Search Results

The GC85A 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 GC85A digital X-ray imaging system is a stationary x-ray system designed for general radiography and used to capture images by transmitting X-ray to a patient's body. The Xray 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 S-station, which is the Operation Software (OS) of Samsung Digital Diagnostic X-ray System, and save in DICOM file, a standard for medical imaging. The captured images are tuned up by an Image Post-processing Engine (IPE) which is exclusively installed in S-station, and sent to the Picture Archiving & Communication System (PACS) sever for reading images.

The GC85A digital X-ray imaging system was previously cleared with K172229, and through this premarket notification, we would like to add more configurations in the previously cleared GC85A as three High Voltage Generators and two detectors are newly added, and three software features are newly added as stated below.

S-Enhance is renamed from Tube & Line Enhancement (TLE), which was cleared before with the predicate device GM85 at K171119, to enhance visibility of tubes and lines and provide enhanced images separately from original images. In this submission, the scope of S-Enhance is expanded from tubes and lines on chest images to foreign body (e.g. tubes, lines and needles) and urinary stones on chest, abdomen, and L-spine. And Pediatric Exposure Management (PEM), which was cleared before with the predicate device GM85 at K171119, is subdivided patient size and exposure conditions especially for pediatric patients based on weight and protocols, and Remote View to enable the images on the device is being displayed on the remote monitor. It was determined that the level of concern for the software contained in the GC85A digital X-ray imaging system was Moderate in accordance with the FDA guidance, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Device".

The provided document, a 510(k) Premarket Notification for the Samsung GC85A digital X-ray imaging system, primarily focuses on demonstrating substantial equivalence to predicate devices rather than establishing novel acceptance criteria or presenting an in-depth study proving a device meets specific performance criteria for new features. The document describes additions and changes to an already cleared device (GC85A, K172229) and incorporates features from another predicate device (GM85, K171119).

However, based on the Clinical data section (page 8), we can infer the following about acceptance criteria and the study conducted for S-Enhance and the new detectors:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in a table format for new features. Instead, it relies on a qualitative assessment of "equivalence" to predicate devices. For S-Enhance and the new detectors, the acceptance criteria are implicitly based on achieving equivalent image quality to the predicate devices and ensuring S-Enhance provides "clear visibility" for foreign bodies.

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

• Test Set Sample Size: Not explicitly stated. The document mentions "Anthropomorphic phantom images were provided." This indicates that the images used in the evaluation were of phantoms (physical models representing human anatomy), not actual patient data. The exact number of phantom images is not specified.
• Data Provenance: The data is from "Anthropomorphic phantom images." This implies a controlled, laboratory-based study. No information about country of origin is provided, but Samsung Electronics Co., Ltd. is based in the Republic of Korea. It is a prospective study as these images were generated specifically for this evaluation.

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

• Number of Experts: Not explicitly stated. The document mentions "professional radiologists."
• Qualifications of Experts: "professional radiologists." Specific experience (e.g., "10 years of experience") is not provided.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. The phrasing "evaluated by professional radiologists and found to be equivalent" suggests a consensus or majority opinion approach, but the specific method (e.g., 2+1, 3+1) is not detailed. The mention of "average score considering the standard deviation of image quality evaluation" suggests a quantitative assessment that might have been averaged across multiple readers, but the method of handling disagreements is not described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size

• A formal MRMC comparative effectiveness study to quantify human reader improvement with vs. without AI assistance was not described in the provided text. The study described focuses on whether the device's image quality (including S-Enhance) is equivalent to predicate devices, and whether S-Enhance provides clear visibility. It does not measure the impact of AI assistance on human reader performance.

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

• The document implies that the S-Enhance feature (an algorithm) was evaluated in terms of its ability to "generate a companion image which provide clear visibility for foreign bodies." This is a form of standalone evaluation of the algorithm's output. However, it's not a standalone diagnostic performance study (e.g., sensitivity/specificity of an AI model to detect foreign bodies). The evaluation relies on human radiologists assessing the quality and visibility provided by the algorithm's output.

7. The Type of Ground Truth Used

• For the phantom images, the "ground truth" for the new detectors and S-Enhance would be the inherent properties and known structures within the anthropomorphic phantoms. The "equivalence" assessment by radiologists serves as the validation of how well the device's images represent this known ground truth. It's essentially an expert consensus on image quality and perceptibility of structures in controlled phantom images.

8. The Sample Size for the Training Set

• Details about the training set for S-Enhance (or any other software feature) are not provided in this document. Given that S-Enhance was "renamed from Tube & Line Enhancement (TLE), which was cleared before with the predicate device GM85 at K171119," it's likely that any training for the core functionality occurred prior to this submission and was part of the K171119 clearance. This submission expands the scope of S-Enhance.

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

• As the training set details are not provided, information on how its ground truth was established is also not available in the document.

Ask a specific question about this device

The GR40CW Digital X-ray Imaging System is intended for use in general projection radiographic applications wherever conventional screen-film systems or CR systems may be used. This device is not intended for mammographic applications.

The GR40CW digital X-ray imaging system consists of Detector, Power supply box, Battery pack, Battery charger, Access point, CIB(Control Interface Box), Workstation, Barcode scanner, Main cable and software for image acquisition and image processing and does not include the X-ray generator. 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 before 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 GR40CW digital X-ray imaging system was previously cleared with K180543, and through this premarket notification, we would like to add more configurations in the previously cleared GR40CW as three detectors are newly added, and some software features called as SimGrid, S-Enhance, BSI (Bone Suppression Image), Remote View and manual Stitching are newly added as stated below. SimGrid software option, cleared with K171119. is able to compensate the contrast loss due to scatter radiations, primarily acquisitions without a physical anti-scatter grid. BSI software option suppresses bone anatomy and S-Enhance is renamed from Tube & Line Enhancement (TLE), which was cleared before with the predicate device GM85 at K171119, to enhance visibility of tubes and lines and provide enhanced images separately from original images. In this submission, the scope of S-Enhance is expanded from tubes and lines on chest images to foreign body (e.g. tubes, lines and needles) and urinary stones on chest, abdomen, and L-spine. And Manual Stitching to capture a body part that is larger than the detector's by capturing multiple images and Remote View function to remote access to view the current image on the workstation through a web browser. It was determined that the level of concern for the software contained in the GR40CW digital X-ray imaging system was Moderate in accordance with the FDA guidance for the Content of Premarket Submissions for Software Contained in Medical Device".

Here's a breakdown of the acceptance criteria and study information for the GR40CW device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly list a table of "acceptance criteria" with pass/fail thresholds in the typical sense for product validation. Instead, it focuses on demonstrating substantial equivalence to predicate devices. The performance evaluation is primarily comparative.

However, based on the non-clinical and clinical data descriptions, we can infer the key performance areas evaluated and the general finding of equivalence.

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

• Test Set for New Detector and S-Enhance (Clinical Data):
  • Sample Size: Not explicitly stated as a number of images or patients. It mentions "Anthropomorphic phantom images were provided"; and "these images were not necessary to establish substantial equivalence... but they provide further evidence...".
  • Data Provenance: Not explicitly stated (e.g., country of origin). The study used "Anthropomorphic phantom images," which are specialized phantoms designed to mimic human anatomy for imaging studies. This is a controlled, laboratory-based setup rather than real patient data. It is a prospective study design as the images were "provided" for evaluation.

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

• Number of Experts: Not explicitly stated. The document mentions "They were evaluated by professional radiologists." The exact number (e.g., 3, 5, 10) is not provided.
• Qualifications: "Professional radiologists." No specific years of experience or subspecialty are listed.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. The text only says "They were evaluated by professional radiologists." This implies individual evaluation, but it doesn't describe a consensus or majority rule method if multiple radiologists were involved, nor does it specify if a single radiologist was the sole evaluator.

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

• MRMC Study: No, a formal MRMC comparative effectiveness study, comparing human readers with AI assistance versus without AI assistance, was not explicitly detailed or performed as part of this submission. The clinical data section focuses on "Anthropomorphic phantom images" evaluated by radiologists to demonstrate equivalence of the device (including the S-Enhance feature) to predicate devices, not on the improvement of human performance using the AI feature.
• Effect Size: Not applicable, as an MRMC study demonstrating human reader improvement with AI assistance was not described.

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

• Standalone Performance: The non-clinical data provides standalone performance metrics for the device components like MTF and DQE (measured by IEC 62220-1), which characterize the imaging chain's inherent physical performance.
• For the software features like S-Enhance, the clinical data describes evaluations by radiologists of images generated by the software. While radiologists evaluate the output, the core performance of the S-Enhance algorithm in creating the companion images is assessed based on their ability to "provide clear visibility for foreign bodies such as lines, and needles, and urinary stones." This suggests a form of standalone performance evaluation of the algorithm's output, even if human experts are interpreting that output. The submission aims to show the complete system works as intended and that S-Enhance produces images with desired characteristics.

7. The Type of Ground Truth Used

• Ground Truth Type: For the clinical evaluation regarding the new detector and S-Enhance, the ground truth was expert consensus/opinion (professional radiologists) on the "image quality evaluation" and the "clear visibility for foreign bodies... and urinary stones" in images generated from anthropomorphic phantoms. Phantoms provide a known truth in terms of implanted objects.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not provided or discussed in this document. This submission pertains to modifications to an already cleared device, and the focus is on the performance of the new detectors and expanded software features (S-Enhance). Details about the training data for the S-Enhance or other software algorithms are not included.

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

• Training Set Ground Truth Establishment: Not provided or discussed, as the training set sample size was not mentioned.

Ask a specific question about this device

The GM85 Digital Mobile 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 GM85 Digital Mobile X-ray imaging 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 on the S-Station, which is the Operation Software (OS) of Samsung Digital Diagnostic X-ray System, and save in DICOM file, a standard for medical imaging. The captured images are tuned up by an Image Post-processing Engine (IPE) which is exclusively installed in S-Station, and send to the Picture Archiving & Communication System (PACS) sever for reading images.

The GM85 Digital Mobile X-ray imaging System was previously cleared with K180543, and through this premarket notification, we would like to add more configurations in the previously cleared GM85 as a fixed column type and two detectors are newly added, and three software features are newly added as stated below.

S-Enhance is renamed from Tube & Line Enhancement (TLE), which was cleared before with GM85 at K171119, to enhance visibility of tubes and lines and provide enhanced images separately from original images. In this submission, the scope of S-Enhance is expanded from tubes and lines on chest images to foreign body (e.g. tubes, lines and needles) and urinary stones on chest, abdomen, and L-spine. And Manual Stitching to capture a body part that is larger than the detector's by capturing multiple images and Remote View function to remote access to view the current image on the workstation through a web browser. It was determined that the level of concern for the software contained in the GM85 Digital Mobile X-ray imaging System was Moderate in accordance with the FDA guidance, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Device".

The provided text does not contain detailed acceptance criteria or a comprehensive study report specifically outlining acceptance criteria with reported device performance metrics in a tabular format. However, it does discuss performance characteristics, non-clinical data, and clinical data used to establish substantial equivalence.

Here's an attempt to extract and infer the information based on the provided document.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria. Instead, it focuses on demonstrating substantial equivalence to a predicate device. The performance is generally reported as "equivalent to the predicate devices" or "satisfying the standards."

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

• Test Set Sample Size: The document does not specify a numerical sample size for the clinical image evaluation. It only mentions "Anthropomorphic phantom images were provided."
• Data Provenance: The document does not specify the country of origin of the data. The study involved "Anthropomorphic phantom images." It is a prospective evaluation using phantoms, rather than retrospective patient data.

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

• Number of Experts: "a professional radiologist" (singular)
• Qualifications of Experts: The document specifies "a professional radiologist." It does not provide additional details such as years of experience.

4. Adjudication Method for the Test Set

The document states that the phantom images "were evaluated by a professional radiologist." It does not mention any adjudication method (e.g., 2+1, 3+1) involving multiple readers or a consensus process.

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 multi-reader multi-case (MRMC) comparative effectiveness study focusing on human readers improving with AI vs. without AI assistance was not explicitly described or reported. The study focused on demonstrating the equivalenc of the device's image quality and the S-Enhance feature's ability to provide clear visibility.

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

The S-Enhance feature and new detectors were evaluated, suggesting an assessment of the algorithm's output (the enhanced image) and the detector's image characteristics. While not a purely "standalone algorithm" in the sense of a diagnostic AI making decisions, the evaluation of the S-Enhance feature generating "companion images which provide clear visibility" effectively assesses the algorithm's performance without direct human interaction during the image generation process. The radiologist then evaluates these generated images.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

For the clinical data, the ground truth was based on the inherent properties of the anthropomorphic phantom images, which simulate human anatomy and disease conditions. The radiologist's evaluation of the clarity and visibility in these phantom images served as the assessment against this simulated ground truth.

8. The Sample Size for the Training Set

The document does not provide any information regarding the sample size used for the training set for features like S-Enhance.

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

The document does not provide details on how the ground truth for training data was established for the S-Enhance feature or any other software components. It mentions that S-Enhance is the same image processing technology as a previously cleared feature (TLE) and extends its scope. This implies that previous development and potentially associated training (if applicable to the algorithm) would have been used.

Ask a specific question about this device

The GU60A & GU60A-65 Digital X-ray Imaging Systems are 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 GU60A & GU60A-65 digital X-ray imaging systems are to be used to take and store image for diagnosis of patients. It consists of HVG(High voltage generator), U-arm positioner, Detector, X-ray tube, Collimator, AEC(Auto Exposure Control), DAP(Dose Area Product), CIB(Control Interface Box), Remote controller, Grid, Barcode scanner and Autostitching stand.

These systems are 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 GU60A & GU60A-65 digital X-ray imaging systems is stationary, and it was previously cleared under K151685. The software features cleared with K171119, SimGrid, BSI (Bone Suppression Image) and TLE (Tube & Line Enhancement), is added to the predicate x-ray system (K151685).

The software features called as SimGrid, BSI (Bone Suppression Image) and TLE (Tube & Line Enhancement) is a post-image processing software option which provides companion images to assist diagnosis in addition to the images obtained from normal diagnosis protocol.

The SimGrid software option is able to compensate the contrast loss due to scatter radiations, primarily acquisitions without a physical anti-scatter grid.

The BSI software option suppresses bone anatomy and the TLE software option enhances visibility of tube and catheter features in a companion image that is delivered in addition to the original diagnostic image.

These software features are designed to be exclusively installed in S-station, SAMSUNG digital X-ray operation software, while it uses the radiological image as an input and do not depend on how the image is acquired or which radiology device is used.

The provided document does not contain details about specific acceptance criteria, a study proving the device meets those criteria, or reported device performance metrics in the format requested. The document is a 510(k) premarket notification summary for an X-ray imaging system, focusing on demonstrating substantial equivalence to predicate devices rather than providing detailed performance study results against specific acceptance criteria.

Therefore, many of the requested fields cannot be filled from the provided text.

Here's an analysis of what can be extracted:

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

• Acceptance Criteria: Not explicitly stated in the provided text. The document refers to conformance with various standards (ES 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-2-28, IEC 60601-2-54, ISO14971, 21CFR1020.30, 21CFR1020.31, IEC 62220-1) and a guidance document for wireless technology. It also states that all test results were "satisfying the standards." However, specific numerical acceptance criteria for performance (e.g., sensitivity, specificity, accuracy) for the software features are not detailed.
• Reported Device Performance: No specific performance metrics (e.g., sensitivity, specificity, accuracy) are reported for the device, or its software features (SimGrid, BSI, TLE). It only mentions that MTF and DQE measurements "show no difference in non-clinical testing data... from the predicate device."

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

• Not specified. The document states "The application of SimGrid, TLE, S-DAP and BSI, cleared with K171119, to the proposed device GU60A & GU60A-65 does not require clinical data." This implies no clinical test set was used for the substantial equivalence demonstration of these specific software features. Non-clinical testing data (MTF and DQE) likely used phantoms, but the sample size or provenance of that data is not 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 no clinical data or specific test set adjudicated by experts is described in the document.

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

• Not applicable as no clinical data or specific test set with expert adjudication is described 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 comparative effectiveness study is mentioned. The document explicitly states that clinical data was not required for the software features in question.

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

• The document implies that the software features (SimGrid, BSI, TLE) provide "companion images to assist diagnosis." This suggests an assistive role rather than a standalone diagnostic role, but no specific performance metrics for this assistance are provided. The fact that clinical data was not required for these features further supports that a standalone performance study was not conducted for this submission.

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

• Not applicable, as no clinical studies with established ground truth are described for the performance of the features. For non-clinical MTF and DQE measurements, the ground truth would be determined by the phantom properties and measurement protocols per IEC 62220-1.

8. The sample size for the training set

• Not specified. The document describes the device as a hardware system with added post-processing software features. There is no mention of an "AI" or "machine learning" algorithm in the modern sense that would require a distinct training set. The software features (SimGrid, BSI, TLE) are described as "post-image processing software option" rather than adaptive learning algorithms.

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

• Not applicable, as a training set for an AI/ML algorithm is not described.

Ask a specific question about this device