Search Results

The GC80 Series Digital X-ray imaging System is intended for use in generating radiographic images of human anatomy by a qualified/trained doctor or technician. This device is not intended for mammographic applications.

The GC80 digital X-ray imaging system consists of High voltage generator (HVG), Ceiling Suspension, X-ray tube, Collimator, Detector, AEC, DAP, CIB(Control Interface Box), Wall Stand, Patient Table, Collimator, Detector, Remote controller, Grid, Foot switch, Barcode scanner and Auto-stitching stand. This system is used to capture images by transmitting X-ray to a patient's body. 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 device being sent to the S-Station (Operation Software) and saved in DICOM file, a standard for medical imaging. The captured images are sent to the Picture Archiving & Communication System (PACS) server, and can be used for reading images.

The provided document is a 510(k) Premarket Notification for the SAMSUNG ELECTRONICS Co., Ltd. Digital Diagnostic X-ray System (GC80). It primarily focuses on demonstrating substantial equivalence to a predicate device (XGEO GC80) and does not detail specific acceptance criteria and a study dedicated to proving the device meets those criteria in the typical sense of a novel AI/CAD device.

Instead, the submission for the GC80 X-ray system focuses on confirming that its performance, despite the addition of a new detector, remains consistent with established medical device standards and is substantially equivalent to a previously cleared device. Therefore, the "acceptance criteria" here are effectively the performance standards met by the predicate device and relevant international/national standards, and the "study" is a comparative assessment.

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

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

The document does not explicitly present a table of acceptance criteria for specific diagnostic performance metrics (e.g., sensitivity, specificity for disease detection) that would be common for AI/CAD devices.
Instead, it focuses on the equivalence of technical specifications and image quality. The implicit acceptance criteria are that the device performs as well as the predicate device and meets relevant international standards.

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

• Sample Size for Clinical Data: The document states, "Clinical images were provided," but it does not specify the sample size (number of images or patients) used for this clinical evaluation.
• Data Provenance: Not explicitly stated in terms of country of origin or whether it was retrospective/prospective. Given "Clinical images were provided," it implies a retrospective collection of existing images for evaluation.

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)

• The document states, "In clinical data, the radiologists evaluate the image of GC80 is substantially equivalent, and superior in some images to the predicate device."
• Number of experts: Not specified (plural "radiologists" suggests more than one).
• Qualifications of experts: Not specified beyond "radiologists."

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

• The document does not specify an adjudication method. It only mentions that "radiologists evaluate the image."

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 done. This submission is for an X-ray system, not an AI/CAD device. The "clinical data" involved radiologists evaluating the images themselves, not evaluating AI output or comparing their performance with and without AI. Therefore, there's no discussion of human reader improvement with AI assistance.

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 AI algorithm. Its performance is inherent in its ability to generate radiographic images, not in its interpretation.

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

• For the clinical evaluation, the "ground truth" for the image quality assessment was the expert evaluation of radiologists. The goal was to confirm that the images generated by the GC80 were of comparable, or superior, quality for diagnostic purposes as those from the predicate device.

8. The sample size for the training set

• Not applicable / Not specified. As this is an X-ray imaging system and not an AI/CAD device, there is no "training set" in the context of machine learning. The system's performance is based on its hardware and software engineering meeting physical and technical standards.

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

• Not applicable. See point 8.

Ask a specific question about this device

The XGEO GU60A Digital X-ray Imaging System is intended for use in generating radiographic images of human anatomy by a qualified/trained doctor or technician. This device is not intended for mammographic applications.

The XGEO GU60A digital X-ray imaging system is to be used to take and store image for diagnosis of patients. It consists of the High voltage generator (HVG), U-arm positioner, Detector, X-ray tube, Collimator and etc.

The provided text describes a 510(k) premarket notification for the "XGEO GU60A Digital Diagnostic X-ray System." It outlines the device's intended use and compares it to a predicate device, but it does not contain acceptance criteria or a study proving the device meets those criteria in the format requested.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (Revolution XR/d of General Electric Company) for regulatory purposes. It mentions various tests conducted for safety, EMC, and performance according to established standards (e.g., IEC 60601 series, 21 CFR 1020.30, 21 CFR 1020.31, and FDA guidance for 510(k)s for Solid State X-ray Imaging Devices). It states, "All test results were satisfied," which implies the device passed, but it does not specify what those acceptance criteria were or present the detailed results of those tests.

Therefore, most of the requested information cannot be extracted from this document, specifically:

1. A table of acceptance criteria and the reported device performance: Not provided. The document states "All test results were satisfied" for safety, EMC, and performance tests, but does not list specific criteria or performance metrics.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective): Not provided. The document mentions "Non-clinical testing and Clinical Testing were conducted," but gives no details about sample size, provenance, or study design.

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 provided.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not provided.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: Not explicitly stated. The device is a "Digital Diagnostic X-ray System" for generating images, not an AI-powered diagnostic aid that assists human readers. Therefore, an MRMC study comparing human readers with and without AI assistance is unlikely for this type of device as described.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable. The device is a hardware system for image acquisition, not a standalone algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not provided, as detailed clinical study results are absent.

8. The sample size for the training set: Not provided. This device is an X-ray imaging system, not an AI model that typically requires a training set in the same context.

9. How the ground truth for the training set was established: Not provided. (See point 8).

Summary of what is present:

• Device Name: XGEO GU60A Digital Diagnostic X-ray System (K123106)
• Intended Use: Generating radiographic images of human anatomy by a qualified/trained doctor or technician. Not for mammographic applications.
• Predicate Device: Revolution XR/d of General Electric Company.
• Studies Conducted (mentioned, not detailed): Electrical, mechanical, environmental safety and performance testing according to IEC 60601 series, 21CFR1020.30, 21CFR1020.31; EMC testing according to IEC 60601-1-2(2001); Non-clinical testing and Clinical Testing in accordance with FDA guidance for 510(k)s for Solid State X-ray Imaging Devices.
• Conclusion: The device is safe and effective and substantially equivalent to the predicate device, with all test results reported as "satisfied."

Ask a specific question about this device

The DIAMOND-5A,6A,8A Digital Diagnostic X-ray System is indicated for use in generating radiographic images of human anatomy. This device is not intended for mammographic applications.

The digital X-ray imaging system consists of a high voltage (HV) generator, a tube support unit, an X-ray beam limiting device, a wall stand unit, a bucky table unit, a detector, operating software, and a tube, operates on a high-frequency inverter method, and is primarily used in a hospital for diagnosis of diseases in skeletal. respiratory and urinary systems.

The provided 510(k) summary (K102408) for the DRGEM Corporation's DIAMOND-5A, 6A, 8A Digital Diagnostic X-ray System does not contain information related to specific acceptance criteria for device performance or a study demonstrating the device meets such criteria in terms of diagnostic accuracy or clinical effectiveness.

Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Sedecal X-Plus LP Plus Digital, K090238) by showing compliance with electrical, mechanical, environmental safety, and EMC standards, which are considered sufficient for this type of device in the 510(k) pathway.

Therefore, many of the requested details about acceptance criteria, clinical studies, ground truth, and expert involvement are not present in the provided document.

Here's a breakdown of what can be extracted based on the input:

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

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

• Not Applicable / Not Provided. The submission details compliance with engineering and safety standards, not a clinical performance study with a test set of images or patients.

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

• Not Applicable / Not Provided. No clinical performance study requiring ground truth establishment is mentioned.

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

• Not Applicable / Not Provided. No clinical performance study requiring adjudication is mentioned.

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

• No. This is a traditional X-ray imaging system, not an AI-assisted diagnostic device. A MRMC study was not conducted or mentioned.

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

• No. This is a traditional X-ray imaging system, not an algorithm.

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

• Not Applicable / Not Provided. No clinical performance study requiring ground truth is mentioned.

8. The sample size for the training set

• Not Applicable / Not Provided. This is not an AI/machine learning device that would typically have a "training set."

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

• Not Applicable / Not Provided. This is not an AI/machine learning device.

Summary of the Study (as described in the 510(k) summary):

The "study" described in this 510(k) summary is primarily a technical verification and validation (V&V) against recognized electrical, mechanical, environmental, and EMC safety and performance standards (EN/IEC 60601 series). The manufacturer performed these tests to demonstrate that the DIAMOND-5A,6A,8A system operates safely and effectively as an X-ray imaging system, and is substantially equivalent to the predicate device. The results of these tests were deemed "satisfactory," indicating compliance with the standards, which serves as the basis for the safety and effectiveness conclusion. There is no mention of clinical trials or studies related to diagnostic accuracy or clinical outcomes.

Ask a specific question about this device

The MAK 1500, MAK 2000, MAK 3000 Digital Diagnostic X-Ray System (STATIONARY). (Digital Diagnostic X-Ray Systems) are intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position.

The MAK 1500 employs a ceiling mounted tubehead/collimator combination made by Suinsa, the NOVA . The system has one digital panel inside the universal bucky in the chest stand. It employs the Suinsa NBS-2100 Universal Bucky. The MAK 2000 uses a conventional vertical column mount and adds a Suinsa NET-4100 table. The MAK 3000, like the MAK 1500, employs a ceiling mount and universal bucky in the chest stand and adds the Suinsa NET-4100 table with a digital panel mounted inside. The digital pancl is the same one we supplied in K080582, manufactured by DRTcch Corporation (K080064) and the software is also unchanged.

The provided text is a 510(k) summary for a Digital Diagnostic X-Ray System (MAK 1500, MAK 2000, MAK 3000) and an FDA clearance letter. It describes the device, its intended use, and its equivalence to predicate devices. However, this document does not contain information about specific acceptance criteria or a study proving that the device meets such criteria in terms of performance metrics.

The 510(k) summary primarily focuses on:

• Identification of the Device: Proprietary-Trade Name, Classification Name, Product Codes, Common/Usual Name.
• Equivalent legally marketed devices: Stating it's a modified device based on K080582.
• Indications for Use: What the device is intended to be used for (diagnostic radiographic exposures of various body parts in adults and pediatrics).
• Description of the Devices: Details about the components (tubehead, bucky, digital panel, software).
• Safety and Effectiveness, comparison to predicate device: A general statement that "The results of bench and standards testing indicates that the new device is as safe and effective as the predicate devices."

The FDA letter confirms the substantial equivalence determination but does not delve into specific performance data or acceptance criteria.

Therefore, based solely on the provided text, I cannot complete the requested tables and sections related to acceptance criteria, detailed study information, sample sizes, expert qualifications, or ground truth establishment. The document does not contain this level of detail regarding performance studies.

Here's what I can extract and state based on the provided text, noting the missing information:

Description of Device and General Regulatory Context:

• Device Name: Model MAK 1500, MAK 2000, MAK 3000 Digital Diagnostic X-Ray System (Stationary).
• Manufacturer: MedicaTech USA
• 510(k) Number: K082798
• Indications for Use: Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position.
• Predicate Device: K080582 (The current device represents a variation of the tubehead mounting method described in this 510(k)).

Missing Information from the Provided Text:

1. Table of Acceptance Criteria and Reported Device Performance:

• Not provided in the document. The document states "The results of bench and standards testing indicates that the new device is as safe and effective as the predicate devices," but no specific performance metrics, acceptance criteria, or comparative data are listed.

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

• Not provided in the document. No information on a specific "test set" for performance evaluation (e.g., number of images, patient demographics, country, retrospective/prospective nature) is available.

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

• Not provided in the document. There is no mention of expert reviews or ground truth establishment for a test set.

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

• Not provided in the document. No adjudication method is mentioned as there is no described test set evaluation.

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/Not provided. This is a diagnostic imaging system (X-ray machine), not an AI-assisted diagnostic software. Therefore, an MRMC study comparing human readers with/without AI assistance would not be relevant to this specific device's clearance. The document does not describe any AI component.

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

• Not applicable/Not provided. As stated above, this is an X-ray system, not an algorithm, so a standalone algorithm performance evaluation is not relevant or described.

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

• Not provided in the document. No ground truth type is mentioned as no specific performance study is detailed.

8. The sample size for the training set:

• Not applicable/Not provided. As this is a hardware X-ray system and not an AI/machine learning algorithm, there is no "training set" in the conventional sense.

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

• Not applicable/Not provided. (See point 8).

Conclusion:

The provided 510(k) summary and FDA letter pertain to the substantial equivalence of a general-purpose digital X-ray system. The documentation focuses on hardware specifications, intended use, and comparison to a predicate device based on bench and standards testing for safety and effectiveness. It does not provide the detailed performance study information, acceptance criteria, sample sizes, expert qualifications, or ground truth establishment methods typically found for software algorithms or devices requiring specific diagnostic accuracy claims. For an X-ray system, "safety and effectiveness" often refers to image quality (resolution, contrast, dose), electrical safety, mechanical safety, and compliance with performance standards, rather than diagnostic accuracy metrics of a distinct algorithm.

Ask a specific question about this device