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e Volve PACS, is a software device used for viewing and manipulating medical images and other healthcare related electronic records. Digital imaging units (including DR, CR, CT, MR, US, RF, and 2D/3D mammography), other computed and direct radiographic devices, secondary capture devices, document and film scanners, imaging gateways, other imaging devices and healthcare related electronic records can be displayed, processed, managed, stored and communicated across computer networks using this software.

e Volve PACS, can be integrated with a facility's existing Electronic Medical Records System (EMR), Hospital Information System (HIS), Practice Management System, Radiology Information System (RIS) and Dictation System. eVolve PACS, may also be integrated with the facility's Teleradiology Provider's systems. These integrations provide seamless operation and access for Providers and other caregivers to the entire spectrum of a patient's radiology records from the Provider's orders, to images of the exam, to completion data all the way to the interpretations (results/reports).

Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretation on the eVolve PACS. Mammographic images may only be interpreted using an FDA cleared display that offers at least 5 MP resolution and meets other technical specifications reviewed and accepted by the FDA. eVolve PACS is not intended for diagnostic review or other diagnostic uses on mobile devices.

eVolve PACS, uses web-based technology and a secure operating system. This means that virtually any computer at any location can use an Internet browser to access eVolve PACS (and RIS) systems. Whether on-site or from another location, physicians can manage, edit, view and move diagnostic exams quickly and efficiently. As part of eVolve PACS support, eVolve PACS Inc., performs virtually all the system maintenance. eVolve PACS, has been designed to be expandable, with storage beginning at 2 TB and growing to 25 TB onboard or 256 TB expansion.

eVolve PACS is an implementation of an IHE (Integrating the Healthcare Enterprise) compliant Image Archive and Report Repository. This includes the capabilities:

• To store and retrieve various kinds of DICOM Objects such as:
  • Images from multiple modalities,
  • Grayscale Presentation States [GSPS], which specifies the presentations of images as gray scaling, zoom, text and graphical annotations,
  • Key Objects [KO], which specifies a particular selection of images for a specified reason and with an attached note,
  • Structured Reports [SR].
• To process HL7 notification messages from the Order Filler, about Procedure Scheduling, Procedure Updates and Patient Information Updates,
• To process DICOM Modality Performed Procedure Step [MPPS] messages from modalities and forward them to the Order Filler.

eVolve PACS is a server application. Its Web-based User Interface is intended for system configuration and monitoring by system administrators.

eVolve PACS, was developed with special emphasis on its telerad features for those facilities that use teleradiology either full time or for night reads.

The provided text describes the eVolve PACS system and its comparison to a predicate device for 510(k) clearance. However, it explicitly states that clinical testing was not necessary and that "Successful Bench Testing should be sufficient in demonstrating substantial equivalence." Therefore, there is no information in the document regarding a study involving acceptance criteria as typically understood for clinical performance, human readers, ground truth establishment, or effect sizes for AI assistance.

The document focuses on non-clinical performance data, primarily validation testing to ensure the device functions as intended and meets technical standards.

Here's a breakdown based on the information provided, highlighting what is not available from the text:

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

• Medical image management and processing system
• Web-based system architecture
• Log-on user ID & password security
• Remote monitoring functionality
• Standard image viewing layouts (up to 4x4)
• WW/WL functionality
• Zoom in/Zoom out
• Hounsfield Measurement
• Linear and angle measurements
• Series Comparison
• Scout line display
• MPR/MIP capabilities
• Stack mode
• Gray scale invert
• Filters
• Rotate
• Key Image selection
• DICOM Print
• Windows print
• Query/Retrieve
• Lossless streaming image compression
• Thumbnails selection tools
• Reporting Interface with template support, digital signature, and MS office formats (PDF, rtf, text, Docx)
• Link to Hospital Information System (HIS)
• Link to Radiology Information System (RIS)
• Electronic patient record (through Broker Software)
• HIPAA Compliant
• PACS Server
• Radiology Workstation
• Basic Image Viewer
• Mobile app viewer | Demonstrated Through:
• Comparison table showing "Yes" for all listed features/functions for both subject and predicate devices.
• "Validation testing indicated that as required by the risk analysis, designated individuals performed all verification and validation activities and that the results demonstrated that the predetermined acceptance criteria were met." |
  | Compliance with Standards:
• DICOM Set (PS 3.1 - 3.20 (2016))
• IEC 60812 Edition 3.0 2018-08 (FMEA)
• ANSI AAMI IEC 62304:2006/A1:2016 (Medical device software life cycle processes)
• FDA Guidance on Cyber Security: Content of Premarket Submissions for Management of Cybersecurity in Medical Devices (Oct 2, 2014)
• FDA Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices (May 11, 2005) | "eVolve PACS, and the device has met all the requirements listed in the Standards except for inapplicable requirements." |
  | Safety and Effectiveness Profile (Comparable to predicate device) | "Based on the performance as documented in the Validation Testing, eVolve PACS, was found to have a safe and effectiveness profile that is similar to the predicate device." |

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

• Not Applicable / Not Provided: The document states "Clinical testing is not necessary to show substantial equivalence for the subject device. Successful Bench Testing should be sufficient in demonstrating substantial equivalence." Therefore, no patient test set was used. The non-clinical testing refers to "Validation Test Plan" results but does not specify a "sample size" in terms of clinical cases or data provenance.

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

• Not Applicable / Not Provided: No clinical test set requiring expert ground truth was used.

4. Adjudication method for the test set

• Not Applicable / Not Provided: No clinical test set requiring adjudication was used.

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, not done: The device is a PACS system, not an AI-assisted diagnostic tool. No MRMC study was performed, and no AI assistance is mentioned.

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

• No, not done (and not applicable): The eVolve PACS is a software device for viewing and managing medical images, not an algorithm providing diagnostic outputs. It is explicitly stated that it "does not intend to replace the skills and judgment of a qualified physician/radiologist."

7. The type of ground truth used

• Not Applicable / Not Provided: No clinical ground truth (expert consensus, pathology, outcomes data) was used, as no clinical study was deemed necessary. The "ground truth" for the non-clinical validation was likely the expected functional behavior and compliance with technical standards.

8. The sample size for the training set

• Not Applicable / Not Provided: No machine learning or AI models are described as being part of this device, therefore, no training set data would be relevant or provided.

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

• Not Applicable / Not Provided: No machine learning or AI models are described.

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