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The Jumong General is 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, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

This device represents a combination of an already cleared solid state digital x-ray acquisition panel with software and diagnostic x-ray components required to make a complete system. Film cassettes may be employed in place of the x-ray generator has been changed to a Delta Electronics Delta DMP 100R The collimator has been changed to a Fairy Medical Electronics model CRUX FR04. The tubehead has been changed to a Hangzhou Kailong Medical Instruments Co., Ltd H1074X. The system complies with the CDRH Radiological Health performance standard in the Code of Federal Regulations, as well as the voluntary IEC standards IEC 60601-1 and IEC 60601-1-2.

The provided text is a 510(k) Pre-market Notification document for the "Jumong General" stationary x-ray system. This document is a submission to the FDA demonstrating that a new device is substantially equivalent to a legally marketed predicate device.

It's important to understand that in this context, "acceptance criteria" and "study that proves the device meets the acceptance criteria" refer to the demonstration of substantial equivalence, primarily through non-clinical performance testing and comparison to an established predicate device, rather than a clinical study with human-in-the-loop performance measurement of an AI algorithm.

The document states:

• "5. Safety and Effectiveness, comparison to predicate device. This combination device has the same indications for use and very similar technological characteristics as the predicate device, and employs already 510(k) cleared digital panels and software."
• "No software modifications were made to the imaging chain."
• "8. Summary of clinical testing: Not applicable."

This clearly indicates that this submission does not involve an AI algorithm that requires a separate performance study with human readers or standalone algorithm performance assessment. The device is a conventional x-ray imaging system, albeit with some updated components compared to its predicate.

Therefore, many of the requested points related to AI performance, such as MRMC studies, standalone AI performance, ground truth establishment for AI training/testing, and expert adjudication, are not applicable to this specific submission.

However, I can still interpret how the concept of "acceptance criteria" and "proof" apply to this device based on the provided text, focusing on its non-clinical performance and substantial equivalence demonstration.

Acceptance Criteria and Study for Jumong General X-Ray System

Given that the Jumong General is a stationary x-ray system (Product Code: KPR, MQB) and not an AI-powered diagnostic device, the "acceptance criteria" and "proof" focus on demonstrating substantial equivalence to a previously cleared predicate device (K150816, Jumong Series Stationary Radiographic System). This is achieved primarily through non-clinical performance testing, safety standards compliance, and direct comparison of functional characteristics. The document explicitly states "No software modifications were made to the imaging chain," and "Clinical testing: Not applicable."

The "acceptance criteria" for demonstrating substantial equivalence primarily revolve around meeting recognized performance standards, electrical safety, EMC compliance, and demonstrating comparable image quality and intended use to the predicate device.

1. Table of Acceptance Criteria and Reported Device Performance

The new components are:

• Generator: Delta Electronics DMP 100R (same kVp range as CPI CMP 200 DR predicate)
• Collimator: Fairy Medical Electronics CRUX FR04 (changed from Ralco Model R225)
• Tubehead: Hangzhou Kailong Medical Instruments Co., Ltd H1074X (changed from Varian RAD14)

Digital Panel Models, Image acquisition panel specifications, DICOM, Image acquisition software, and Power Source are all SAME as predicate. (page 5, comparison chart).

Conclusion: "This combination device has the same indications for use and very similar technological characteristics as the predicate device, and employs already 510(k) cleared digital panels and software." (page 4, section 5) |
| Safety & Performance Standards | Compliance with relevant US Radiation Safety Performance Standards and IEC standards for medical electrical equipment. | - Conforms to the US Performance Standard. (page 6, section 7)

• New generator complies with: IEC 60601-2-54:2009+A1+A2, IEC 60601-1:2005+Corrigendum 1+Corrigendum 2+A1, IEC 60601-1-3:2008+A1, and IEC 60601-1-6:2010+A1. (page 6, section 7)
• EMC testing complies with IEC 60601-1-2:2014. (page 6, section 7)
• New collimator tested for compliance with EN/IEC 60601-2-54 for radiation leakage. (page 6, section 7)
• New tubehead tested to IEC 60613:2010 and IEC 60336:2005. (page 6, section 7)
• "Every unit is tested for electrical safety, input power, display of operation and exposure factors, collimator operation, reproducibility, and accuracy." (page 6, section 7) |
  | Image Quality | Image quality should be diagnostically acceptable and comparable to the predicate device. | "Test images were acquired which showed excellent diagnostic quality." (page 6, section 7) |
  | Risk Analysis | Assessment of risks associated with modifications and demonstration of acceptable risk profile. | "A risk analysis was performed with regard to the modifications. No software modifications were made to the imaging chain." (page 6-7, section 7) The conclusion states the device is "as safe and effective as the predicate device." (page 7, section 9) |

As this is a conventional X-ray system submission and not an AI/CADe device, the following points are largely "Not Applicable."

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

• Not Applicable in the traditional sense of a clinical test set for an AI algorithm. The "test set" here refers to the physical system undergoing non-clinical verification and validation tests. The document references "test images" acquired for image quality assessment, but the sample size or specific provenance of these images is not detailed as it would be for a clinical AI study. The testing is described as non-clinical ("integration and image quality testing").

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

• Not Applicable. Ground truth, in the context of diagnostic accuracy for AI, is not relevant here. The "diagnostic quality" of images was assessed, presumably by qualified personnel, but this is a standard engineering and quality assurance assessment for image generators, not an AI ground truth establishment process.

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

• Not Applicable. This pertains to clinical AI studies for diagnostic accuracy.

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 is specific to AI-assisted diagnostic devices. The document explicitly states "Summary of clinical testing: Not applicable."

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

• Not Applicable. This is specific to the performance of an AI algorithm. The device is a hardware x-ray system, and no AI algorithm's standalone performance is being evaluated.

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

• Not Applicable. Ground truth for diagnostic accuracy is not relevant here as it's a hardware device demonstrating fundamental imaging capability and safety, not a diagnostic interpretation tool.

8. The sample size for the training set

• Not Applicable. There is no AI algorithm being trained for this device as per the submission details ("No software modifications were made to the imaging chain").

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

• Not Applicable. As there is no AI algorithm being trained by the applicant, this point is not relevant.

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The Jumong Series Stationary Radiographic System is 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. Not for mammography.

This device represents a new combination of an already cleared solid state digital x-ray acquisition panel with software and diagnostic x-ray compnents required to make a complete system. Film cassettes may be employed in place of the digital panel. The purchaser can select from one of four configurations. The x-ray generator is a CPI CMP 200DR. The x-ray tubes are supplied by Varian (RAD-14), and the collimator is the Ralco R225 ACS DHHS. The system complies with the CDRH Radiological Health performance standard in the Code of Federal Regulations, as well as the voluntary IEC standards IEC 60601-1 and IEC 60601-1-2. All major components are either UL or CSA listed.

The provided text is a 510(k) summary for the "Jumong Series Stationary Radiographic System." It primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing specific acceptance criteria and performance data from a standalone study. Therefore, much of the requested information cannot be extracted directly from this document.

Here's what can be gathered:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria for image quality or clinical performance that the device was tested against. Instead, it relies on demonstrating that the device meets general safety and performance standards, and that its components (like digital panels) are previously cleared. The "performance" assessment is framed as "bench, safety test, and software validation documentation indicates that the new device is as safe and effective as the predicate device" and that the device "conforms to US Performance Standards" and various IEC/NEMA voluntary standards.

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

The document mentions that "Clinical images were provided," but does not specify the sample size, data provenance (e.g., country of origin), or whether they were retrospective or prospective. It explicitly states these images "were not necessary to establish substantial equivalence."

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 in the document. The phrase "clinical images were provided" suggests some form of evaluation but no details on expert involvement or ground truth establishment for a test set.

4. Adjudication Method:

This information is not provided in the document.

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

No MRMC comparative effectiveness study is mentioned in the document. The submission focuses on substantial equivalence based on technical characteristics and safety/performance standards, rather than a clinical trial comparing human reader performance.

6. Standalone Performance Study:

The document implies that images were used to show the "complete system works as intended," suggesting some form of standalone evaluation. However, it does not describe a formal standalone performance study with specific metrics, acceptance criteria, or a detailed methodology. The "non-clinical testing" section primarily covers integration, bench, safety, and software validation.

7. Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for any clinical image evaluation, given that the clinical images were "not necessary to establish substantial equivalence."

8. Sample Size for the Training Set:

This information is not applicable as the document describes a device (X-ray system), not an AI algorithm that would typically require a training set.

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

This information is not applicable as the document describes a device (X-ray system), not an AI algorithm.

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Radlink GPS is intended for digital image capture use in general radiographic examinations, whenever conventional screen-film systems may be used. Radlink GPS allows imaging of the pelvis, knee, skull, chest, shoulder, spine, abdomen and extremities. The digital images are transmitted from the panel or from a connection to PACS via computer networks or from a video input port to a personal computer (PC) where they may be displayed, processed, altered, overlaid with templates, compressed for archiving or transmission via computer networks to other medical facility sites. Not for mammography.

The Radlink GPS system represents the straightforward integration of digital x-ray receptor panels with their own FDA 510(k) clearance and our acquisition software that has been previously cleared by the FDA for use with our Radlink CR-Pro Solid State X-ray Imager (K052938) and Radlink LaserPro-16 (K020243). The Radlink GPS is compatible with the following digital x-ray receptor panels:

• . Vieworks VIVIX-S (K120020) and VIVIX-S Wireless (K122865)
• . Trixell Artpix Mobile EZ2GO with portable PIXIUM 3543EZ (K110849)
• -Perkin Elmer XRpad 4336 MED (K140551)
  Radlink GPS is a Digital Radiography (DR) system, featuring an integrated flat panel digital detector (FPD). Radlink GPS is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advantages of digital radiography for a filmless environment and improves cost effectiveness. The major functions and principle of operations of the Radlink CR Pro acquisition software and PACS were not changed. The digital copies are transmitted to an internal personal computer (PC) where they may be displayed, processed for archiving or transmission via computer networks to other medical facility sites. Images can be rotated, flipped, coomed, window level, overlaid and annotated (markers, text, freestyle, line distance measurements, angles). Digital images may be received via the flat panel digital detector (FPD), from a connection to PACS via computer networks or from a video input port.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Radlink GPS device:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state formal acceptance criteria with numerical targets for performance metrics (e.g., sensitivity, specificity, image quality scores). Instead, the "acceptance criteria" appear to be implicit in demonstrating that the device is "as safe and effective as products currently legally for sale in the USA" and "substantially equivalent to predicate devices."

The reported device performance primarily focuses on functionality, safety, and diagnostic quality rather than specific quantitative performance metrics.

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

• Test Set Sample Size: The document states that "Human images were obtained from each of the panels." It does not specify the exact number of human images or cases used for this review.
• Data Provenance: Not explicitly stated. Given the context of seeking FDA clearance in the USA, it's likely the images were acquired in a medical setting, possibly in the USA, but no specific country or retrospective/prospective nature is mentioned.

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

• Number of Experts: "a Board Certified Radiologist." (Singular)
• Qualifications of Experts: "Board Certified Radiologist." No specific number of years of experience is provided.

4. Adjudication Method for the Test Set

• Adjudication Method: "reviewed by a Board Certified Radiologist." There is no mention of multiple readers or an adjudication process (e.g., 2+1, 3+1). The assessment appears to be a single-reader evaluation.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The document focuses on demonstrating substantial equivalence primarily through functional comparison, technical performance verification, and a limited clinical review by a single radiologist. There is no mention of comparing human readers with and without AI assistance. The device itself is an image acquisition and processing system, not an AI diagnostic aid.

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

• Standalone Performance: The Radlink GPS is a digital radiography system, not an AI algorithm in the context typically discussed for standalone performance (e.g., detecting disease). Its "performance" is inherently linked to image acquisition and display. The "algorithm" here refers to the acquisition and processing software, and its standalone performance is tested through aspects like "conformance to its defined specifications" using phantoms, software validation, and DICOM compatibility. While not referred to as "standalone AI performance," the non-clinical testing and software validation serve a similar function for the core components of the system.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the diagnostic quality assessment was based on expert consensus (from a single Board Certified Radiologist) who evaluated the human images and found them to be of "good diagnostic quality." For other aspects like image acquisition and technical specifications, the ground truth was based on physical measurements (e.g., gray-scale wedge, line resolution phantom) against predefined technical standards.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable in the context of this submission. The Radlink GPS is described as an integration of existing cleared components (digital panels and acquisition software that was previously cleared). It is not an AI/machine learning model that undergoes a distinct "training phase" on a dataset in the way a diagnostic algorithm would. The software was previously cleared (K052938, K020243), implying its development and validation occurred prior to this submission.

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

• Ground Truth for Training Set: Not applicable. As mentioned above, this is an integration of pre-cleared components, not a new AI algorithm requiring a dedicated training set and associated ground truth establishment for that training. The development and validation of the constituent software and hardware components would have involved their own respective "ground truths" at the time of their original clearance.

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ViVIX-S with VXvue is indicated for digital imaging solution designed for general radiographic system for human anatomy. It is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. Not to be used for mammography and/or for fluoroscopy.

ViVIX-S with VXvue is a digital X-ray flat panel detector which has 43x43cm (FXRD-1717SA, FXRD-1717SB) or 35.8x43cm (FXRD-1417SA, FXRD-1417SB) imaging area. The device intercepts x-ray photons and the scintillator emits visible spectrum photons that illuminate an array of photo (a-SI)-detectors that create an electrical signals. After the electrical signals are generated, it is converted to digital value, and the images will be displayed on monitors. This device should be integrated with an operating PC and an X-Ray generator to utilize as digitalizing X-ray images and transfer for radiography diagnostic. Advanced digital imaging process allows considerably efficient diagnosis, all kind of information management, and sharing of image information on network.

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

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document states that the non-clinical and clinical studies "show that the ViVIX-S with VXvue is substantially equivalent to the predicate devices in the market." For the clinical study, it specifically notes "no significant differences between the images." This implies the acceptance criteria for these metrics were met by demonstrating equivalence or lack of significant difference compared to the predicate. The specific numerical thresholds for "acceptance criteria" are not provided in this document.

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

• Sample Size (Test Set): 30 clinical images.
• Data Provenance: Not explicitly stated regarding country of origin or whether it was retrospective or prospective. It is implied to be clinical data used for comparison.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document only mentions a "concurrence study" comparing images, but does not detail the methodology for establishing ground truth or who performed the comparison.

4. Adjudication Method for the Test Set

• Not specified. The document simply states "A concurrence study of 30 clinical images was conducted to compare the performance... There were no significant differences." It doesn't describe the adjudication process if multiple reviewers were involved or how disagreements were resolved.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size.

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly stated or described. The clinical study was a concurrence study comparing images from the new device to the predicate, not an assessment of human reader performance with or without AI assistance.

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

• While the device itself is a digital X-ray flat panel detector (hardware), and the "VXvue" part is advanced digital imaging process, the study described is a comparison of images produced by the device against a predicate, not an "algorithm-only" performance evaluation in the context of AI. The "advanced digital imaging process" implies software components, but its standalone diagnostic performance is not detailed separately from the hardware's image acquisition.

7. The type of ground truth used

• The implicit "ground truth" for the clinical study was the image quality and diagnostic information provided by the predicate device (K120020). The study aimed to show "no significant differences" between the images of the proposed device and those of the legally marketed predicate. It's a comparison to an established device, rather than an independent expert consensus, pathology, or outcomes data.

8. The sample size for the training set

• Not applicable/Not specified. This device is a digital X-ray detector, not an AI/ML algorithm that requires a training set in the conventional sense. The "advanced digital imaging process" is mentioned, but there is no indication of a machine learning component requiring a distinct training set. The study focuses on the performance of the imaging hardware and its processing in comparison to the predicate.

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

• Not applicable/Not specified, as no training set for an AI/ML algorithm is described in this submission.

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