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The 'TOPAZ Mobile X-ray System' is intended for use in obtaining human anatomical images of patients who cannot be moved to the radiology department for medical diagnosis.

"TOPAZ" system is a system providing state-of-the-art image quality, user interface. "TOPAZ" system may be moved quietly and smoothly with motor drive mechanism "TOPAZ" system has a basic type column, and a collapsible type column option with a trendy design that allows driving without disturbing the front view. The core part of x-ray source adopts high quality tube assembly, motorized x-ray collimator. HV cable assembly and High Voltage X-Ray Generator. Touch screen LCD based x-ray control console provides user-friendly interface and easy technique selection. Collimator supports high accuracy for selected x-ray field size over any SID. Direct radiography via flat panel detector improves-exam speed and comfort with efficiency. Digital flat panel detector with Csl screen provides spatial resolution, MTF, DQE and stability based on fine pixel pitch. Selection of an anatomical study on the Digital Imaging Software automatically sets up the x-ray generator's preprogrammed exposure technique. The types of "TOPAZ" system are divided into TOPAZ-32D, and TOPAZ-40D according to maximum power and mA. The higher the maximum output, the wider the mA range to choose from, giving the user more technical options to choose from. The "TOPAZ Mobile X-ray System" consists of a tube assembly. x-ray collimator. High Voltage X-Rav Generator, detector and mechanical parts for mobility.

The provided text is a 510(k) Summary for the TOPAZ Mobile X-ray System, which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a performance study with acceptance criteria in the format typically used for AI/CADe devices. This document describes the device, its intended use, technological characteristics, and differences from the predicate, along with non-clinical testing for safety and EMC standards.

Therefore, the specific information about "acceptance criteria and the study that proves the device meets the acceptance criteria" as requested for AI/CADe devices (including details like sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, type of ground truth, and training set details) is not present in this 510(k) Summary.

This document primarily asserts that the "TOPAZ Mobile X-ray System" is substantially equivalent to the predicate device "TOPAZ Mobile DR System (K201124)" based on:

• Identical intended use.
• Similar technological characteristics, with modifications thoroughly tested for safety and effectiveness against international standards.
• Nonclinical testing results provided in the 510(k) demonstrating that predetermined acceptance criteria were met for safety (electrical safety, EMC, radiation protection) and software validation.

The "study that proves the device meets the acceptance criteria" in this context refers to the nonclinical testing against various recognized international and FDA standards, not a clinical performance study with human readers or pathology, as would be expected for AI/CADe systems.

Here's a summary of the available information regarding acceptance criteria and testing, tailored to what is provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly present a table of acceptance criteria and reported device performance in the typical format for clinical accuracy for AI/CADe. Instead, it states that the device was assessed, tested, and passed predetermined testing criteria during validation testing, aligning with the risk analysis. It also confirms that the device meets "all the requirements listed in the Standards" (see the Standards table below). The "device performance" reported is its conformance to these standards and its substantial equivalence to the predicate.

Nonclinical Standards Met (acting as acceptance criteria for safety and effectiveness):

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

• Not Applicable/Not Provided. The document describes non-clinical engineering and software validation testing against standards, not a clinical study involving a "test set" of patient data for diagnostic performance. The focus is on the device's hardware, software (RADMAX), and new flat panel detectors meeting safety and electrical standards.

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

• Not Applicable/Not Provided. Ground truth establishment by experts is relevant for clinical performance studies, which this document does not describe.

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

• Not Applicable/Not Provided. This is relevant for clinical performance studies.

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

• No. This document describes a 510(k) for an X-ray system, not an AI/CADe system. No MRMC study was performed or is mentioned.

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

• Not Applicable/No. The device itself is an X-ray system, not an algorithm, and its performance is assessed in terms of meeting engineering and regulatory standards, not standalone diagnostic performance. The imaging software (RADMAX) is mentioned as identical to the predicate and has a "Basic Documentation Level" of concern, implying human interpretation of images.

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

• Not Applicable/Not Provided. For the non-clinical testing described, "ground truth" would relate to the correct functioning of the hardware and software according to specifications and standards, not clinical diagnostic accuracy.

8. The sample size for the training set:

• Not Applicable/Not Provided. This is relevant for AI/ML models. While the device contains software, it is not described as an AI/ML diagnostic algorithm needing a training set. The software changes are primarily GUI and image processing module updates, verified for impact on safety and effectiveness (not AI training).

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

• Not Applicable/Not Provided. As above, this is not an AI/ML submission requiring a training set.

In summary, the provided 510(k) document is for a mobile X-ray system and demonstrates substantial equivalence through nonclinical testing against recognized performance, safety, and EMC standards, rather than a clinical performance study with acceptance criteria related to diagnostic accuracy, which would be typical for AI-powered diagnostic devices.

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The TOPAZ Mobile DR System, is a mobile X-ray imaging system, for the purpose of acquiring X-ray images of the desired parts of a patient's anatomy.

This device is not intended for mammography, bone density, fluoroscopy and angiography applications.

The TOPAZ Mobile DR System, (TOPAZ), is a mobile x-ray system and is a modification of the predicate device. There are 2 models for TOPAZ: TOPAZ-32D (32KW) and TOPAZ-40D (40KW). TOPAZ, may be moved quietly and smoothly with a motor drive mechanism.

The core part of x-ray source is a tube assembly, motorized x-ray collimator, HV cable assembly and high frequency x-ray generator. A touch screen LCD based x-ray control console provides a user-friendly interface and technique selection. The Collimator supports high accuracy for selected x-ray field size over any SID. Selection of an anatomical study on the imaging software automatically sets up the x-ray generator's pre-programmed exposure technique.

The X-ray passing through a patient's body is sent to the detector and then converted into electrical signals. These signals go through the process of amplification and digital data conversion in the signal process on the workstation and saved in a DICOM file for review on the device or on a Picture Archiving & Communication System (PACS) workstation.

The provided text is a 510(k) summary for the DRGEM TOPAZ Mobile DR System. It discusses the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain any information about a study that proves the device meets specific acceptance criteria related to a human-in-the-loop or standalone AI performance study.

The "PERFORMANCE DATA" section explicitly states that "Nonclinical testing results are provided in the 510(k). Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met." This refers to engineering and safety testing against recognized standards (e.g., IEC 60601-2-54, ANSI AAMI ES60601-1, IEC 62304 for software), not clinical performance studies involving AI or human readers.

The key information missing to answer your request is data from a clinical performance study (e.g., diagnostic accuracy, reader study results). The device described is a mobile X-ray imaging system, which captures images. There is no mention of any integrated AI component that would require an AI-specific performance study with acceptance criteria for diagnostic performance.

Therefore, I cannot populate the table or answer most of your questions as the necessary information is not present in the provided document.

Here's what can be inferred or stated based on the provided text, and what cannot:

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

Cannot populate. The document focuses on regulatory compliance and engineering standards for the X-ray system itself, not diagnostic performance metrics (e.g., sensitivity, specificity, AUC) for an AI component. The "acceptance criteria" mentioned are for non-clinical engineering and safety tests, not clinical performance.

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

Not applicable/Not mentioned for clinical performance. The "test set" referenced in the document pertains to engineering validation and verification tests of the X-ray system's functions, not a clinical data set for evaluating diagnostic performance of an AI.

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/Not mentioned. Ground truth establishment by experts (e.g., radiologists) is relevant for diagnostic performance studies. This document reports on non-clinical engineering tests.

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

Not applicable/Not mentioned. Adjudication methods are used in reader studies or for ground truth establishment in clinical performance. This document does not describe such studies.

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. The document does not describe any MRMC study.

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

No. The document does not describe any standalone algorithm performance testing related to diagnostic accuracy.

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

Not applicable/Not mentioned for clinical performance. For engineering tests, the "ground truth" would be the successful operation of the device according to its specifications and regulatory standards.

8. The sample size for the training set

Not applicable/Not mentioned. This information would be relevant for an AI device. The document describes an X-ray imaging system, not an AI.

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

Not applicable/Not mentioned. This information would be relevant for an AI device. The document describes an X-ray imaging system, not an AI.

Summary of the Device and its Testing as per the document:

The TOPAZ Mobile DR System is a mobile X-ray imaging system. The 510(k) submission primarily focuses on demonstrating its substantial equivalence to an existing predicate device (K183292, also a TOPAZ Mobile DR System from DRGEM). The main difference for this new 510(k) (K201124) is the addition of five previously cleared digital X-ray detectors to the TOPAZ system.

The "Performance Data" section details that the system underwent non-clinical testing against various recognized international and national standards (e.g., IEC 60601 series for medical electrical equipment safety, radiation protection, usability; IEC 62304 for medical device software; DICOM standards, JPEG standards, etc.). The acceptance criteria for these tests were met, demonstrating the device's safety and effectiveness as an X-ray imaging system, and its performance as well as the predicate device. This refers to the engineering and regulatory compliance of the hardware and integrated software for image acquisition and handling, not the diagnostic interpretation or AI assistance.

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The TOPAZ Mobile DR System, is a mobile X-ray imaging system, for the purpose of acquiring X-ray images of the desired parts of a patient's anatomy.

This device is not intended for mammography, bone density, fluoroscopy and angiography applications.

The TOPAZ Mobile DR System. (TOPAZ), is a mobile x-ray system. There are 2 models for TOPAZ: TOPAZ-32D (32KW) and TOPAZ-40D (40KW). TOPAZ, may be moved quietly and smoothly with a motor drive mechanism.

The core part of x-ray source is a tube assembly, motorized x-ray collimator, HV cable assembly and high frequency x-ray generator. A touch screen LCD based x-ray control console provides a user-friendly interface and technique selection. The Collimator supports high accuracy for selected x-ray field size over any SID. Selection of an anatomical study on the imaging software automatically sets up the x-ray generator's pre-programmed exposure technique. Direct radiography via a flat panel detector improves workflow, exam speed and user comfort with efficiency. Digital flat panel detector with Csl screen provides good spatial resolution, MTF, DQE and stability based on a fine pixel pitch. The digital detector type used in TOPAZ is "VARIAN PacScan4336W" or "VARIAN PacScan4336W_V4 which was cleared as part of the Nexus DR™ Digital X-ray Imaging System (with PaxScan 4336Wv4), K161459.

The X-ray passing through a patient's body is sent to the detector and then converted into electrical signals. These signals go through the process of amplification and digital data conversion in the signal process on the workstation and saved in a DICOM file for review on the device or on a Picture Archiving & Communication System (PACS) workstation Image Management features and functions are:

• ROI: Default 13 ROI support .
• MARK: Unlimited support (User preset support) ●
• Horizontal Flip ●
• Vertical Flip .
• Rotate Clockwise (CW) ●
• . Rotate Counter Clockwise (CCW)
• Inverse (Black or White) .
• . Text Annotation
• Caliper / Ruler: Distance tool
• Angle: Angle measurement tool
• Zoom: Image zoom in/out ●
• . Magnify: Image magnify glass window
• . Pan: Image panning

The provided text does not describe acceptance criteria for a device's performance that is proven by a study. Instead, it is a 510(k) summary for the TOPAZ Mobile DR System, which is a mobile X-ray imaging system. The purpose of this document is to demonstrate "substantial equivalence" to a predicate device, meaning it's as safe and effective as a device already on the market.

Therefore, many of the requested points cannot be directly extracted from this document as it focuses on regulatory equivalence rather than specific performance acceptance criteria from a clinical or standalone study.

However, I can extract information related to the non-clinical testing performed to establish safety and effectiveness in comparison to the predicate device.

Here's an analysis based on the provided text, addressing the points where information is available:

1. Table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria for device performance in terms of diagnostic accuracy (e.g., sensitivity, specificity). Instead, it refers to fulfilling predetermined testing criteria based on regulatory standards for X-ray systems.

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: Not applicable in the context of diagnostic performance. The testing mentioned is non-clinical, focusing on compliance with safety and performance standards of the physical device and its software.
• Data Provenance: Not applicable. The testing was conducted at the factory and by "Standards testing facilities."

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

• Not applicable as this document details non-clinical testing for substantial equivalence, not a study evaluating diagnostic performance against a ground truth.

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

• Not applicable. The "test set" here refers to the system itself being tested against regulatory standards, not image data being adjudicated.

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. A MRMC comparative effectiveness study was explicitly NOT done. The document states: "Clinical testing is not necessary for the TOPAZ Mobile DR system in order to demonstrate substantial equivalence to the predicate device." This device is a basic X-ray system, not an AI-powered diagnostic tool.

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

• Not applicable. This device is an X-ray imaging system, not an algorithm, and its performance is evaluated in the context of its function to acquire images, not analyze them.

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

• Not applicable. For the non-clinical testing, the "ground truth" was the specifications and requirements outlined by the various recognized international and national standards (e.g., IEC, ANSI AAMI, NEMA, ISO).

8. The sample size for the training set

• Not applicable. There is no mention of a "training set" as this is not an AI/algorithmic device.

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

• Not applicable.

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The TOPAZ® EZ Microdebrider Coblation® Wand with Integrated Finger Switch is indicated for debridement, resection, ablation, and coagulation of soft tissue and hemostasis of blood vessels in arthroscopic and orthopedic procedures:

The TOPAZ® EZ Microdebrider Coblation® Wand with Integrated Finger Switch (Topaz EZ IFS) is a bipolar, sterile, high frequency electrosurgical device, which consists of a distal electrode tip composed of tungsten, an alumina ceramic spacer, stainless steel shaft, saline irrigation tubing and a molded handle with an integrated single finger switch used to activate the Wand. The handle connects proximally to the radiofrequency Controller via an electrical cable. The Topaz EZ IFS is only compatible with the ArthroCare Quantum Controllers.

Here's an analysis of the provided text regarding the acceptance criteria and supporting studies for the TOPAZ® EZ Microdebrider Coblation® Wand with Integrated Finger Switch:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document describes non-clinical performance testing to support substantial equivalence. It does not explicitly state the sample sizes for each specific test (e.g., how many wands were used for ablation testing or shaft stiffness tests). It also does not specify the provenance of "data" in the sense of patient data, as the tests are non-clinical, mechanical, and electrical in nature.

The changes are largely related to materials and manufacturing, and the data provenance for such tests would typically be laboratory-based (e.g., in-house testing at ArthroCare Corporation), rather than geo-specific or patient-derived. The study is not based on human or animal subjects, but on the device's physical and electrical characteristics.

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

Not applicable. The "ground truth" for non-clinical performance and safety testing (e.g., dimensions, electrical impedance, biocompatibility) is established by engineering specifications, international standards (like IEC 60601-2-2:2009), and material science principles, not by human expert interpretation of results in the way it would be for a diagnostic AI.

4. Adjudication Method for the Test Set:

Not applicable. As this is not a diagnostic or interpretative study involving human readers, there is no adjudication method used. The results are quantitative measurements against predefined criteria.

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

No. An MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic devices where human readers interpret medical images or data, and an AI might assist or replace them. The TOPAZ® EZ Microdebrider Coblation® Wand is a surgical tool, and its efficacy is evaluated through non-clinical performance, safety, and substantial equivalence to a predicate device.

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

No. This concept is not applicable as the device is a physical surgical tool, not an algorithm. The performance described is inherently "standalone" in the sense that the device's functional characteristics (e.g., ablation, electrical safety) are tested on their own.

7. Type of Ground Truth Used:

The ground truth used for these non-clinical tests is based on:

• Engineering Specifications: Designed dimensions, material properties, electrical characteristics.
• Performance Requirements: Defined operational parameters (e.g., saline flow rate, ablation efficacy).
• International Standards: e.g., IEC 60601-2-2:2009 for electrical safety.
• Biocompatibility Standards: Standards for assessing biological reactions to materials.
• Predicate Device Performance: The predicate device's established performance serves as a benchmark for demonstrating substantial equivalence.

8. Sample Size for the Training Set:

Not applicable. This device is not an AI/ML algorithm that requires a "training set" of data for learning. Its design and manufacturing process are based on engineering principles.

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

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

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