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The Vue Motion software program is used for patient management by clinicians in order to access and display patient data, medical reports, medical data, and medical images for different modalities including CR, DR, CT, MR, NM, ECG, and US.

Vue Motion provides wireless and portable access to medical images for remote reading or referral purposes from web browsers including usage with validated mobile device is not intended to replace full workstations and should be used only when there is no access to a workstation. For primary interpretation and review of mammography images, only use display hardware that is specifically designed by FDA for mammography.

CARESTREAM Vue Motion with ECG Feature is a Light Viewer designed to provide wireless and portable access to medical images for remote reading or referral purposes from web browsers including enterprise distribution of radiology images and related data. The modification to the Vue Motion device described in this submission includes the addition of software to facilitate display of ECG data.

The provided text describes a 510(k) submission for the "CARESTREAM Vue Motion" device, specifically detailing the addition of an ECG display feature. The focus of this document is on establishing substantial equivalence to previously cleared predicate devices, rather than an in-depth clinical study demonstrating acceptance criteria met by the device's performance in a diagnostic context. Therefore, much of the requested information regarding a study proving the device meets acceptance criteria, such as sample size for test sets, data provenance, ground truth establishment, or human reader effectiveness, is not present.

However, based on the information provided, we can extract details concerning the device's intended use, the "testing" performed for this specific modification, and the basis for its clearance.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative clinical acceptance criteria for diagnostic performance outcomes (e.g., sensitivity, specificity). Instead, the acceptance criteria for this modification revolve around functional equivalence and safety. The performance is reported as meeting these functional requirements.

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

• Sample Size for Test Set: Not specified. The testing mentioned is "non-clinical (bench) testing" and "simulated user test environment." This suggests functional testing with sample data rather than a clinical study with a patient cohort.
• Data Provenance: Not specified, but referred to as "sample waveform data, patient information, and measurement information obtained from the source data." This implies synthetic or pre-existing (possibly de-identified) data used for functional verification rather than patient data from a specific country or collected prospectively/retrospectively for a clinical trial.

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

• This information is not provided. The "ground truth" in this context appears to be the "source data" used for comparison in the simulated user test, and the exact method of its establishment or the experts involved are not detailed.

4. Adjudication Method for the Test Set

• Not applicable/Not specified. Given the nature of the testing (functional verification against source data), a formal adjudication method for diagnostic consensus among experts is not 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, a MRMC comparative effectiveness study was not done. The device is a "Light Viewer" for display and access, not an AI-powered diagnostic tool, and the submission primarily focuses on the addition of an ECG display feature, not on improving human reader performance with AI assistance.

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

• Not directly applicable in the terms of a diagnostic algorithm's standalone performance. The device itself is a viewer, and its "performance" is its ability to accurately display medical data. The "Discussion of Testing" describes verifying the functionality and accuracy of this display against source data, which can be considered a form of standalone verification of the display component. However, it's not a standalone diagnostic algorithm performance study.

7. The Type of Ground Truth Used

• The "ground truth" for the "simulated user test environment" was "source data" comprising "sample waveform data, patient information, and measurement information." This implies a reference set of known-correct data points against which the device's display accuracy was compared.

8. The Sample Size for the Training Set

• Not applicable. This device is a display software, not a machine learning or AI algorithm that requires a "training set."

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

• Not applicable, as there is no training set for this type of device.

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The CARESTREAM Vue PACS is an image management system whose intended use is to provide completely scalable local and wide area PACS solutions for hospital and related institutions/sites, which will archive, distribute, retrieve and display images and data from all hospital modalities and information systems.

The system contains interactive tools in order to ease the process of analyzing and comparing three dimensional (3D) images. It is a single system that integrates review, dictation and reporting tools to create a productive work environment for the radiologists and physicians.

The Vue Motion software program is used for patient management by clinicians in order to access and display patient data, medical reports, and medical images for diagnosis from different modalities including CR. DR, CT, MR, NM and US.

Vue Motion provides wireless and portable access to medical images for remote reading or referral purposes from web browsers including usage with validated mobile devices. This device is not intended to replace full workstations and should be used only when there is no access to a workstation. For primary interpretation and review of mammography images, only use display hardware that is specifically designed for and cleared by the FDA for mammography.

CARESTREAM Vue PACS is an image management system whose intended use is to provide completely scalable local and wide area PACS solutions for hospital and related institutions/sites, which will archive, distribute, retrieve and display images and data from all hospital modalities and information systems.

It is a software only solution that contains interactive tools in order to ease the process of analyzing and comparing three dimensional (3D) images. It is a single system that integrates the review, dictation and reporting tools that creates a productive work environment for the radiologists and physicians.

Vue PACS provides functionality to allow remote site access to image and patient data enabling diagnostic reading through industry standard interfaces. It is designed using an open architecture that allows for various proprietary and off the shelf software components to be integrated with off the shelf hardware components and configured meeting the user's specific needs in a single-site or multi-site environment.

CARESTREAM Vue Motion is a Light Viewer designed to provide wireless and portable access to medical images for remote reading or referral purposes from web browsers including enterprise distribution of the radiology images and related data. The needs to provide real time imaging results and imaging related data to the enterprise users' commands that imaging solutions have a simple distribution mechanism through simple and broadly used technology. The patient portfolio is made available to physicians from their offices within their EMR. from home on local PC's or remotely through tablet and other devices. With integration into EMR systems, Vue Motion helps hospital users and healthcare facilities enhance patient care, by bringing the complete patient imaging record and supporting data into the healthcare enterprise. Image storage, viewing and distribution becomes a seamless part of the EMR.

A "patient search page", including smart Google-like search capabilities is also available for users that have no local EMR/HIS integration.

Vue Motion is offered as an option for the PACS, Vue Archive (onsite or via Vue Cloud) or The Carestream Vendor Neutral Archive and provides a zero footprint imaging viewer that can be deployed on the fly and accessible by the right user from anywhere, over virtually any operating system or over virtually any browser enabled device. The software technology uses HTML5 which allows any browser enabled device to run the software application.

CARESTREAM Vue Motion has a simpler GUI for viewing including zoom, pan, windowing, basic measurements, cine etc. It works on any operating system and with virtually any browser enabled device such as PC's, iPad, mobiles etc. It is selfdeployable and performs well over low bandwidth networks. It supports collaboration with other users through the sticky notes mechanism.

The provided text describes the CARESTREAM Vue PACS v11.4 Vue Motion, an image management system with mobile access capabilities. It outlines the product's description, intended use, and technological characteristics, as well as its substantial equivalence to a predicate device.

However, the document does not explicitly state specific acceptance criteria in a quantitative or pass/fail manner, nor does it detail a formal study with a defined test set, ground truth establishment, or expert involvement. Instead, it broadly describes testing activities.

Here's an analysis based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

As specific quantitative acceptance criteria are not explicitly stated, the table below presents the types of performance aspects tested and the overall reported outcome.

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

• Sample Size for Test Set: Not explicitly stated as a numerical count of cases or images. The document refers to "each of the devices" (Apple iPad2, Apple iPhone 4S, Galaxy S3, and Galaxy Note 10.1) being tested.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions "Vue Motion images of diagnostic quality" were used but doesn't detail their source or type.

3. Number of Experts and Qualifications for Ground Truth Establishment

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. It only states that "Clinical Assessments" were performed, implying involvement of medical professionals, but their number and specific qualifications (e.g., radiologists, years of experience) are not detailed.

4. Adjudication Method for the Test Set

• Adjudication Method: Not specified. The document does not describe any multi-reader review or consensus process for clinical assessment.

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

• MRMC Study Done: No. The document does not mention an MRMC study comparing human readers with and without AI assistance. The focus is on demonstrating that the device itself can display images of diagnostic quality and is equivalent to the predicate PACS.
• Effect Size of Human Readers Improvement with AI vs. without AI: Not applicable, as no MRMC study was performed.

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

• Standalone Performance Done: This device is an image display and management system, not primarily an AI algorithm for diagnostic interpretation. Its performance is tied to its ability to render medical images accurately on specified mobile devices. The "Bench Testing" and "Functional QA testing" could be considered components of standalone performance for the software/device combination, but not in the context of an AI diagnostic algorithm's standalone accuracy. The "Clinical Assessments" evaluate the display capabilities for human diagnostic use, rather than an algorithm's diagnostic output.

7. Type of Ground Truth Used

• Type of Ground Truth: For the "Clinical Assessments," the implicit ground truth seems to be the widely accepted understanding of "diagnostic quality" for medical images when viewed on the tested devices, presumably benchmarked against a full diagnostic workstation (the predicate PACS). This is not an explicit ground truth like pathology reports or patient outcomes data, but rather a qualitative assessment of display fidelity suitable for diagnosis by human users.

8. Sample Size for the Training Set

• Sample Size for Training Set: Not applicable. This document describes a PACS and mobile viewer, not a machine learning or AI model that requires a "training set" in the conventional sense. The "training" here would refer to the software development and quality assurance processes.

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

• Ground Truth for Training Set: Not applicable, as it's not an AI/ML system with a conventional training set. The "ground truth" for the software development and testing would be the functional requirements and specifications of the PACS and mobile viewer, ensuring it correctly processes, transmits, and displays DICOM images in accordance with industry standards and clinical needs.

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