question is not applicable in the typical sense of AI standalone performance.

7. The Type of Ground Truth Used

The "ground truth" for the performance testing appears to be based on:

• Known engineering specifications and physical laws: For beam performance, mechanical movements, dose delivery accuracy, etc.
• Safety standards: Compliance with IEC and AAPM standards.
• Software requirements: Validation against specified software functions.

There is no mention of expert consensus, pathology, or outcomes data as "ground truth" for the reported performance testing.

8. The Sample Size for the Training Set

The concept of a "training set" is usually applicable to machine learning algorithms. While the system involves software, the document describes traditional software validation and verification for system control and safety functions, not the development of a machine learning model that would require a distinct training set. Therefore, this question is not applicable based on the provided text.

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

As no "training set" (in the context of machine learning) is mentioned, the method for establishing its ground truth is also not applicable.

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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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ProBeam 360° Proton Therapy System provides protons for precision radiotherapy of lesions, tumors, and conditions anywhere in the body where radiation treatment is indicated.

The ProBeam 360° Proton Therapy System v2.0 (Multiroom) is designed to deliver radiation treatment in accordance with the physician's prescribed treatment plan. Proton radiation therapy takes advantage of the Bragg peak characteristic of proton attenuation to minimize radiation of normal tissue outside the target volume. Varian markets two lines of proton therapy systems, the standard ProBeam Proton Therapy Systems and the smaller, newer ProBeam 360° Systems. The ProBeam 360° Proton Therapy System line of proton systems includes single-room (cleared in K221791) and multi-room configurations. The ProBeam 360° System Multiroom (subject device) introduces the multi-room, compact configuration and includes the following primary components: Cyclotron (226MeV), Beam Transport System (energy selection system and beam transport system), Two (2) to five (5) Treatment Rooms: Rotating Isocentric Gantry room with attached scanning nozzle; and a treatment table, One Treatment Control Room for each treatment room within the chosen configuration.

The provided FDA 510(k) summary for the ProBeam 360° Proton Therapy System v2.0 (Multiroom) does not include specific acceptance criteria and detailed study results in the manner requested.

Instead, the document focuses on demonstrating substantial equivalence to a predicate device (ProBeam 360° Proton Therapy System v1.0, K221791) and a reference device (ProBeam Proton Therapy System v2.0, K133191). The study described is a design verification and validation process, rather than a clinical trial or performance study with defined statistically-based acceptance criteria against a specific benchmark.

Here's a breakdown of what can and cannot be extracted from the provided text according to your request:

Acceptance Criteria and Device Performance Study for ProBeam 360° Proton Therapy System v2.0 (Multiroom)

The ProBeam 360° Proton Therapy System v2.0 (Multiroom) primarily underwent design verification and validation testing to demonstrate that it performs as intended and meets its essential performance, confirming its substantial equivalence to previously cleared devices. The document does not specify quantitative acceptance criteria for performance metrics (such as sensitivity, specificity, accuracy) typically associated with medical device studies, nor does it provide a table of measured device performance against such criteria. The "performance" described is in the context of functionality and safety.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a "sample size" in terms of patient data or clinical cases for a test set. The testing described is non-clinical design verification and validation testing of the system components and software. This typically involves engineering tests, simulations, and hardware/software testing rather than patient data. Therefore, details regarding country of origin or retrospective/prospective nature are not applicable to the described non-clinical testing.

3. Number of Experts Used to Establish Ground Truth and Qualifications

This information is not provided in the document. As the described testing is non-clinical design verification and validation, the concept of "ground truth" as established by experts (e.g., clinicians) in the context of diagnostic accuracy or treatment efficacy is not directly relevant. The "ground truth" for these engineering tests would be the design specifications and expected functional behavior, which are internally verified by the manufacturer's engineers.

4. Adjudication Method for the Test Set

This information is not provided in the document. The adjudication method (e.g., 2+1, 3+1) is typically used in studies where human readers independently assess cases, and their discrepancies are resolved. This is not applicable to the non-clinical design verification and validation testing described.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed, or at least not described in this 510(k) summary. The submission explicitly states: "No animal studies or clinical tests have been included in this submission." This type of study would involve human readers (possibly with and without AI assistance) evaluating clinical cases, which is not what was conducted for this submission.

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

A standalone performance study of an algorithm in a clinical context (e.g., diagnostic accuracy for a specific disease) was not performed, or at least not described in this 510(k) summary. The device described is a proton therapy system, not typically a diagnostic AI algorithm. While software is a component, its performance testing is framed within system functionality and safety, not as an isolated algorithm performance study against clinical ground truth.

7. Type of Ground Truth Used

The ground truth for the non-clinical design verification and validation testing would be the engineering specifications, design requirements, and recognized industry standards (e.g., electrical safety, electromagnetic compatibility). These are validated through a series of tests to ensure the device performs according to its design and regulatory requirements. Clinical ground truth (e.g., pathology, outcomes data) was not used, as no clinical studies were submitted.

8. Sample Size for the Training Set

This information is not applicable/not provided. The document describes a medical device (proton therapy system), not an AI model that requires a "training set" of data in the typical machine learning sense. The software development follows a lifecycle process (IEC 62304) and involves verification and validation, but not training on a dataset of clinical cases.

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

This information is not applicable/not provided, for the same reason as in point 8. No "training set" in the context of machine learning was used or described.

In summary: The provided document is an FDA 510(k) summary for a hardware-based medical device (a proton therapy system) with associated software. The "study" it describes is the design verification and validation process to demonstrate the device's safety and effectiveness compared to existing, cleared devices, rather than a clinical performance study with specific quantitative acceptance criteria and clinical outcome measures.

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The P-Cure Proton Therapy System is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other condition susceptible to treatment by radiation in the head, neck and thorax.

The P-CURE system is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other condition susceptible to treatment by radiation in the head, neck and thorax.

The P-CURE proton beam therapy system comprises four main subsystems that function in tandem to generate the desired dose level and distribution at the target site:
Beam production system (Synchrotron based accelerator)

• Injector produces and delivers protons to the synchrotron
• Synchrotron ring accelerates the proton beam in circular orbit (within the ring) to the desired energy level
• Extraction system extracts the beam from the ring to the beam delivery subsystem
  Beam delivery system for a single fixed beam treatment room. Steers and monitors the extracted proton pencil beam from the synchrotron to the desired treatment location (Nozzle).
  Patient Positioning System (P-ARTIS). Mechanically orients the seated patient; provides independent means of patient registration using CT (3D) and X-ray (2D)
• CT system (P-ARTIS CT)
• Robotic arm and chair (6 Degree of freedom Couch) (P-ARTIS PPS)
• X-ray system (P-ARTIS XR)
• Positioning Software (P-ARTIS SW)
  Control and Safety Systems
• Control Subsystem (TSM). Synchronizes the various subsystem actions and connects with hospital oncology information systems and PACS.
• Safety Subsystem. Includes hardware and software means to ensure safe system operation for patient and personnel. It includes subsystem interlocks, treatment beam parameters monitoring, and others.

The provided text describes a 510(k) premarket notification for the P-Cure Proton Beam Therapy System, demonstrating its substantial equivalence to a predicate device (ProTom Radiance 330). However, it does not contain the specific information required to answer your request regarding acceptance criteria and a detailed study proving the device meets those criteria for an AI/CADe device.

The document primarily focuses on:

• Legal/Regulatory Status: FDA clearance (K221996), device classification, and general controls.
• Device Description: Components of the P-Cure system (synchrotron, beam delivery, patient positioning, control/safety).
• Comparison to Predicate: Highlighting similarities in core technology (proton beam, synchrotron, energy range, pencil beam scanning) and differences (fixed beam vs. gantry, seated vs. supine patient position).
• Performance Data (General): A high-level list of tests performed (mechanical, beam performance, safety interface, simulation/validation, repeatability/reproducibility) and a general statement that the device "functioned as intended and met its specifications."

Therefore, I cannot provide the requested information for the following reasons:

• No Acceptance Criteria Table or Reported Performance: The document states "In all instances, the P-Cure System functioned as intended and met its specifications" but does not provide a table with specific acceptance criteria (e.g., precision, accuracy, sensitivity, specificity values) or the numerical results of performance for each criterion.
• No Information on AI/CADe Study: The P-Cure device is a Proton Beam Therapy System, not an AI/CADe (Computer-Assisted Detection/Diagnosis) device for image analysis. The performance data mentioned (mechanical, beam, safety, positioning) are related to the physical operation and output of the radiation therapy system itself, not to the performance of an AI algorithm in detecting or diagnosing conditions from medical images.
• No Test Set Details: Since it's not an AI/CADe study, there's no mention of sample size for a test set, data provenance, ground truth establishment methods (expert consensus, pathology), adjudication, or MRMC studies.
• No Training Set Details: Similarly, for a physical device, there isn't a training set in the context of an AI model.

If the request was based on a misunderstanding of the document's content and aimed at describing the performance validation of a complex medical device (like the proton therapy system) in a general sense, the document provides the following limited details:

• General Performance Testing Categories: Mechanical, beam performance, safety interface, simulation/validation, and repeatability/reproducibility testing.
• Applicable Standards: IEC 60601-1, IEC 600601-1-2, EN 606601-2-44, IEC 60601-1-3, IEC 60601-1-8, IEC 60601-2-54, IEC 60601-1-64, IEC 60601-2-68, IEC 62667, and AAPM TG-224. These standards are typically related to general medical electrical equipment safety, electromagnetic compatibility, radiation therapy equipment, and specific performance measurements for such devices.
• Overall Conclusion: "In all instances, the P-Cure System functioned as intended and met its specifications. Testing demonstrated substantial equivalence in terms of performance and safety to the predicate."

In summary, the provided document is a 510(k) clearance letter for a proton beam therapy system, not a study report for an AI/CADe device. Therefore, it does not contain the specific information required for your detailed questions about AI model acceptance criteria and validation.

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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 ProBeam 360° Proton Therapy System provides protons for precision radiotherapy of lesions, turnors, and conditions anywhere in the body where radiation treatment is indicated.

The ProBeam 360° Proton Therapy System is a device that generates ionizing radiation (protons) in order to deliver radiation therapy in accordance with a predetermined treatment plan. The ProBeam 360° System version 1.0 is available in single-room, compact configuration and includes the following primary components: Cyclotron, Beam Transport System, Treatment Room with a rotating Gantry, Treatment Control Room.

The provided text is a 510(k) Premarket Notification summary for the Varian ProBeam 360° Proton Therapy System. It details the device, its intended use, comparison to a predicate device, and a summary of performance testing.

However, it does not contain information about the acceptance criteria and the study that proves the device meets the acceptance criteria in the context of an AI/ML-driven medical device validation. The document explicitly states:

"No animal studies or clinical tests have been included in this pre-market submission."

This indicates that the submission relies on design verification and validation testing, conformance to standards, and comparison to a predicate device, rather than performance studies that would involve a test set, ground truth experts, MRMC studies, or standalone algorithm performance as typically found in AI/ML medical device submissions.

Therefore, I cannot extract the information required to answer your prompt points 1-9 from the provided text. The document describes a traditional medical device (a radiation therapy system), not an AI/ML device that requires validation of its diagnostic or predictive performance on a data set.

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The intended use of the myQA iON product is to perform patient quality assurance activities for radiation therapy treatment delivery systems. myQA iON is a software toolbox allowing the Medical Physicist to perform quality assurance activities before and after the patient treatment fractions for all patients undergoing radiation therapy.

The myQA iON product is a server-based software application for performing patient quality assurance for radiation therapy. In its full scope, the product delivers means for the verification of:

• The patient treatment plan prior to the first treatment fraction by
  • Using an independent dose algorithm to compute a dose map based on the patient treatment plan;
  • Performing measurements using external measurement devices and analyzing the results;
  • Performing machine log analysis during a treatment dry run session and reconstructing the delivered dose.
• The patient treatment delivery by
  • Performing machine log analysis and reconstructing the delivered dose for each treatment fraction.
    In its full scope, the product interfaces with the Treatment Planning System, the Oncology Information System, the treatment delivery System and the external measurement device.

Here's a breakdown of the acceptance criteria and the study information based on the provided text, using the requested format:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific quantitative acceptance criteria or corresponding reported device performance metrics for the myQA iON. Instead, it describes general testing categories to assess the device's performance. The study aims to demonstrate substantial equivalence, implying that its performance should be comparable to the predicate device but doesn't quantify this in a numerical acceptance table within this document.

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

The document does not specify the sample size used for any of the described tests (Risk Analysis, Software, Physics, Integration, System, or Beta Testing). It also does not mention the country of origin of the data or whether the tests were retrospective or prospective. These tests appear to be internal verification and validation activities conducted by the manufacturer.

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

The document does not provide information on the number of experts used or their qualifications for establishing ground truth within the described non-clinical tests. The tests focus on software functionality, physics algorithms, and workflow, which typically rely on internal validation against established standards or expected behaviors rather than expert consensus on a "ground truth" dataset in the typical clinical AI sense.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1, none) for the test set. Given the nature of the described non-clinical tests, such adjudication methods are typically not applicable.

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

The document explicitly states: "The subject of this premarket submission, the IBA Dosimetry myQA iON product, did not require clinical testing to support substantial equivalence to the predicate device." Therefore, no MRMC comparative effectiveness study was done, and there is no reported effect size regarding human reader improvement with or without AI assistance.

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

The document describes "Physics Testing verifying the correct behavior of the physics algorithms" and "Software Testing verifying the correct software implementation." While these evaluate the algorithm's performance in isolation from a human user in some sense, they are part of non-clinical verification and validation activities, not a formal standalone performance study as would typically be conducted for a diagnostic AI. The device's intended use is as a "software toolbox allowing the Medical Physicist to perform quality assurance activities," implying a human-in-the-loop interaction for its full functionality. However, the core independent dose calculation and analysis features could be considered standalone algorithmic functions. The document does not present a dedicated "standalone performance study" with metrics like sensitivity, specificity, or AUC.

7. Type of Ground Truth Used

The ground truth for the non-clinical tests appears to be based on:

• Identified hazard mitigations: For Risk Analysis Testing.
• Expected software implementation and behavior: For Software, Integration, and System Testing.
• Known physical principles and expected outputs: For Physics Testing verifying the correct behavior of physics algorithms.
• Usability goals: For Beta Testing.

This is not "expert consensus, pathology, or outcomes data" in the typical clinical context but rather internal validation against design specifications and established scientific/engineering principles.

8. Sample Size for the Training Set

The document does not mention a training set sample size. The myQA iON is described as a "software toolbox" and implies deterministic physics algorithms and analysis tools rather than a machine learning model that would require a distinct training set.

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

Since the document does not indicate the use of a training set for a machine learning model, this information is not applicable and is not provided.

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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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