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The VFSS Pro Mobile system is intended for use by a qualified/trained medical professionals, who have full understanding of the safety information and emergency procedures as well of capabilities and function of the device. The device provides fluoroscopic imaging and is used for guidance and visualization during diagnostic radiographic, surgery, and interventional procedures. The device is to be used in healthcare facilities both inside of hospital, in a variety of procedures of the skull, spinal column, chest, abdomen, extremities, and at the medical professional the device may be used for other imaging applications on all patients except neonates (birth to one month) within the limits of the device. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. The system is not intended for mammography applications.

The VFSS Pro™ Mobile system is intended for use by a qualified/trained medical professionals, who have full understanding of the safety information and emergency procedures as well as the capabilities and functions of the device. The device provides fluoroscopic imaging and is used for guidance and visualization during routine fluoroscopic and image-guided procedures. The device is to be used in professional healthcare facilities, in a variety of image-guided procedures such as feeding tube and catheter insertion on pediatric patients except neonates (birth to one month). This device is not indicated for large/obese patients or interventional use. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. The system is not intended for mammography applications.

The VFSS Pro Mobile system is a mobile imaging system that can acquire, process, and display fluoroscopic images. It can be easily positioned within a room and moved from room within a facility. To provide the ability to perform fluoroscopic examinations as needed within a facility. The system employs a low-powered mono-block generator and a dynamic flat-panel detector so that it can be powered through a single-phase 120VAC power outlet. The imaging chain is powered by the Insight Agile DRF Digital Imaging System which allows the operator to view and enhance high-definition fluoroscopy images up to 30 fps. Images may be viewed and enhanced enabling the operator to bring out diagnostic difficult or impossible to see using conventional imaging techniques. Images can be stored locally for short term storage. The Insight Agile DRF Digital Imaging System enables the operator to produce hardcopy images with a laser printer or send images over a network for longer-term storage. The major system components include: a dynamic flat panel detector, monitors, and an image processor PC. This device employs either the Vieworks FXDD-1212G or the Rayence 1212FCA digital x-ray receptor panels (previously cleared, see Reference devices). The device software employed is from the Reference device Insight Agile DRF.

The provided text describes a 510(k) premarket notification for a medical device, the VFSS Pro Mobile Digital Imaging System. This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving a new level of clinical effectiveness or safety through extensive clinical trials as might be required for a PMA (Premarket Approval) device.

Therefore, the study conducted is primarily focused on non-clinical bench testing to demonstrate that the new device performs similarly and is as safe and effective as the predicate device. It does not involve clinical studies with human patients or AI-powered diagnostic algorithms that would require the specific acceptance criteria and study design elements typically found in AI/CADe (Computer-Assisted Detection/Diagnosis) device submissions (e.g., sensitivity, specificity, MRMC studies, expert ground truth adjudication).

Here's a breakdown based on the information provided, addressing the requested points:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence submission based on non-clinical testing, the "acceptance criteria" are primarily established against the performance of the legally marketed predicate device and relevant industry standards. The reported device performance is comparative.

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

• Test Set Sample Size: Not applicable in the traditional sense of a clinical test set with patient data. The "test set" here refers to the bench testing for hardware, software, electrical, mechanical, and radiation safety. This would involve specific setup configurations and phantoms in a lab environment. The document does not specify the number of phantom images or specific test runs; it only states that "phantom images were acquired" and "bench testing was performed."
• Data Provenance: Not applicable as clinical patient data was not used. The testing was laboratory/bench-based.

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

• Number of Experts: Not applicable. For this type of submission, "ground truth" relates to measurable physical parameters (e.g., radiation output, image quality metrics on phantoms, electrical safety measurements) compared to pre-defined standards or the predicate device's measured performance. There were no human expert interpretations for image diagnostic accuracy needed.
• Qualifications of Experts: The testing was performed by "Imaging Engineering" and the overall submission prepared by IMAGExRAY, LLC's "Principal Engineer." These are engineering and technical experts, not clinical experts for diagnostic accuracy.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable. As there were no human readers interpreting images for diagnostic accuracy, no adjudication method (e.g., 2+1, 3+1) was used.

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 submission explicitly states "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification. Bench testing was performed to assess the device safety and effectiveness." This indicates that human reader performance with or without AI assistance was not evaluated.

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

• Standalone Performance: Not applicable. The device is an imaging system, not an AI or algorithm-only device intended for standalone diagnostic assessment. Its performance is evaluated as an integrated system for image acquisition and display. There is no mention of a diagnostic algorithm within the device that would require a standalone performance study.

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for this submission is based on:
  • Engineering specifications and measurements: Comparing the device's measured performance (e.g., power output, image acquisition frames per second, pixel characteristics) against its own specifications and the predicate device's known characteristics.
  • Compliance with recognized industry standards: The device's ability to pass tests for electrical safety (IEC 60601 series), radiation control (21 CFR 1020.32), and software/cybersecurity guidance.
  • Phantom image analysis: Comparing the quality and characteristics of images produced using phantoms to those from the predicate device.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is not an AI/ML model that undergoes a "training" phase with a dataset. It's a hardware and software system for image acquisition.

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

• Training Set Ground Truth Establishment: Not applicable, as there is no AI/ML training set.

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The Insight Agile DRF is intended for use by a qualified/trained medical professionals, who have full understanding of the safety information and emergency procedures as well as the capabilities and functions of the device. The device provides fluoroscopic imaging and is used for guidance and visualization during routine fluoroscopic and image-guided procedures. The device is to be used in professional healthcare facilities, in a variety of image-guided procedures such as feeding tube and catheter insertion on pediatric patients and neonates (birth to one month). This device is not indicated for large/obese patients or interventional use. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. The system is not intended for mammography applications. (Rx Only)

The Insight Agile DRF Digital Imaging System is a modification of Insight Enhanced DRF, a previously cleared (K200396) fluoroscopic imaging chain employing a flatpanel digital detector (Vieworks 1212G) to replace the image intensifier and video camera on GE R&F systems (P500, Legacy and Advantx). This system has now been modified in the following manner: 1) the digital interface board (DIB) that provides communications with the GE systems has been replaced with a software program that utilizes virtual serial ports. 2) Another software program has been added to allow the system to communicate with and control a Source-Ray x-ray generator. The generator interface provides for Automatic Brightness Stabilization (ABS) control and optional manual control through a graphical user interface on the Insight Aqile image acquisition screen. 3) A second dynamic flat-panel detector (Rayence 1212FCA, K202722) has been integrated to provide an alternate digital detector. 4) the software risk assessment has been changed from minor to moderate. 5) the Indications for Use has been changed to that of the predicate device.

With these modifications, Insight Agile DRF is a fluoroscopic imaging chain that can acquire, process, and display fluoroscopic images when installed on any suitable positioning system in a fixed room, on a mobile or portable stand. Another purpose of this application is to expand the indications for use.

The Insight Agile DRF is an X-ray system, and the provided text does not define acceptance criteria typical for AI/ML-driven diagnostic devices (e.g., sensitivity, specificity, AUC). Instead, it focuses on bench testing and qualitative expert assessment for its substantial equivalence to a predicate device.

However, based on the provided text, I can extract information related to the device's performance, testing, and evaluation:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Test Set Sample Size: The text mentions a "series of fluoroscopic patient exam images" evaluated by a radiologist. However, a specific number for this series is not provided.
• Data Provenance: The provenance of the patient exam images is not explicitly stated (e.g., country of origin, retrospective or prospective). It is likely from a clinical setting where the OEC mobile c-arms are used for comparison.

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

• Number of Experts: One radiologist was used.
• Qualifications: The text identifies the expert simply as "A radiologist." No further details on their years of experience or sub-specialty are provided.

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

• The text describes a single radiologist's evaluation. There is no mention of an adjudication method involving multiple experts.

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. The study described is a qualitative assessment by a single radiologist comparing fluoroscopic images from the subject device to predicate devices (OEC 9800 and 9900). There is no AI assistance mentioned, and therefore, no effect size of human readers improving with AI vs without AI assistance is reported.

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

• The device described is an X-ray imaging system, not an AI/ML algorithm. The evaluation focuses on the image quality and performance of the hardware and integrated software. Therefore, the concept of a "standalone (algorithm only)" performance does not directly apply in this context. The bench testing and phantom image comparisons represent the device's inherent imaging capabilities.

7. The type of ground truth used:

• For the image quality assessment, the "ground truth" was the expert opinion/consensus of a single radiologist, who deemed the images "clinically acceptable for the intended use and fully comparable" to existing systems. For bench testing, the ground truth was based on established technical standards and predicate device performance (e.g., image quality characteristics from phantom images).

8. The sample size for the training set:

• The provided text does not describe an AI/ML training set. Therefore, there is no information on a training set sample size.

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

• As there is no mention of a training set for an AI/ML component, this information is not applicable and not provided in the text.

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Intended for use by a qualified/trained medical professionals, who have full understanding of the safety information and emergency procedures as well of capabilities and function of the device provides radiographic, multiradiographic and fluoroscopic imaging and is used for guidance and visualization during diagnostic radiographic, surgery, and interventional procedures. The device is to be used in healthcare facilities both inside and outside of hospital, in a variety of procedures of the skull, spinal column, extremities, and at the discretion of the medical professional the device may be used for other imaging applications on all patients except neonates (birth to one month) within the limits of the device. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. The system is not intended for mammography applications

The Virtual C DRF system is a mobile imaging system that acquire, process and display both static radiographic images and dynamic radiographic images such as multi-rad and fluoroscopy. Dynamic image acquisition is performed without the limitation of a mechanical linkage between the x-ray source and the x-ray detector. The mechanical linkage typical in existing dynamic imaging systems is either a c-arm or u-arm that ensures the alignment of the imaging components during image acquisition. The Virtual C DRF System features a novel collimator with built-in x-ray source to detector alignment software (Machine-Vision Collimator (MVC), combine they provide the technology for a "virtual c-arm" system. The novel MVC utilized four independent shutter to automatically position the radiation beam, so the area of exposure always remains within the confines of the active area of the detector. In addition, the angle and inclination of x-ray source is displayed to the operator. A visual display provides real time video images of the patient and a shaded area within the video images represent the location and size of the radiation beam with respect to the patient. As compared to our predicate device, there are three main changes: The digital receptor panel become a DRTECH brand panel, the generator changes from Sedecal to Source-ray, and and the collimator is changed from Colimar to a PortaVision "Machine Vision" collimator. An initial report was submitted for that collimator.

The provided document is a 510(k) Premarket Notification for the "Virtual C DRF Digital Imaging System." It focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study with an AI algorithm.

Therefore, the document does not contain the information requested regarding acceptance criteria for an AI-powered device, a study proving it meets these criteria, or details about expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance.

The document primarily discusses non-clinical testing (bench testing, electrical safety, EMC, software validation, cybersecurity) and a comparison of the new device's technical specifications and intended use against a predicate device. It explicitly states: "No clinical data is necessary to evaluate safety or effectiveness for purposes of determining substantial equivalence of the proposed modification."

In summary, none of the requested information (acceptance criteria table, study details, sample sizes, expert qualifications, ground truth, MRMC study, standalone performance) for an AI-powered device is present in this medical device submission.

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