(246 days)
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:
| Acceptance Criteria (from Radiologists' Rating) | Reported Device Performance (Vitrea View vs. Reference System) |
|---|---|
| Visualization of the adipose and fibroglandular tissue | Met clinical equivalence for diagnostic quality |
| Visualization of the breast tissue and underlying pectoralis muscle | Met clinical equivalence for diagnostic quality |
| Image contrast for differentiation of subtle tissue density differences | Met clinical equivalence for diagnostic quality |
| Sharpness, assessment of the edges of fine linear structures, tissue borders and benign calcifications | Met clinical equivalence for diagnostic quality |
| Tissue visibility at the skin line | Met clinical equivalence for diagnostic quality |
| Artifacts due to image processing, detector failure and other external factors to the breast | Met clinical equivalence for diagnostic quality |
| Overall clinical image quality | Met clinical equivalence for diagnostic quality |
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.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).