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Vitrea View software is a medical image viewing and information distribution that provides access, through the internet and within the enterprise to multi-modality softcopy medical images (including mammography and digital breast tomosynthesis), reports, and other patient-related information. This data is hosted within disparate archives and repositories for diagnosis, review, communication, and reporting of DICOM and non-DICOM data.

Lossy compressed mammography images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA cleared display that meets technical specifications reviewed and accepted by FDA or displays accepted by the appropriate regulatory agency for the country in which it is used.

Display monitors used for reading medical images for diagnostic purposes must comply with the applicable regulatory approvals and quality control requirements for their use and maintenance.

Vitrea View software is indicated for use by qualified healthcare professionals including, but not restricted to. radiologists, non-radiology specialists, physicians and technologists.

When accessing Vitrea View software from a mobile device, images viewed are for informational purposes only and not intended for diagnostic use.

The Vitrea View software is a web-based, cross-platform, zero-footprint enterprise image viewer solution capable of displaying both DICOM and non-DICOM medical images. The Vitrea View software enables clinicians and other medical professionals to access patients' medical images with integrations into a variety of medical record systems, such as Electronic Health Record (EHR), Electronic Medical Record (EMR), Health Information Exchange (HIE), Personal Health Record (PHR), and image exchange systems. The Vitrea View software is a communication tool, which supports the physician in the treatment and planning process by delivering access to images at the point of care.

The Vitrea View software offers medical professionals an enterprise viewer for accessing imaging data in context with reports from enterprise patient health information databases, fosters collaboration, and provides workflows and interfaces appropriate for referring physicians and clinicians. IT departments will not have to install client systems, due to the web-based zero-footbrint nature of the Vitrea View software. The Virea View software offers scalability to add new users as demand grows, and may be deployed in a virtualized environment. Some of the general features include:
. Fast time-to-first-image

• Contextual launch integration with single-sign-on
• . Easy study navigation and search capability
• Supports multi-modality vendor-neutral DICOM images
• . Supports non-DICOM images
• lmages display at full diagnostic quality (with appropriate hardware)
• . Basic 2D review tools (zoom, pan, measure)
• Basic 3D and MPR viewing
• Radiology key images
• . Comparative side-by-side review, regardless of image types
• . Collaboration tools
• . Leverages traditional DICOM as well as next-generation DICOMweb image transfer protocols
• Enables federated access to across multiple data sources across multiple sites
• . Web-based zero-footprint architecture
• Secure Access on various Windows® and Mac computers through standard internet
• browsers
• . Secure Access on various iOS®, Android™, and Windows® tablet devices through the device's Internet browser
• . Secure Access on various iOS and Android smartphones through the device's Internet browser

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

Device Name: Vitrea View
510(k) Number: K163232

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Mammography Image Quality Validation: 50 studies.
  • Data Provenance: Studies were "chosen randomly from existing patient studies obtained over a two-day time-frame at the designated Breast Imaging center." This indicates retrospective data from a specific imaging center.
• Digital Breast Tomosynthesis Image Quality Validation: 50 studies.
  • Data Provenance: Studies were "chosen randomly from existing patient studies obtained at the designated Breast Imaging center." This also indicates retrospective data from a specific imaging center.

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

• Mammography Image Quality Validation: Four experienced radiologists. No further specific qualifications (e.g., years of experience) are provided.
• Digital Breast Tomosynthesis Image Quality Validation: Three experienced radiologists. No further specific qualifications are provided.

4. Adjudication Method for the Test Set:

The studies were multi-reader, multi-case tests where radiologists were asked to rate image quality equivalence. The text states:

• "The radiologists found all of the images displayed met the clinical equivalence for diagnostic quality when displayed using the Vitrea View software as compared to the same studies displayed using the McKesson system."
• "The radiologists found all of the images displayed met the clinical equivalence for diagnostic quality when displayed using Vitrea View as compared to the same studies using the sites existing Phillips Radiology system."
  This suggests a consensus or agreement among the radiologists was reached, rather than a formal adjudication method like a 2+1 or 3+1 rule. The criteria were rating the image quality on a scale of 1 to 3, but the specifics of how these individual ratings were combined or adjudicated to reach the overall "met clinical equivalence" conclusion are not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance:

Yes, MRMC studies were done for both mammography and digital breast tomosynthesis. However, these were not comparative effectiveness studies evaluating human reader improvement with AI assistance. Instead, they were image quality equivalence studies comparing the device's display quality against a cleared predicate/reference device. The purpose was to show that images displayed by "Vitrea View software... met the clinical equivalence for diagnostic quality" when compared to a reference system displaying the same images. Therefore, an effect size of human improvement with AI vs. without AI is not applicable to these studies.

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

No, the studies described were focused on the display quality of the Vitrea View software in conjunction with diagnostic monitors, for review by human radiologists. It was not a standalone algorithmic performance evaluation.

7. The Type of Ground Truth Used:

The ground truth was established by the subjective rating of "experienced radiologists" on the "overall clinical image quality" and other specific image quality parameters. This is effectively expert consensus on image quality and clinical equivalence for diagnostic use. It does not appear to involve pathology or outcomes data to define disease presence or absence.

8. The Sample Size for the Training Set:

The document does not specify a training set or its size. The studies described are verification and validation of the device's performance, not the training of a machine learning model.

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

Not applicable, as no training set or ground truth establishment for a training set is mentioned in the provided text.

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McKesson Radiology Mammography Plus™ ("Mammography Plus"), is an accessory to McKesson Radiology Station™, a component of McKesson Radiology™. McKesson Radiology is medical image and information management software that is intended to receive, transmit, store, archive, manage, display, print and process digital medical images, digital medical video and associated patient and medical information. McKesson Radiology™ includes a suite of standalone, web-enabled software components, and is intended for installation and use with off-the-shelf hardware that meets or exceeds minimum specifications.

McKesson Radiology Station™ is the primary software component used for processing and presentation of medical images on display devices with network access to McKesson Radiology. McKesson Radiology Station is intended to process and display lossless and non-lossed medical images provided from DICOM conformant modalities such as X-Ray Radiography (including digital mammography), X-Ray Computed Tomography, Magnetic Resonance Imaging. Ultrasound, and Nuclear Medical images obtained from other DICOM-compliant modalities.

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations.

Mammographic images may only be interpreted using cleared monitors intended for mammography display.

McKesson Radiology is indicated for use by qualified healthcare professionals including, but not restricted to, radiologists. non-radiology specialists, physicians and technologists.

Mammography Plus, an accessory to the McKesson Radiology Station, the radiology viewing component of McKesson Radiology, consists of image display and manipulation tools that help radiologists zoom in onto an image, interpret Computer Aided Detection (CAD) findings, navigate through and visualize digital mammography and Digital Breast Tomosynthesis (DBT) images, compare historically similar images, and configure their reading environment.

Mammography Plus uses the underlying capabilities of McKesson Radiology's diagnostic viewer, McKesson Radiology Station, to integrate specialized functionality into the diagnostic reading workflows. The McKesson Radiology Station viewer interfaces with the McKesson Radiology Platform to access patient and study information.

Here's an analysis of the provided text regarding the acceptance criteria and study for the McKesson Radiology Mammography Plus device:

The provided documents (K142850) do not contain typical acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, AUC) or a dedicated clinical study demonstrating these metrics against ground truth. Instead, the submission focuses on verifying the device's functionality and image quality against established standards and its substantial equivalence to a predicate device for its intended use as a PACS accessory with mammography viewing and manipulation tools.

The "Performance Data" section describes verification and validation testing, which are typically aimed at ensuring the device meets its design specifications and complies with relevant regulatory and consensus standards.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not provide specific quantitative "acceptance criteria" related to diagnostic performance (e.g., sensitivity, specificity) for the device itself. The acceptance is based on functional verification, compliance with standards, and demonstration of substantial equivalence.

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

The document does not describe a "test set" in the context of a diagnostic performance study with patient data. The testing described is primarily focused on functional verification, image quality assessment, and usability. Therefore, there is no information provided on the sample size or data provenance (country, retrospective/prospective) for a clinical test set as one would typically find for a diagnostic AI algorithm.

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

As there is no mention of a diagnostic performance study with a clinical test set, there is no information provided on the number of experts or their qualifications for establishing ground truth for such a test set.

4. Adjudication Method for the Test Set

Since a diagnostic performance study with a clinical test set is not described, there is no information on adjudication methods.

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

The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance. The device is characterized as an accessory for image display and manipulation, not as a diagnostic AI tool that directly provides CAD findings (though it supports interpretation of CAD findings from other systems).

6. Standalone Performance Study

A standalone performance study (i.e., algorithm only without human-in-the-loop performance evaluation) for diagnostic accuracy is not described in the provided text. The device's performance is gauged by its ability to meet design specifications, adhere to industry standards for image quality and display, and its usability as an accessory.

7. Type of Ground Truth Used

For the described verification and validation, the "ground truth" is implicitly related to:

• Design Specifications: The device's intended functionality.
• Consensus Standards: (e.g., NEMA, AAPM, DICOM) which define expected behavior for image display and processing.
• Predicate Device Performance: Used for comparison in usability and image quality assessments.

There is no mention of pathology, outcomes data, or expert consensus on patient cases being used as ground truth for diagnostic accuracy in a clinical study.

8. Sample Size for the Training Set

The document does not describe a machine learning algorithm or AI model requiring a "training set." McKesson Radiology Mammography Plus is presented as software for image display, manipulation, and workflow integration for mammography images, including support for CAD findings (presumably from other CAD systems). Therefore, no information on a training set size is provided.

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

Since no training set is mentioned as part of the device's development, this information is not applicable and not provided.

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