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The URS-50RF is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures. It is also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The Canon Dynamic/Static DR URS-50RF is a portable digital radiography that can take images of any part of the body. It directly converts the X-ray images captured by the LANMIT (Large Area New MIS Sensor and TFT) sensor into a high-resolution digital images. The instrument is suited for use inside a patient environment. This unit converts the X-rays into digital signals. The unit can acquire still and moving images.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Canon Dynamic/Static DR Model URS-50RF Fluoroscopic Digital X-Ray System:

Summary of Device and Study Information (K093688)

This 510(k) summary describes a fluoroscopic digital X-ray system, the Canon Dynamic/Static DR URS-50RF, intended to generate fluoroscopic images for vascular angiography, diagnostic and interventional procedures, and cardiology. It aims to replace image intensifier technology. The submission focuses on demonstrating substantial equivalence to predicate devices, primarily through performance testing and software validation.

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document is a 510(k) summary. For medical devices, particularly those establishing substantial equivalence, explicit "acceptance criteria" are often phrased in terms of meeting or exceeding the performance of legally marketed predicate devices, or complying with relevant standards. The document does not list specific numerical acceptance criteria for image quality, diagnostic accuracy, or clinical endpoints. Instead, it makes a general statement about performance.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "Tests were performed on the device," but does not specify the number of cases, images, or subjects used for performance testing.
• Data Provenance: Not specified. It's unclear if the testing involved human subjects, phantoms, or simulated data, or the country of origin of any data used. Given the nature of a 510(k) for an imaging device, it's highly probable that bench testing with phantoms and potentially some limited clinical evaluation (if required to show equivalence for image quality) was involved, but details are absent.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. With no mention of expert review or ground truth establishment, no adjudication method is detailed.

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

• MRMC Study: No, a multi-reader multi-case (MRMC) comparative effectiveness study was not specifically mentioned or implied in the provided 510(k) summary. The summary focuses on demonstrating substantial equivalence to already marketed devices based on technological characteristics and general performance testing, rather than a direct comparison of physician performance with and without AI assistance.
• Effect Size of Human Reader Improvement: Not applicable, as no MRMC study (or AI assistance) was described.

6. Standalone (Algorithm Only) Performance Study

• Standalone Study: This device is a hardware fluoroscopic digital X-ray system, not an AI algorithm. Therefore, the concept of a "standalone (algorithm only)" performance study does not apply in this context. The performance described relates to the entire system's ability to acquire and process images.

7. Type of Ground Truth Used

• Type of Ground Truth: Not explicitly stated. The performance testing is generally described as validating that the device is "safe and effective" and "performs comparably" to predicate devices. For an imaging system, ground truth might involve:
  • Physical Measurements: Using phantoms to verify spatial resolution, contrast resolution, noise, dose efficiency, etc.
  • Clinical Image Quality Assessment: Expert review of images to ensure diagnostic interpretability, though this isn't detailed as "ground truth" establishment in the psychological sense.
  • Comparison to Predicate: Performance is often benchmarked against images from the predicate device.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This device is a hardware imaging system, not an AI or machine learning algorithm that requires a "training set."

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

• Ground Truth for Training Set Establishment: Not applicable, as there is no training set for a hardware device.

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The CXDI-50RF is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures. It is also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology. Not intended for mammography applications.

The Canon Dynamic/Static DR CXDI-50RF is a portable digital radiography that can take images of any part of the body. It directly converts the X-ray images captured by the LANMIT (Large Area New MIS Sensor and TFT) sensor into a high-resolution digital images. The instrument is suited for use inside a patient environment. This unit converts the X-rays into digital signals. The unit can acquire still and moving images.

The Canon Dynamic/Static DR Fluoroscopic Digital X-Ray Receptor Panel (Model CXDI-50RF) is indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic, and interventional procedures, as well as for cardiology, diagnostic, and interventional procedures. It is intended to replace fluoroscopic images obtained through image intensifier technology and is not intended for mammography applications.

Here's an analysis of the provided information regarding acceptance criteria and the study:

Details of the Study:

The provided 510(k) summary (K092439) for the Canon Dynamic/Static DR Model CXDI-50RF Fluoroscopic Digital X-Ray Receptor Panel primarily relies on showing substantial equivalence to predicate devices rather than a detailed clinical performance study with specific metrics like sensitivity, specificity, or AUC based on expert reads.

Here's what can be inferred from the document:

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

   • The document does not specify a sample size for a test set in the context of an accuracy or performance study involving image interpretation.
   • The data provenance is not described in terms of country of origin or whether it was retrospective or prospective.
   • The "Performance Testing/Data" section mentions "Tests were performed on the device," but these tests appear to be primarily technical and safety assessments (e.g., electrical safety, EMC, software validation) and comparative assessments against predicate devices' technological characteristics, not a clinical study on diagnostic accuracy.

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

   • This information is not provided. The submission focuses on technical equivalence and safety, not on evaluating human reader performance with the device against a ground truth established by experts.

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

   • This information is not provided, as there is no described clinical test set requiring expert adjudication for diagnostic accuracy.

4. 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 predates the widespread regulatory requirement for such studies for AI-powered devices. The device described is a digital X-ray receptor panel, an imaging hardware component, not an AI diagnostic algorithm. Therefore, the concept of "human readers improve with AI vs without AI assistance" is not applicable here.

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

   • No, a standalone algorithm performance study was not done. The device is an image acquisition component, not a diagnostic algorithm.

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

   • This information is not provided for a clinical diagnostic performance study. The "ground truth" implied in the submission relates to technical specifications, safety standards, and functional equivalence to predicate devices.

7. The sample size for the training set:

   • There is no mention of a training set in the context of machine learning or AI models. The device is a hardware component for imaging, not a software algorithm that requires a training set.

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

   • This information is not applicable as there is no training set for an AI/machine learning model described.

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This device is intended for high resolution hard copy imaging of digital image source material (DICOM). The hardcopy output includes however is not limited to, digital radiography, nuclear medicine, ultrasound, CT, MRI, CR and Radiation Therapy planning; Images are suitable for medical image diagnosis use and referral. The system is intended for use by medical radiologists, imaging modality specialists, and communications to referring physicians. Not for mammography use.

CYPHER implements the necessary DICOM services to receive DICOM print jobs and provides an interface for printing the received data on a Windows™ printer. The device is designed for use with the CANON imagePRESS™ C1 Digital Print System. It consists of an Intel® 945GSE Mini-ITX Board in a shielded enclosure. The user interface is implemented on either an attached monitor or via the remote desktop function inherent in Windows XP. Power is supplied via an external UL listed 12 volt power supply.

The provided text describes a medical image hardcopy device, the "Cypher DICOM Print Solution," and its FDA 510(k) summary. However, it does not contain the detailed information necessary to answer all sections of your request regarding acceptance criteria and the comprehensive study proving its performance.

The document is a regulatory submission for substantial equivalence to a predicate device, focusing on its DICOM compatibility and ability to produce high-quality hardcopy printouts. It mentions "Performance Testing/Data" that demonstrated the device is "safe and effective, performs comparably to and is substantially equivalent to the predicate device," and that "Tests include: Software Validation and evaluation of hardcopy output." Beyond this general statement, specific acceptance criteria, detailed study design, sample sizes, expert qualifications, or ground truth methods are not provided.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document only states that the device meets these general criteria but does not provide specific quantitative metrics or results that would typically constitute detailed acceptance criteria (e.g., specific resolution targets, color accuracy thresholds, DICOM conformance test results with pass/fail ratios).

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 states "Tests were performed on the device," but gives no details about the size or nature of the test set, nor the provenance of any data used 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)

• Not provided. While the device is intended for "medical image diagnosis use and referral" by "medical radiologists, imaging modality specialists," the document does not mention the involvement of experts in establishing ground truth for any performance testing.

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

• Not provided. The document does not describe any adjudication method, suggesting that such a method was either not relevant to the type of testing performed (e.g., functional and imaging quality evaluation for a printer) or not considered necessary for this 510(k) submission.

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 study was not done, nor would it be relevant for this device. This device is a "Medical Image Hardcopy Device (Printer)," not an AI-powered diagnostic tool. Its function is to print DICOM images, not to assist in image interpretation or diagnosis directly via AI. Therefore, an MRMC study measuring human reader improvement with AI assistance is not applicable.

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

• Yes, in the sense that the "device" (printer) was tested independently. The performance testing mentioned ("Software Validation and evaluation of hardcopy output") would inherently be a standalone evaluation of the printer's output quality and DICOM conformance. However, this is not an "algorithm only" in the context of an AI device, but rather a functional evaluation of a hardware/software system.

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

• Not explicitly stated in terms of diagnostic ground truth. For a printer, the "ground truth" would likely involve objective measures of print quality, color accuracy, resolution, adherence to DICOM standards for rendering, and potentially comparison to the digital image data itself. It's not about clinical diagnosis ground truth (like pathology or patient outcomes).

8. The sample size for the training set

• Not applicable / Not provided. This is a medical image printer, not an AI model requiring a training set in the conventional sense. The "training" would be more akin to software development and testing, not machine learning model training.

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

• Not applicable / Not provided. See point 8.

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The RadPro ION Mobile Fluoroscopy Systems are designed to provide fluoroscopic and spot-film images of the patient during diagnostic, surgical and interventional procedures Examples of clinical application may include cholangiography, endoscopy, urologic, orthopedic, neurologic, critical care and emergency room procedures The system may be used for other imaging applications at the physician's discretion

The RadPro ION Mobile Fluoroscopy Systems (Multiple Models) are mobile x-ray units which employ unage intensifier units and have various options for image display and storage The units are used to equip a radiological room of general surgery, orthopedic, traumatology and cardiology The CCD camera is characterized by high contrast and sensitivity and no persistence of image The camera head include a mage rotation and image reversal system The automatic dose control, which acts either on KV and mA values, allows the user to reduce step by step the x-ray radiation to the minimum value, in accordance with the thickness and the density of the screened part All the configurations can accept connection to a digital memory, which allows to store and display in real time the ımage on the monitor only with a very little x-ray dose The new control panel with an alphanumerical display permits a fast and easy use by a rational and simple symbology, this console by an extension cable, could be located on the patient support to enable the c-arm control by the operator itself The system employs a Dose Area Product (DAP) meter for compliance with the US performance standard requirements

The provided text is a 510(k) summary for the RadPro ION Mobile Fluoroscopy Systems. The document focuses on demonstrating substantial equivalence to a predicate device, rather than providing a detailed study proving performance against specific acceptance criteria.

The acceptance criteria discussed are primarily related to general device characteristics and compliance with regulatory standards, which are met by comparing the new device to a legally marketed predicate device.

Here's an analysis of the provided information in the context of your request:

1. Table of Acceptance Criteria and Reported Device Performance

The concept of "acceptance criteria" in this document is effectively the characteristics of the predicate device, which the new device aims to match or demonstrate equivalence to. "Reported device performance" refers to how the RadPro ION Mobile Fluoroscopy Systems compare to these characteristics.

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

The document does not detail a specific "test set" in the way one would for an AI algorithm or a clinical trial with patient data. The evaluation is based on "bench and test laboratory testing" and "clinical images."

• Sample Size: Not specified for "clinical images." No specific number of cases or patients is mentioned.
• Data Provenance: Not specified. It's unclear if "clinical images" refer to retrospective data, prospective data, or from which country they originated.
• Retrospective/Prospective: Not specified.

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

This information is not provided. The document states "clinical images" were analyzed but does not specify how "ground truth" was established for these images or if experts were involved in establishing it for the context of this 510(k). The evaluation leans heavily on engineering and regulatory compliance rather than expert image interpretation in a comparative setting.

4. Adjudication Method for the Test Set

Not applicable/Not specified. There is no mention of an adjudication process for clinical images or expert consensus within this 510(k) summary. The "Conclusion" indicates that Virtual Imaging, Inc. concluded the device's safety and effectiveness.

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

• No, a MRMC comparative effectiveness study was not done. The document describes a comparison to a predicate device for substantial equivalence, focusing on technical characteristics and intended use, not on the improvement of human readers with or without AI assistance.
• Effect size: Not applicable, as no such study was conducted.

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

• Not applicable. This device is a mobile fluoroscopy system, which is a hardware device that produces images, not an AI algorithm that operates standalone or assists in image interpretation without human intervention. Its performance is inherent in the image quality and system functionality for human use.

7. Type of Ground Truth Used

The concept of "ground truth" for image interpretation, as would be used for evaluating diagnostic accuracy, is not explicitly defined or used in this 510(k) summary. The evaluation relies on:

• Comparison of technical specifications (e.g., generator power, image intensifier size).
• Compliance with performance standards (21 CFR 1020.30).
• Results from "bench and test laboratory testing."
• Review of "clinical images" to support safety and effectiveness, likely focusing on image quality and proper function, but without defining a specific "ground truth" against which diagnostic accuracy was measured.

8. Sample Size for the Training Set

Not applicable. This device is a hardware system, not an AI algorithm requiring a training set.

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

Not applicable, as there is no training set for a hardware fluoroscopy system.

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Intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for obtaining fluoroscopic radiographic images of the skull, spinal column, chest, abdomen, extremities, and other body parts.

The FluoroPro RF Digital Imaging System is a high resolution, digital imaging system designed for digital videography. It is intended to replace conventional film techniques in multipurpose or dedicated applications where general fluoroscopy, interventional fluoroscopy or angiography or cardiac imaging procedures are performed. The FluoroPro RF Digital Imaging System allows the operator to view and enhance 1000 line fluoroscopy. High resolution digital spot images (1024) may be acquired at single or rapid acquisition rates, up to 30 fps. Images may be viewed and enhanced enabling the operator to bring out diagnostic details difficult or impossible to see using conventional imaging techniques. Images can be stored locally for medium term storage. The FluoroPro RF Digital Imaging System enables the operator to hardcopy image with a laser printer or send images over a network for longer term storage. The major system components include: a fluoroscopic TV camera, monitors, and an image processor.

The provided documentation describes the FluoroPro RF Digital Imaging System, a fluoroscopic X-Ray system, and its substantial equivalence to a predicate device. The core of the submission focuses on demonstrating similarity to a legally marketed device rather than proving performance against specific acceptance criteria in a comparative clinical study.

Here's an analysis based on the provided text:

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

The submission does not present explicit "acceptance criteria" in the traditional sense of a clinical trial (e.g., target sensitivity, specificity). Instead, it demonstrates performance by showing equivalence to a predicate device based on technical characteristics. The table below summarizes these characteristics and how the new device compares to the predicate.

Study that Proves the Device Meets the Acceptance Criteria:

The documentation states: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." and "After analyzing both bench and user testing data, it is the conclusion of Virtual Imaging that the FluoroPro RF Digital Imaging System is as safe and effective as the predicate device, has few technological differences, and has no new indications for use, thus rendering it substantially equivalent to the predicate device."

This indicates that the "study" was primarily bench testing (evaluating technical specifications, performance parameters, and compliance with standards) and user testing (likely validation by trained personnel in a simulated or controlled environment to confirm functionality and usability). The goal of these tests was to demonstrate substantial equivalence to the predicate device, not to meet specific quantitative clinical performance metrics like sensitivity or specificity.

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

The document does not provide details on the sample size used for the "bench and user testing." It also does not specify the provenance of any data (e.g., country of origin, retrospective/prospective), as it relies on technical and operational comparisons rather than clinical data from human subjects.

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. Given that the submission focuses on substantial equivalence based on technical specifications and functional testing, it's unlikely that "ground truth" for diagnostic accuracy was established by medical experts in the way it would be for an AI-powered diagnostic device. The "user testing" likely involved qualified technicians or doctors evaluating the system's operational aspects, image quality for diagnostic interpretation (compared to the predicate), and ease of use.

4. Adjudication method for the test set

This information is not provided. As "ground truth" from experts for diagnostic accuracy in a clinical context isn't explicitly mentioned, an adjudication method for such a ground truth would not be detailed.

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 was not conducted or reported in this submission. This device is a digital imaging system (hardware and software for image acquisition and display), not an AI-powered diagnostic tool, so the concept of human readers improving with AI assistance is not applicable here.

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

No, a standalone algorithm performance study was not done. The device itself is an imaging system; its "performance" is tied to its ability to acquire and display images comparable to a predicate device, and it is intended for use by a "qualified/trained doctor or technician." It is not an autonomous diagnostic algorithm.

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

For this type of device (a digital fluoroscopic x-ray system), the "ground truth" used for validation would primarily relate to its technical performance and image quality, not disease diagnosis. This would involve:

• Technical Specifications: Confirming that the system meets its stated parameters (resolution, frame rate, power consumption, etc.) through engineering tests.
• Image Quality Assessment: Evaluating the acquired images against established standards or by comparison to the predicate device for clarity, contrast, and diagnostic interpretability by a qualified user. This often involves phantoms and possibly human users assessing image quality visually.
• Safety Standards: Adherence to electrical safety and other relevant performance standards (e.g., US FDA performance standards mentioned).

There is no mention of ground truth established via expert consensus, pathology, or outcomes data related to diagnostic accuracy from patient images.

8. The sample size for the training set

This information is not applicable and therefore not provided. The FluoroPro RF Digital Imaging System is a digital X-ray system, not a machine learning or AI algorithm that requires a "training set" in the computational sense.

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

This information is not applicable and therefore not provided, as there is no "training set" for this device.

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