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Intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion DR + Wireless allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion DR + Wireless system represents the straightforward integration of a modified digital x-ray receptor panel and our previously cleared software. This is a MODIFICATION of our clearance K152279 wherein we have changed the panel scintillator to Cesium Iodide in addition to having the GOS scintillator available. Changing the scintillator is the only modification.

ViZion DR + Wireless is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD). ViZion DR + Wireless 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 operation of the Viztek PACS and the new receptor panel were not changed.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Vizion DR + Wireless device, presented in the requested format:

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

The document describes a modification to an existing device (K152279) where the scintillator material was changed from Gadolinium Oxysulfide (GOS) to Cesium Iodide (CSI). The primary acceptance criteria for equivalence appear to be related to imaging performance metrics (MTF and DQE) and clinical image quality.

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

• Sample Size for Test Set: Not explicitly stated for either the quantitative (MTF/DQE) or clinical image evaluation. For the clinical images, it states "Clinical images were acquired," implying a set of images, but no number is given.
• Data Provenance: Not explicitly stated. The document is from the US FDA, and the company address is in North Carolina, USA, suggesting the study was likely conducted in the USA, but this is not confirmed. It is implied to be prospective or specifically acquired for this evaluation, as it mentions "Clinical images were acquired and evaluated..."

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)

• Number of Experts: One
• Qualifications of Experts: "a board certified radiologist" (no mention of years of experience).

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

• Adjudication Method: None. A single board-certified radiologist performed the evaluation.

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

• MRMC Study: No. The study described is a comparison of two imaging technologies (different scintillators), not an AI-assisted reading study. The device is a digital X-ray receptor, not an AI diagnostic tool.

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

• Standalone Performance: Not applicable. This device is an imaging acquisition system, not an AI algorithm. The performance evaluation focuses on the image quality produced by the system itself before interpretation. The quantitative metrics (MTF, DQE) are "standalone" in the sense that they measure the physical performance of the sensor, but this is not an AI algorithm.

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

• Type of Ground Truth:
  • For MTF and DQE: These are objective physical measurements of image quality, not dependent on a "ground truth" derived from patient data in the same way clinical diagnostics are. They are measured against known physical standards.
  • For Clinical Image Quality: The "ground truth" for clinical image quality comparison was the subjective opinion of a board-certified radiologist, who evaluated whether images from the modified panel were "as good as or better than" images from the predicate panel. This is a form of expert opinion/subjective evaluation rather than an objective clinical endpoint like pathology.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. The Vizion DR + Wireless is a hardware device (digital X-ray detector) and associated software, not a machine learning or AI algorithm that requires a "training set" in the conventional sense. The "software" was previously cleared and confirmation testing was performed after the hardware modification.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" for this type of device.

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Intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion DR + Wireless allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion DR + Wireless system represents the straightforward integration of a modified digital x-ray receptor panel and our previously cleared software. This is a MODIFICATION of our clearance K123644 wherein we have changed panel to a wireless version of the previously cleared panel/software combination. Going wireless (with batterv operation possible) are the ONLY modifications.

ViZion DR + Wireless is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD). ViZion DR + Wireless 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 operation of the Viztek PACS and the new receptor panel were not changed. Our predicate is ViZion DR +, K123644. We do not supply the router, but any router meeting the IEEE 802.11 a/b/g/n specifications will work. With the advent of AED (automatic exposure detection) by the panel, integration with or connection to specific generators is no longer required. If the user decides NOT to use AED, wired synchronization with Sedecal Series SHF generators is known to work.

Here's a breakdown of the acceptance criteria and study information for the Viztek ViZion DR + Wireless device based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document provided does not explicitly state formal "acceptance criteria" in a quantitative, measurable sense for the device, beyond equivalence to a predicate device. Instead, it focuses on demonstrating substantial equivalence through a comparison of technical specifications and performance characteristics, some of which could be considered de-facto acceptance criteria derived from the predicate's performance.

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

• Sample Size for Test Set: The document simply states "Clinical images were acquired" and "bench, and test laboratory results." It does not specify the number of clinical images or cases used for evaluation.
• Data Provenance: The document does not explicitly state the country of origin. Given the submission is to the U.S. FDA, it is likely that the clinical image acquisition was performed in the U.S. The study appears to be prospective in the sense that new images were acquired specifically for this evaluation.

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

• Number of Experts: One board-certified radiologist.
• Qualifications: "board certified radiologist." No specific tenure or experience level is mentioned beyond board certification.

4. Adjudication Method for the Test Set

• Adjudication Method: None mentioned. A single radiologist evaluated the images.

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

• No, a MRMC comparative effectiveness study was not done. The evaluation was based on a single radiologist's assessment of clinical images from the new panel compared to the predicate, and bench testing.

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

• Not applicable / not a software-only algorithm. The device is a digital X-ray receptor panel (hardware) with associated software. The "performance" being evaluated is of the integrated system and its ability to produce diagnostic images. The comparison focuses on the image quality produced by the device, which is inherently designed for human interpretation.

7. Type of Ground Truth Used

• Expert Consensus / Expert Interpretation: The ground truth for image quality was established by the interpretation of a single board-certified radiologist. There is no mention of pathology, outcomes data, or other objective measures for ground truth.

8. Sample Size for the Training Set

• Not applicable / Not explicitly a machine learning model requiring a training set. The device is primarily a hardware modification (wireless panel) to an existing cleared system. While there's "software," the document states "Since no software modifications were required, confirmation testing was performed." This suggests the software itself was not re-trained or developed with a new dataset for this specific submission, but rather integrated with the new wireless panel.

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

• Not applicable. As stated above, a distinct "training set" for a machine learning model isn't indicated as part of this device's submission or the testing described.

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EXA™ is a software device that receives digital images and data from various sources (i.e. CT scanners, ultrasound systems, R/F Units, computed & direct radiographic devices, secondary capture devices, scanners, imaging gateways or other imaging sources). Images and data can be stored, communicated, processed and displayed within the system and or across computer networks at distributed locations. Lossy compressed mammographic images are not intended for diagnostic review. Mammographic images should only be viewed with a monitor approved by FDA for viewing mammographic images. For primary diagnosis, post process DICOM "for presentation" images must be used. Typical users of this system are trained professionals, nurses, and technicians.

EXA™ is a software suite of web based PACS applications that was developed specifically to handle the DICOM protocol, for both transmitting and viewing DICOM images and data elements. The applications were developed so that access to the PACS can occur from any Microsoft Windows computer with internet capabilities, and offer an interface that users find to be quite intuitive after some initial learning. (Not intended for use on mobile devices) The EXA™ applications deal with all manner of DICOM images and modalities, including MR, CT, CR, US, MG and many others. These images can be viewed, annotated, transmitted to other facilities, printed, animated and stored using the EXA™ RAD suite.

The provided document is a 510(k) premarket notification for a Picture Archiving and Communications System (PACS) named EXA™. This document focuses on demonstrating substantial equivalence to a predicate device (Viztek OPAL-RAD™) through software validation and a comparison of characteristics rather than a clinical study with specific acceptance criteria related to diagnostic performance.

Therefore, the requested information regarding acceptance criteria for device performance, sample sizes for test and training sets, expert qualifications, ground truth establishment, or clinical effectiveness studies (MRMC or standalone AI) are not explicitly present or applicable in the context of this 510(k) submission.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

Not applicable in the conventional sense of diagnostic performance metrics (e.g., sensitivity, specificity). The acceptance criteria were based on software verification and validation, ensuring the device meets its predetermined software requirements specifications and performs equivalently to the predicate device in terms of functionality and image handling.

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

• Test Set Sample Size: Not explicitly stated. The testing involved "Software Verification and Validation" and "Clinical images collected." It's likely these were internal tests rather than a formal clinical study with a defined patient cohort.
• Data Provenance: Not specified. "Clinical images collected" suggests real-world data, but details about country of origin or whether it was retrospective/prospective are not provided. Given the nature of a PACS, the images themselves would originate from various imaging modalities.

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

Not applicable. The submission focuses on software functionality and image handling, not on diagnostic accuracy requiring expert ground truth in a clinical trial. The "clinical images collected" were likely used to verify image quality and system functionality, not for diagnostic performance evaluation against an expert-established ground truth.

4. Adjudication method for the test set

Not applicable. No formal adjudication method is mentioned as there's no clinical diagnostic performance study described.

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 was done. This device is a PACS, which is infrastructure for displaying and managing medical images, not an AI-assisted diagnostic tool.

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

Not applicable. This is not an AI algorithm with standalone performance. It is a PACS system.

7. The type of ground truth used

Not applicable. For a PACS, the "ground truth" would relate to the accurate storage, retrieval, processing, and display of image data conforming to DICOM standards and system specifications, rather than a clinical diagnosis.

8. The sample size for the training set

Not applicable. This is not an AI device that requires a training set in the machine learning sense. The "training" for such a system refers to software development and testing based on predetermined requirements.

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

Not applicable.

Summary of the Study that Proves the Device Meets Acceptance Criteria:

The study that proves the device meets the (implied) acceptance criteria is described as Software Verification and Validation and Risk Analysis.

• Methodology: The submission states, "The results of software validation and comparison to our predicate device indicates that the new device is as safe and effective as our predicate device. Clinical images collected demonstrate equal or better image quality as compared to our predicate." It further clarifies, "The testing showed that the device meets its predetermined Software Requirements Specifications."
• Conclusion: Based on the software validation and risk analysis, Viztek Inc. concluded that EXA™ is "as safe and effective as the predicate device, have few technological differences, and has the same indications for use, thus rendering it substantially equivalent to the predicate device."

Essentially, the "study" was a comprehensive software testing and comparison effort, confirming that the new PACS system performed its intended functions in a manner comparable to or better than a previously cleared PACS, and that all software requirements were met. It did not involve a clinical utility study to evaluate diagnostic accuracy or improvements for human readers.

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ViZion Ultra is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion Ultra allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion Ultra system represents the straightforward integration of a new digital x-ray receptor panel (K110849) and our previously cleared software. This is a MODIFICATION of our clearances K112661 and K123644 wherein we have changed the supplier of the panel. Therefore a special 510(k) has been submitted. The ViZion Ultra is compatible with Sedecal SHF generators. Some manufacturers rebrand the Sedecal SHF generators, and these generators are compatible as well.

ViZion Ultra is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) ViZion Ultra is designed to perform digital radiographic examinations as a replacement for conventional film. This integrated platform provides the benefits of PACS with the advartages of digital radiography for a filmless environment and improves cost effectiveness. The major funciple of operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion + DR, K123644, wherein we combined our OPAL-RAD software with two new digital panels.

Here's an analysis of the acceptance criteria and the study proving the device meets them, based on the provided text:

Key Takeaway: This 510(k) submission is for a modification to an existing digital X-ray system, specifically changing the supplier of the digital receptor panel. Therefore, the "study" primarily focuses on demonstrating that the new panel performs as well as or better than the previously cleared predicate device, rather than establishing de novo efficacy. The acceptance criteria are implicitly met by achieving substantial equivalence to the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

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 images used in the evaluation. It only states that "Clinical images were acquired."
• Data Provenance: The document does not explicitly state the country of origin or whether the data was retrospective or prospective. Given the nature of a 510(k) for a minor modification (panel change), it's likely these were prospectively acquired images for comparison purposes, but this is not definitively stated.

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

• Number of Experts: "a board certified radiologist" (singular, implies one).
• Qualifications of Experts: "board certified radiologist." Specific years of experience are not mentioned.

4. Adjudication Method for the Test Set

• The document states that "a board certified radiologist... concluded the images from the new panel are as good as the images acquired with the predicate panel." This indicates a single-reader assessment rather than a multi-reader adjudication method (like 2+1 or 3+1). There was no additional adjudication process described.

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

• No, an MRMC comparative effectiveness study was not done. The evaluation described involves a single radiologist comparing images from the new panel to those from the predicate panel. The focus was on demonstrating non-inferiority (equal or better image quality) rather than quantifying an improvement in human reader performance with AI assistance. This device is a digital X-ray receptor, not an AI-powered diagnostic aid.

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

• This question is not applicable in the context of this device. The ViZion Ultra is a digital X-ray receptor panel and associated software for image acquisition. It is not an algorithm designed for interpretation or diagnosis that would typically undergo a standalone performance study in the way AI algorithms are evaluated. Its "performance" is inherently tied to the image it produces for a human reader. The technical parameters like MTF and DQE (mentioned as being supplied by the manufacturer) represent objective standalone measures of the detector's physical performance.

7. Type of Ground Truth Used

• The ground truth for the clinical images was implicitly established by expert consensus/opinion (from the single board-certified radiologist) that the images produced by the new panel were "as good as" those from the predicate panel. There is no mention of pathology, outcomes data, or other objective measures of disease presence as ground truth, as the study's purpose was image quality comparison for substantial equivalence, not diagnostic accuracy.

8. Sample Size for the Training Set

• Not applicable / Not provided. The device described is a hardware component (digital X-ray detector) and associated software for image acquisition and viewing. It is not an AI/Machine Learning algorithm that typically requires a distinct "training set" in the conventional sense for its function. The software is noted as "SAME as K112661," implying that its functionality is established.

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

• Not applicable. As stated above, this is not an AI/ML device that requires a training set with established ground truth for learning.

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ViZion + DR is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion + allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion + DR system represents the straightforward integration of a new digital x-ray receptor panel and our previously cleared software. This is a MODIFICATION of our clearance K112661 wherein we have changed the supplier of the panel. ViZion + DR is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) ViZion + 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 operation of the Viztek PACS and the new receptor panel were not changed. Our main predicate is ViZion DR, K112661, wherein we combined our OPAL-RAD software with a new digital panel. We now also offer two sizes of panels: 14" x 17" and 17" x 17" panels.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Viztek ViZion + DR device:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary (K123644) does not outline specific numerical acceptance criteria for image quality metrics. Instead, it relies on a qualitative assessment for substantial equivalence.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "Clinical images were acquired," implying a set of images, but the exact number is not provided.
• Data Provenance: The document does not specify the country of origin of the data. It is implied to be retrospective or a limited prospective acquisition for the purpose of the 510(k) submission, as it involves comparison to existing predicate devices. The study is described as a clinical image evaluation, not a large-scale clinical trial.

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

• Number of Experts: "a board certified radiologist" (singular).
• Qualifications: "board certified radiologist." No further details on years of experience are provided.

4. Adjudication Method for the Test Set

• Adjudication Method: "a board certified radiologist who concluded the images from the new panel are as good as or better than the images acquired with the predicate panel." This indicates a single reader assessment, not a multi-reader adjudication method (like 2+1 or 3+1).

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done. The evaluation was performed by a single board-certified radiologist.
• Effect Size: Not applicable, as no MRMC study was conducted.

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

• This device is a digital flat panel X-ray detector system, not an AI algorithm. Therefore, a standalone performance study in the context of an AI algorithm is not applicable. The device itself is the imaging system, and its performance is assessed directly (both technically and clinically).

7. The Type of Ground Truth Used

• Type of Ground Truth: The ground truth for the clinical image evaluation was expert opinion/consensus, specifically the judgment of a single board-certified radiologist comparing the new panel's images to those from predicate panels. There is no mention of pathology or outcomes data for establishing ground truth in this submission.

8. The Sample Size for the Training Set

• This submission describes a hardware modification (a new digital panel combined with existing software) and its equivalence to predicate devices, not the development or training of a new AI algorithm. Therefore, there is no "training set" in the context of machine learning.

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

• Not applicable, as there is no training set for an AI algorithm.

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ViZion DR is intended for digital image capture use in general radiographic examinations, wherever conventional screen-film systems may be used, excluding fluoroscopy, angiography and mammography. ViZion allows imaging of the skull, chest, shoulders, spine, abdomen, pelvis, and extremities.

The ViZion DR system represents the straightforward integration of two cleared devices: ViZion DR, K102123 and K102587, the Samsung Digital Flat Panel. ViZion DR is a Digital Radiography system, featuring an integrated flat panel digital detector (FPD) (K102587, Samsung Flat-Panel X-Ray Detector), made by Samsung Mobile Display Co., Ltd. (this is the 510(k) for the flat panel detector) and Viztek's proprietary OPAL-RAD PACS image viewing and acquire interface software technology, (K063337) which incorporates state of the art object-oriented software and connectivity. ViZion 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 film less. environment and improves cost effectiveness. The major functions and principle of operation of the Viztek PACS and Samsung FPD were not changed.

This is a 510(k) premarket notification for a new version of the Viztek ViZion DR, a Digital Radiography (DR) system. The submission focuses on replacing the digital flat panel detector (FPD) with a new model while maintaining the existing software and overall functionality. As such, the "acceptance criteria" and "study that proves the device meets the acceptance criteria" are framed in terms of demonstrating substantial equivalence to a predicate device, rather than proving a specific diagnostic accuracy against a clinical ground truth.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the demonstration of substantial equivalence to the predicate device, specifically regarding safety and effectiveness, and the absence of new indications for use or technological differences that would raise new questions of safety or effectiveness. The reported performance is a comparison to the predicate.

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

The document states: "Clinical images collected demonstrate equal or better image quality as compared to our predicates." However, it does not specify the sample size for this clinical image inspection, nor does it provide details about the data provenance (e.g., country of origin, retrospective or prospective nature). Given the nature of a 510(k) for a component change (the FPD), this might have been a limited comparative study rather than a large-scale clinical trial.

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

The document mentions "clinical image inspection" but does not provide any information on the number of experts involved in this inspection or their qualifications.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method. It only mentions "clinical image inspection."

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 done. This device is a digital X-ray detector system, not an AI-assisted diagnostic tool. The comparison is between the new detector and a previous detector system, with the focus on image quality and equivalence, not reader performance improvement with AI.

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

This refers to an algorithm's performance without human intervention. Since the device is a digital X-ray detector system (hardware), not a diagnostic algorithm, this concept does not apply. The "standalone performance" for this device would relate to its hardware specifications and image acquisition capabilities, which are covered by bench and laboratory testing.

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

The available information suggests that the "ground truth" for the comparison was based on "clinical image inspection" and possibly "bench, and test laboratory" results, comparing the image quality of the new device to that of the predicate device. This implies a subjective assessment of image quality by potentially experts, but the specifics are not detailed. It is unlikely to involve pathology or outcomes data for this type of 510(k) submission.

8. The Sample Size for the Training Set

This submission is for a digital X-ray detector system, not an AI algorithm that requires a training set. Therefore, there is no training set in the context of this device.

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

As there is no training set for this hardware device, this question is not applicable.

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