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Radiance V5 is a software system intended for treatment planning and analysis of radiation therapy administered with devices suitable for intraoperative radiotherapy.

The treatment plans provide treatment unit set-up parameters and estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by the intended user.

The system functionality can be configured based on user needs.

The intended users of Radiance V5 shall be clinically qualified radiation therapy staff trained in using the system.

Radiance V5 is a treatment simulation tool with faster Monte-Carlo simulation, multi-modal planning based on modern imaging standard for intraoperative radiotherapy (IORT). A software program for planning and analysis of radiation therapy plans. Typically, a treatment plan is created by importing patient images obtained from a CT scanner, defining regions of interest , deciding on a treatment setup and objectives, optimizing the treatment parameters, comparing alternative plans to find the best compromise, computing the clinical dose distribution, approving the plan and exporting it.

The provided text, a 510(k) summary for the Radiance V5 device, does not contain detailed information about the specific acceptance criteria and the study proving the device meets those criteria, particularly in the context of performance metrics like accuracy, sensitivity, or specificity.

Instead, the document focuses on:

• Substantial Equivalence: Arguing that Radiance V5 is substantially equivalent to its predicate device (Radiance V4, K171885).
• Technological Characteristics: Highlighting similarities in functionality and workflow, and noting improvements like faster Monte-Carlo simulation (GPU-based Hybrid Monte Carlo) and a redesigned UI.
• Non-Clinical Data: Stating that validation and verification testing indicated the device meets predefined product requirements and standards (IEC 61217, IEC 62083, IEC 62304, IEC 62366).
• Clinical Data (Limited): Referencing a clinical study performed for an even earlier predecessor (Radiance, K112060) to evaluate effectiveness and repeatability of the planning process in IORT. It then claims this data is safely extrapolatable to V5 because the changes in V5 do not modify basic functionality or workflow.
• Software V&V: Stating conformance with IEC 62304 and FDA guidance for software.

Crucially, the document does not provide a table of acceptance criteria with corresponding performance results for Radiance V5 itself, nor does it describe a study specifically designed to prove Radiance V5 meets quantitative performance metrics like those typically required for AI/ML-based diagnostic or treatment optimization tools (e.g., AUC, sensitivity, specificity, or error rates compared to ground truth).

The "Performance Data" section vaguely mentions "predefined products requirements" and "validation and verification testing" for non-clinical data, but does not elaborate on what these requirements or results were.

Given the information provided in the document:

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

• Acceptance Criteria: Not explicitly detailed in quantitative, verifiable metrics (e.g., specific thresholds for dose accuracy, planning time, or UI usability scores). The document mentions meeting "predefined product requirements" and requirements from standards like IEC 61217, IEC 62083, IEC 62304, and IEC 62366. These standards typically cover aspects like safety, software lifecycle processes, usability engineering, and equipment-specific requirements, but do not necessarily define specific performance thresholds for a treatment planning algorithm's output accuracy against a clinical ground truth.
• Reported Device Performance: The document highlights improvements in "speed of the Hybrid Monte Carlo calculations" as a key performance enhancement over previous versions, making "less precise calculations unnecessary." It also states that validation and verification testing was "carried out on Radiance V5 indicates that it meets its predefined products requirements." No specific numerical performance data (e.g., accuracy, precision) are reported for Radiance V5's core treatment planning capabilities.

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

• Test Set Sample Size: Not specified for Radiance V5. The document only references a clinical study for a predecessor (Radiance, K112060), but does not provide details about its sample size, data provenance (e.g., country of origin), or whether it was retrospective or prospective. It asserts that this prior study's data "can be safely extrapolated and is also valid for Radiance V5."

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

• Not specified. The document does not describe the establishment of a ground truth for performance testing of Radiance V5 or its direct predecessor (V4). The "clinical study" mentioned for the even earlier Radiance (K112060) is vaguely described as evaluating "effectiveness and repeatability of the planning process," but details on ground truth establishment from experts are absent.

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

• Not specified. This level of detail about test set design is not present in the document.

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

• No MRMC study is detailed for Radiance V5. The document focuses on the device as a standalone treatment planning software that assists clinicians, rather than an AI that augments human interpretation in a diagnostic context requiring MRMC studies (which are more common for AI-assisted diagnostic imaging interpretation). The "clinical study" mentioned for the predecessor evaluated the "effectiveness and repeatability of the planning process," not human reading improvement.

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

• The document implies that non-clinical validation and verification testing was done on the software itself to ensure it met "predefined product requirements" and standards. This would effectively be a standalone performance evaluation against defined specifications, but the specifics of what was measured and how (e.g., dose calculation accuracy compared to a gold standard physics model) are not provided. The comparison of Monte Carlo calculations in V5 to less precise calculations in prior versions suggests an internal performance metric, but not a direct standalone clinical performance evaluation against a human or true outcome.

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

• Not specified. For a treatment planning system, ground truth would typically relate to the accuracy of dose calculations compared to a physics model or measurements, or the clinical efficacy and safety of the plans generated. The document only refers to the predecessor's study evaluating "effectiveness and repeatability of the planning process" and "current uncertainties in regard to (manual) treatment planning," which suggests a comparison to manual methods but doesn't define a specific ground truth.

8. The sample size for the training set:

• Not applicable as described. Radiance V5 is described as a "software program for planning and analysis of radiation therapy plans" with a "three dimensional dosimetry engine" and "Hybrid Monte Carlo dose computations." It's not presented as an AI/ML model that would typically have a distinct "training set" of patient data in the modern supervised learning sense. While it's software that performs complex calculations, the term "AI" is not explicitly used, and its "engine" implies a deterministic algorithm rather than a learned model requiring a training dataset.

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

• Not applicable. As noted above, the device is not described as utilizing a training set in the AI/ML context. Its enhancements ("faster Monte-Carlo simulation," "redesigned user interface workflow," "multi-modal multi-image planning") appear to be engineering and algorithmic improvements rather than AI model training on a dataset with established ground truth.

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The RadianceTx Radionuclide Brachytherapy Source (RTx-RBS) is indicated for episcleral brachytherapy of umors and benign growths.

The RTx-RBS is intended for use within a compatible manual brachytherapy applicator system.

Not Found

This is an FDA clearance letter for a medical device called "RadianceTx Radionuclide Brachytherapy Source (RTx-RBS)". This document type does not include information about acceptance criteria or a study proving the device meets those criteria.

FDA clearance letters affirm that a new device is "substantially equivalent" to a predicate device already on the market, meaning it performs as safely and effectively as a device already legally marketed. For such clearance, the FDA does not require a new clinical study to establish acceptance criteria and prove its performance in the same way a Premarket Approval (PMA) application would.

Therefore, I cannot extract the requested information from the provided text.

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The Radiance Ultra 32" 4K ZeroWire Duo is a paired wireless video communication transmitter and receiver, intended for delivery of video signals from a source such as an endoscopy camera/processor, or other video source over a radiofrequency link to a ZeroWire Receiver for display of images during endoscopic and general surgical procedures. The Radiance Ultra 32" 4K ZeroWire Duo is a non-sterile reusable device not intended for use in the sterile field.

Radiance Ultra 32" 4K ZeroWire Duo is a medical LCD display designed to both wirelessly receive or transmit video signal with up to 4K resolution over a radio frequency link to a partner display.

This document describes acceptance criteria and performance data for the Radiance Ultra 32" 4K ZeroWire Duo, a wireless video communication transmitter and receiver intended for displaying images during endoscopic and general surgical procedures.

Important Note: The provided text is a 510(k) summary from the FDA, which focuses on demonstrating substantial equivalence to predicate devices. As such, it often refers to "design verification" and "design validation" studies without providing detailed methodologies or specific performance metrics from those studies. Therefore, some requested information may not be explicitly available in the given text, and conclusions will be drawn based on the information provided.

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

The document does not explicitly list "acceptance criteria" in a quantitative format with corresponding "reported device performance" in the way one might see for an AI algorithm's diagnostic accuracy. Instead, it compares the technical specifications and standards compliance of the proposed device against its predicate devices. The "performance" in this context refers to meeting these specifications and standards.

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" in the context of clinical data or images. This device is a display/wireless transmission system, not a diagnostic AI device that processes patient data. The "design validation" mentioned in section N and O would refer to testing the hardware and software functionality against engineering specifications and relevant medical device standards, rather than a clinical study with patients or patient data. Therefore, information on data provenance or sample size for a test set of clinical cases is not applicable/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 applicable, as a test set for clinical ground truth is not detailed for this type of device. The "ground truth" for this device would relate to engineering specifications and performance standards (e.g., video resolution accuracy, signal latency, wireless range), which are evaluated through technical testing by qualified engineers.

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

Not applicable for the reasons stated above.

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 device is a medical display and wireless video transmission system, not an AI-powered diagnostic tool. Therefore, an MRMC comparative effectiveness study involving human readers assisting with AI is not relevant to its evaluation.

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

Not applicable, as this is hardware, not an algorithm. The "standalone" performance would be about its technical capabilities (e.g., video transmission quality, latency, resolution) which are assessed through engineering tests. The document states in section N and O: "The display has successfully passed design validation to further demonstrate its safety and effectiveness" and "Based upon results from the design verification, Radiance Ultra 32" 4K ZeroWire Duo display demonstrates performance, safety, and effectiveness that are equivalent to the predicate devices." This implies various engineering and performance tests were conducted to verify its operation according to specifications and standards.

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

The "ground truth" for this device would be established by industrial standards (e.g., IEC 60601 series, FCC Part 15), engineering specifications, and validated test methodologies. For example, video resolution is objectively measured against a known signal, latency is measured using precise timing equipment, and electromagnetic compatibility is tested according to regulatory standards to ensure it doesn't interfere with other devices and operates safely in its intended environment.

8. The sample size for the training set

Not applicable. This device does not involve a "training set" in the context of machine learning or AI algorithms.

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

Not applicable for the same reason mentioned above.

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The ProTom Radiance 330 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.

The ProTom Radiance 330® is a medical device designed to produce and deliver a proton beam for the treatment of patients with solid tumors or other diseases susceptible for treatment by radiation. The device includes a method for delivering an accelerated proton beam to the treatment station. The device also includes equipment to position the patient and direct the beam angle.

The system is comprised of six main subsystems that function in tandem to generate the desired dose level and distribution at the target site.

• 1. Beam Production Subsystem. Produces a proton beam at the desired energy level
• 2. Beam Transport Subsystem. Transports the beam from the Beam Production Subsystem to the Beam Delivery Subsystem
• 3. Beam Delivery Subsystem. Monitors and steers the beam to the desired treatment location
• Gantry Subsystem. Mechanically orients the Beam Transport and Beam Delivery Subsystems: providing a means of patient x-ray registration
• 5. Patient Positioning Subsystem. Mechanically orients the patient; provide a separate and means of patient x-ray registration
• Control Subsystem. Synchronizes the various subsystem actions and connects with hospital oncology information systems

This document is a 510(k) summary for the ProTom Radiance 330™ Proton Beam Therapy System. It describes the device, its intended use, and compares it to a previously cleared predicate device (K134052).

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly present a table of acceptance criteria with specific numerical targets. Instead, it describes various tests performed and concludes that the device functioned as intended and was "substantially equivalent in terms of performance and safety in comparison to the predicate."

Here's a breakdown of the types of performance criteria implied and the general reported outcome:

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

The document describes verification and validation testing of the device and its subsystems. This typically involves engineering tests, simulations, and potentially phantom studies, rather than a clinical "test set" of patient data in the sense of an AI/imaging device.

Therefore:

• Sample Size for Test Set: Not applicable in the context of a "test set" of patient data. The testing described is hardware and software functional and safety testing.
• Data Provenance: Not applicable for patient data. The data provenance would be from internal engineering tests and measurements conducted by the manufacturer, ProTom International Holding Corporation. It's a prospective study in the sense of testing a newly manufactured or modified device.

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

This information is not provided because a "ground truth" derived from expert consensus on patient data (as seen in AI/diagnostic device submissions) is not relevant for the type of device and testing described. The "truth" for this device's performance testing is based on engineering specifications, physical measurements, and compliance with performance standards.

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

Not applicable. This device is a radiation therapy system, not an AI or diagnostic imaging device that requires human expert adjudication of results from a diagnostic 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:

Not applicable. The ProTom Radiance 330™ is a proton beam therapy delivery system. It is a fundamental treatment delivery device, not an AI-assisted diagnostic tool that would involve human readers or analysis of AI's improvement on human performance. The document does not describe any MRMC studies or AI involvement in human interpretation.

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

Not applicable. This is not an algorithm or AI product. It is a medical device for delivering radiation therapy.

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

Not applicable. The "ground truth" for the performance of a radiation therapy device is its ability to accurately and safely produce and deliver a proton beam according to its design specifications and relevant safety standards. This is established through physical measurements, dosimetric evaluations, and engineering tests.

8. The sample size for the training set:

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. There is no training set for this device.

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This device is intended for providing drainage of urine from the urinary tract.

The Radiance™ Clear Sharklet® Silicone Foley is identified as a balloon retention type catheter and is supplied sterile for single-use. It is a two-way silicone Foley catheter manufactured in 14.0. 16.0 and 18.0 French sizes with an effective working length of 34 centimeters. One lumen is used for drainage and the other lumen for inflation and deflation of the balloon. Sterile media is used to inflate and deflate the balloon. The proximal end of the drainage lumen has a funnel for connection to a drainage collection device. The proximal end of the inflation lumen has a check valve for connection to a syringe for inflation. The distal end has two drainage eyes placed opposite each other which allow drainage. The shaft has the Sharklet® micro-pattern molded into the outer surface.

This document is a 510(k) Premarket Notification from the FDA regarding the Radiance™ Clear Sharklet® Silicone Foley Catheter. As such, it outlines the device, its intended use, and the testing performed to demonstrate substantial equivalence to a predicate device, rather than providing details of an AI/ML-based device and its performance study using a test set against acceptance criteria. Therefore, the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment for an AI/ML device is not present in the provided text.

The document focuses on:

• Device Identification: Radiance™ Clear Sharklet® Silicone Foley Catheter.
• Intended Use: Providing drainage of urine from the urinary tract.
• Predicate Device: Well Lead Silicone and Latex Foley Catheters (K082815).
• Performance Testing: Physical and mechanical testing to demonstrate compliance with ASTM F623-99 and additional specific testing related to the "Sharklet" micropattern. This includes:
  • Flow Rate through Drainage Lumen
  • Balloon Integrity
  • Inflated Balloon Response to Traction
  • Balloon Volume Maintenance
  • Dimensional Verification
  • Balloon Deflation Reliability
  • Friction Testing (comparing the Sharklet catheter to a control)
  • Ovine Study (animal study comparing the Sharklet catheter to a control in sheep for one month)
  • Accelerated aged performance testing
  • Biocompatibility
  • Sterility testing

No information is provided on:

1. Acceptance criteria and reported device performance (in the context of AI/ML metrics like sensitivity, specificity, etc.): The document describes engineering and biological performance tests, not AI model performance.
2. Sample sizes for a test set and data provenance: The ovine study involved "six sheep," but this is not a test set for an AI/ML model.
3. Number of experts and qualifications for ground truth: Not applicable for this type of device submission.
4. Adjudication method: Not applicable.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study: Not mentioned.
6. Standalone (algorithm only) performance: Not applicable as it's a physical device.
7. Type of ground truth used (expert consensus, pathology, outcomes data): Not applicable in the AI/ML sense.
8. Sample size for the training set: Not applicable as it's not an AI/ML model.
9. How ground truth for the training set was established: Not applicable.

In conclusion, the provided text describes a 510(k) submission for a medical device (Foley catheter), not an AI/ML software as a medical device (SaMD). Therefore, the specific details requested for AI/ML device performance evaluation are not contained within the document.

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Radiance V4 is a software system intented for treatment planning and analysis of radiation therapy administered with devices suitable for intraoperative radiotherapy.

The treatment plans provide treatment unit set-up parameters and estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by the intended user.

The system functionality can be configured based on user needs.

The intended users of Radiance V4 shall be clinically qualified radiation therapy staff trained in using the system.

Radiance V4 is a planning tool for intraoperative radiotherapy (IORT), an application that provides a simulation of the dose distribution according to the parameters involved in the procedure. These parameters in IORT include the geometry of the applicator, its orientation and position with respect to the patient and IORT device parameters.

Radiance V4 is designed to analyze and plan radiation treatments in three dimensions for the purpose of treating patients with cancer. The user can adjust parameters to achieve a predicted outcome, rather than make a decision intra-operatively. The created treatment plans provide estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by qualified medical personnel.

This document describes the Radiance V4, a software system for radiation therapy treatment planning. The device received 510(k) clearance (K171885) on July 25, 2017, from the FDA.

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

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state acceptance criteria in a quantitative format with corresponding reported device performance metrics. Instead, it describes a process of design verification testing to assure the changes were "appropriate, safe and effective for the intended use." The performance data is summarized as addressing the "modifications and the impact on performance and safety."

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

The document does not specify a "test set" in the context of patient data or clinical images. The testing described is "design verification testing" related to technical modifications of the software. Therefore, sample size and data provenance in terms of patient data are not applicable here.

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

This information is not provided. The study focuses on design verification and technical performance rather than clinical performance based on expert-established ground truth on patient data.

4. Adjudication Method for the Test Set

This information is not provided. As the testing is design verification, a clinical adjudication method would not be relevant.

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

No MRMC comparative effectiveness study is mentioned. The submission is for a treatment planning software system, and the focus is on the software's ability to accurately calculate dose distributions and incorporate new features, not on improving human reader performance in diagnosis.

6. Standalone Performance

The primary function of Radiance V4 is a standalone planning tool. The "design verification testing" would inherently assess the algorithm's performance in calculating dose distributions and implementing the new features. However, specific standalone performance metrics (e.g., accuracy of dose calculation compared to a gold standard) are not quantitatively reported in this summary.

7. Type of Ground Truth Used

The "ground truth" for the design verification testing would likely involve:

• Technical specifications and requirements: Ensuring the software behaves according to its designed functionality.
• Physics-based models and simulations: Verifying the accuracy of dose calculations based on established radiation physics.
• Comparisons to established physical measurements (e.g., phantom measurements for dose distribution, though not explicitly stated as being performed here).

The document mentions that the changes include "improved accuracy of the dose in the first millimeters to the applicator surface" and "calculation of water equivalent dose." These imply a comparison against a known, accurate dose distribution or calculation method.

8. Sample Size for the Training Set

No information about a "training set" is provided. As a treatment planning software, it's not a machine learning model that requires a labeled dataset for training in the conventional sense. The development would involve engineering and physics principles rather than AI training.

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

Not applicable, as there is no mention of a training set for a machine learning model.

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The Radiance Ultra series ZeroWire G2 is a paired wireless video communication transmitter and receiver, intended for delivery of video signals from a source such as an endoscopy cameralprocessor, or other video source over a radio-frequency link to a ZeroWire Receiver for display of images during endoscopic and general surgical procedures. The Radiance Ultra series ZeroWire Embedded and ZeroWire G2 wireless video system is a non-sterile reusable device not intended for use in the sterile field

Radiance Ultra series ZeroWire Embedded monitors are designed with an integrated wireless video receiver module (Rx), enabling the reception of a video signal over a radio frequency link instead of a video cable. These monitors are designed for use in non-sterile healthcare environments. The Radiance Ultra series ZeroWire Embedded is a medical grade wireless video streaming device pair. The external transmitter (Tx) unit is designed to be mounted on a primary display, on an endoscopic cart, or any other elevated location in close vicinity to the video source. The Tx unit obtains its video input signal from either the loop through output of the primary display, or directly from the video source. The Tx unit will accept video in either HDMI/DVI or SDI formats up to 1920 x 1080p 60 Hz resolution. The Tx unit is powered by a NDS 12-24V DC-DC power converter while the Rx module shares the same 24V DC input of the display.

The provided text describes a medical device called "Radiance Ultra series ZeroWire Embedded" and its substantial equivalence to a predicate device. However, it does not contain information about specific acceptance criteria, a study proving the device meets those criteria, or a detailed breakdown of performance metrics, sample sizes, ground truth establishment, or expert involvement as requested in the prompt.

The document is a 510(k) premarket notification letter from the FDA, along with the applicant's 510(k) summary. It primarily focuses on establishing substantial equivalence to a predicate device (K151609 model ZeroWire G2) based on technological characteristics and intended use.

Here's a breakdown of what can be extracted and what is missing:

Information that can be extracted from the provided text:

• Device Name: Radiance Ultra series ZeroWire Embedded (and ZeroWire G2 for the paired transmitter/receiver system).
• Intended Use: Delivery of video signals from a source (e.g., endoscopy camera/processor) over a radio-frequency link to a ZeroWire Receiver for display of images during endoscopic and general surgical procedures. It is a non-sterile reusable device not intended for use in the sterile field.
• Predicate Device: K151609 model ZeroWire G2.
• Performance Claim (General): The device "meet and exceed IEC 60601-1, ANSI/AAMI ES60601-1, IEC 60601-1-2 and FCC part 15." It also states, "The displays have successfully passed design validation to further demonstrate their safety and effectiveness."
• Conclusion: The device demonstrates performance, safety, and effectiveness that are equivalent to the predicate device.

Information that is missing from the provided text regarding acceptance criteria and studies:

• A table of acceptance criteria and the reported device performance: While general standards (IEC, FCC) are mentioned, specific measurable acceptance criteria (e.g., latency, signal integrity, resolution maintenance under specific conditions) and the corresponding device performance against these criteria are not provided.
• Sample size used for the test set and the data provenance: No information on any specific test set, its size, or the origin of data is present.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as there's no mention of a test set requiring expert ground truth.
• Adjudication method for the test set: Not applicable.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, the effect size: Not applicable, as this device is a video transmission system, not an AI diagnostic tool that would typically involve human readers.
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable, for the same reason as above.
• The type of ground truth used: Not applicable.
• The sample size for the training set: Not applicable, as this is hardware for video transmission, not an AI algorithm requiring a training set.
• How the ground truth for the training set was established: Not applicable.

In summary, the provided document is a regulatory submission demonstrating substantial equivalence for a video display and transmission system. It focuses on compliance with general safety and electromagnetic compatibility standards and functional equivalence to a predicate device, rather than detailed performance metrics from a specific clinical or technical study against predefined acceptance criteria for a diagnostic or AI-driven device.

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Radiance V3 is a software system intented for treatment planning and analysis of radiation therapy administered with devices suitable for intraoperative radiotherapy.

The treatment plans provide treatment unit set-up parameters and estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by the intended user. The system functionality can be configured based on user needs.

The intended users of Radiance V3 shall be clinically qualified radiation therapy staff trained in using the system.

Radiance V3 is a treatment planning system, that is, a software program for planning and analysis of radiation therapy plans. Typically, a treatment plan is created by importing patient images obtained from a CT scanner, defining regions of interest either manually or semi-automatically, deciding on a treatment setup and objectives, optimizing the treatment parameters, comparing alternative plans to find the best compromise, computing the clinical dose distribution, approving the plan and exporting it.

Radiance V3 improvements over Radiance V2 (K133655) are:

• A Hybrid Monte Carlo dose computation algorithm for photons for the ● INTRABEAM.
• . A beam modeling tool which models and verifies the treatment unit model with measurements for the INTRABEAM.
• . An improved DICOM interface including PACS query&retrieve functionality. Storage SCP and DICOM.RT Structures and Dose exportation.

The list of compatible IOERT/IORT devices are:

• Intrabeam (a Carl Zeiss product) ●
• . NOVAC7 and NOVAC11 (a SIT product)
• . LIAC10 and LIAC12 (a SIT product)
• MOBETRON (an IntraOp Medical product)
• . Conventional LINACs with adapted cylindrical IOERT applicators (telescopic or fixed ones).

Radiance V3 has been tested with Elekta/Precise and Varian/21EX LINACs with particular IOERT cylindrical telescopic applicators.

Characteristics of radiance include:

• 1. Image manipulation and visualization
• 2. IORT applicator simulation
• 3. Contouring manual and interpolation tools
• 4. Dose calculation algorithms, including:
  • a. For Intrabeam, Dose Painting for a fast (a few seconds) interpolation of PDD around the applicator or Hybrid Monte Carlo for a good combination of computation time (a few minutes) and accuracy.
  • b. For IOERT, pencil beam for a fast (less than one minute) calculation of the dose or Monte Carlo for a good combination of computation time (between 1-10 minutes in most of the cases) and accuracy.
• 5. Reporting.
• 6. DICOM & DICOM.RT compatibility

Here's an analysis of the acceptance criteria and study information for the Radiance V3 device, based on the provided text:

Important Note: The provided document is a 510(k) summary, which often focuses on demonstrating substantial equivalence to a predicate device rather than presenting extensive de novo clinical trial data. Therefore, detailed performance metrics and statistical analyses typically found in full clinical study reports are not explicitly detailed here. The information below is extracted and inferred from the available text.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria in terms of performance metrics (e.g., specific accuracy thresholds for dose calculation). Instead, it focuses on verifying that the device meets its predefined product requirements and relevant industry standards. The performance is reported as meeting these requirements and passing various tests.

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

• Test Set Sample Size: The document does not specify a "test set" in terms of number of cases or patients. Instead, it refers to "Over 150 tests" that were executed, including verification tests for new functionality, risk mitigation, and regression tests. These tests involved simulated clinical workflows and algorithm testing with simulated setups. It's not clear if these 150+ tests refer to individual "cases" or different functional aspects.
• Data Provenance: The testing involved "simulated clinical workflows" and "algorithm testing using a simulated clinical setup." This implies that the data was not derived from real patient studies but rather from synthetic or phantom data to simulate various treatment scenarios. Therefore, there is no country of origin for real patient data, and it is a simulated/retrospective (in the sense of being pre-designed scenarios) evaluation rather than prospective clinical data.

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

The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set. Given that the testing involved "simulated clinical workflows" and "algorithm testing using a simulated clinical setup," the "ground truth" likely refers to established physical models, reference dose calculations (e.g., from more precise scientific methods or established phantoms), or mathematically derived correct outputs for the simulated scenarios.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method. Since the ground truth for the test set seems to be derived from physical/mathematical models or established reference calculations in simulated environments, a human adjudication process by multiple experts is not directly applicable in the same way it would be for interpreting medical images. The evaluation of results against the expected simulated outcomes would be done internally by the engineering and testing teams.

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

No MRMC comparative effectiveness study was done. The document explicitly states: "Clinical trials were not performed as part of the development of this product." Therefore, there is no information on the effect size of human readers improving with or without AI assistance, as human reader performance was not evaluated.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance evaluation was done. The entire "Performance Data" section (Section 7) describes verification and validation testing performed on the Radiance V3 system itself. This included:

• Validation and Verification Testing against predefined product requirements and industry standards.
• Algorithm testing to validate the accuracy of dose calculation functions using a simulated clinical setup.
• Over 150 tests executed for new functionality, risk mitigation, and regression.

This testing addresses the performance of the algorithm and software in a standalone capacity, without direct human-in-the-loop performance measurement.

7. Type of Ground Truth Used

The ground truth used was primarily based on:

• Predefined product requirements: The system's output was compared against its own specified functionalities and performance targets.
• Industry standards (IEC 61217, 62083, 62366): Compliance with these standards served as a form of ground truth for safety, design, and usability.
• Simulated clinical setups and reference dose calculations: For dose calculation accuracy, the "ground truth" would have been established by known physical principles, validated models, or highly accurate computational methods for the simulated scenarios, confirming whether the algorithm's output matched the expected physical reality.
• Predicate device comparison: The substantial equivalence argument relies on the Radiance V3 performing comparably or better than the predicate (Radiance V2), particularly with the new Hybrid Monte Carlo algorithm offering "a more accurate simulation."

8. Sample Size for the Training Set

The document does not provide information on the sample size for the training set. Treatment planning software like Radiance V3, while complex, typically relies on established physics models and algorithms rather than machine learning models that require explicit "training sets" in the sense of labeled data for supervised learning. The algorithms are built upon scientific principles and validated against known physical phenomena, not "trained" on a dataset of cases. Therefore, a training set in the typical AI/ML context is not applicable here.

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

As noted above, the concept of a "training set" and associated "ground truth" in the machine learning sense is not applicable to this type of physics-based treatment planning software. The algorithms are based on physics equations and models validated through established scientific methods and comparisons to physical measurements (e.g., beam modeling and output factors for INTRABEAM measurements mentioned in the "Beam modeling tool" section).

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The ProTom Radiance 330 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 Radiance 330 consists primarily of Beam Delivery and Beam Production systems. These systems are comprised of various components and/or accessories designed to produce and deliver a proton beam appropriate for patient treatment. The system components include:

• Beam Production System. This system produces the proton beam and directs it to the appropriate treatment room and is comprised of the following subsystems:
  • Synchrotron subsystem. The accelerator unit is the source of the proton beam and is composed of the injector (which generates the proton beam) and the synchrotron (which accumulates, accelerates, and extracts the proton beam).
  • Beam Transport subsystem. This subsystem guides the proton beam extracted from the synchrotron to the treatment room.
• Beam Delivery System. This system controls the irradiation dose and shapes the proton beam supplied through the beam transportation system into the configuration required for patient treatment, and directs the beam appropriately. It is comprised of the following subsystems:
  • Scan/Dose subsystem
  • Gantry subsystem
  • Patient Positioning subsystem.
  • Treatment Delivery Control subsystem

The provided text describes the ProTom Radiance 330™ Proton Beam Therapy System, but it is not an AI diagnostic device. It is a medical device for delivering proton beam radiation therapy. As such, the concept of "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of diagnostic performance (e.g., sensitivity, specificity, AUC) is not applicable here.

Instead, the performance data presented focuses on the functional aspects of the device in delivering radiation therapy rather than a diagnostic performance study.

Here's a breakdown of the information that is available, reframed to fit the device's purpose:

1. Table of System Specifications and Demonstrated Performance (Conceptual - Based on text)

The document states, "All testing demonstrated that the system met its specifications for its intended use." However, it does not provide a specific table of numerical acceptance criteria or reported performance values (e.g., beam uniformity, dose accuracy to a specific tolerance). It describes the types of performance evaluated.

2. Sample Size and Data Provenance:

• Sample Size for Test Set: Not applicable in the context of a diagnostic dataset. The "testing" refers to verification and validation of the physical system's operation. No information on the number of "cases" or "patients" used for testing is provided, as the testing focuses on hardware performance, not diagnostic accuracy.
• Data Provenance: Not applicable. The testing is likely internal to the manufacturer (ProTom International Inc.) and conducted on the device itself, rather than using patient data from a specific country or being retrospective/prospective in a diagnostic sense.

3. Number of Experts and Qualifications for Ground Truth:

• Not applicable as this is not a diagnostic device requiring expert consensus for ground truth on images or patient outcomes in the same way. The ground truth for operational performance would be established by engineering specifications and metrology standards.

4. Adjudication Method for Test Set:

• Not applicable. This concept is typically related to diagnostic reviews where multiple human readers assess a case.

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

• Not applicable. This is a study design for evaluating the impact of AI on human reader performance in diagnostic tasks. The ProTom Radiance 330™ is a treatment delivery device, not an AI diagnostic tool.

6. Standalone Performance Study:

• Yes, a standalone performance was done for the device itself (as opposed to an algorithm). The document explicitly states: "Each individual subsystem of the Radiance 330™ was verified and validated, and full system verification and validation was also performed." This refers to the operational performance of the machine and its components.

7. Type of Ground Truth Used:

• The ground truth for the device's functional performance would be engineering specifications, physical measurements, and internationally recognized safety/performance standards (e.g., IEC 60601-1). For example, a "designated dose" would have a specified target value, and the device's output would be measured against that.

8. Sample Size for the Training Set:

• Not applicable. This device is not an AI algorithm that undergoes "training" on a dataset. The components are engineered and tested, not "trained."

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

• Not applicable for the same reason as point 8.

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Radiance V2 is a software system intended for treatment planning and analysis of radiation therapy administered with devices suitable for intraoperative radiotherapy.

The treatment plans provide treatment unit set-up parameters and estimates of dose distributions expected during the proposed treatment, and may be used to administer treatments after review and approval by the intended user.

The system functionality can be configured based on user needs.

The intended users of Radiance V2 shall be clinically qualified radiation therapy staff trained in using the system.

Radiance V2 is a treatment planning system, that is, a software program for planning and analysis of radiation therapy plans. Typically, a treatment plan is created by importing patient images obtained from a CT scanner, defining regions of interest either manually or semi-automatically, deciding on a treatment setup and objectives, optimizing the treatment parameters, comparing alternative plans to find the best compromise, computing the clinical dose distribution. approving the plan and exporting it.

The provided text describes Radiance V2, a radiation treatment planning software, and its substantial equivalence to predicate devices, but it does not contain explicit acceptance criteria or a study proving that the device meets specific performance metrics.

However, it does mention validation and verification testing. Based on the available information, here's what can be extracted:

Acceptance Criteria and Device Performance

The document states that "Validation and Verification Testing carried out on the Radiance V2 indicates that it meets its predefined products requirements and requirements from the following product standards." However, the specific predefined product requirements (acceptance criteria) and the results showing how it met them (reported device performance) are not detailed in this summary.

The summary lists two standards that the device meets:

• IEC 61217: Radiotherapy equipment - Coordinates, movements and scales
• IEC 62083: Medical electrical equipment - Requirements for the safety of radiotherapy treatment planning systems

Without the specific product requirements, a table of acceptance criteria and reported performance cannot be generated directly from this document.

Study Information:

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

   • The document states: "The predecessor of Radiance V2 system, i.e., Radiance, has been tested clinically. This Clinical Study evaluated the effectiveness and repeatability of the planning process in IORT with Radiance in regard to the current modalities and the current uncertainties in regard to (manual) treatment planning."
   • No sample size for the test set is provided.
   • No data provenance (country of origin, retrospective/prospective) is provided.

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

   • This information is not provided in the document. The clinical study mentioned refers to the "planning process" in IORT and comparison to "manual treatment planning," suggesting expert involvement, but details are not given.

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

   • This information is not provided in the document.

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

   • An MRMC study per se is not explicitly mentioned. The clinical study cited for Radiance (the predecessor) "evaluated the effectiveness and repeatability of the planning process... in regard to the current modalities and the current uncertainties in regard to (manual) treatment planning." This implies a comparison, but it's not described as an MRMC study with AI assistance in the way typically understood for diagnostic AI. The document does not specify any effect size of human reader improvement with/without AI assistance.

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

   • The document focuses on "validation and verification testing" for the new features of Radiance V2 and states that the "computation algorithms and beam modeling tool" do not modify the basic functionality/workflow of the previous clinical study. This implies the core algorithms were tested, but whether a purely standalone performance evaluation (without any human review or interaction) was performed is not explicitly stated or detailed.

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

   • The document mentions the clinical study "evaluated the effectiveness and repeatability of the planning process... in regard to the current modalities and the current uncertainties in regard to (manual) treatment planning." This suggests that the "ground truth" for the predecessor's performance comparison was likely based on current clinical practice and manual treatment planning outcomes/judgments, but the specific definition (e.g., expert consensus on dose distribution accuracy, actual patient outcomes) is not detailed.

7. The sample size for the training set:

   • The document does not mention a separate training set or its sample size. The device is a "radiation treatment planning software" and the focus is on validation and verification against engineering requirements and a prior clinical study. This type of device typically uses physical models and measured data for beam modeling and dose calculation algorithm development, rather than a "training set" in the machine learning sense.

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

   • As no training set is explicitly discussed in the context of machine learning, this information is not applicable/provided. The "ground truth" for dose calculation algorithms is usually established through highly accurate physical measurements (e.g., in water phantoms) and/or sophisticated Monte Carlo simulations. The document mentions "Beam modeling of the treatment unit based on relative measurements and output factors" as a feature.

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