The xViewNet software is intended as a display and analysis tool for the interpretation of diagnostic images by trained healthcare professionals, including radiologists, physicians, technologists, clinicians and nurses. It is also intended to provide access to covered entities for clinical review, throughout the healthcare facility and at the point of image acquisition.

This device is not intended for mammography use

Device Description

x ViewNet is a secured imaging system that is used to view, edit, manipulate, annotate, analyze, and store images and data that are stored and managed in the web-based RIS. This software-based product provides capabilities for the acceptance, transmission, printing, display, storage, editing and digital processing of medical images and associated data.

Images sent to xViewNet are converted into formats suitable for viewing in its framework, and temporarily stored in a local cache memory. The algorithms used by xViewNet to view JPEG and JPEG 2000 images follow known and acceptable protocols. Changes may be made to the presentation of the images. These changes are saved as display definitions only and do not alter the acquired image pixel data. Any and all display definitions applied to an image can always be reversed to the acquired state.

The xViewNet software includes advanced visualization such as 3-D multiplanar reconstruction of the 2-D images.

x ViewNet uses standard "off-the-shelf" PC hardware and communicates using the standard TCP/IP stack. The network hardware used to support the TCP/IP stack is superfluous to XViewNet.

AI/ML Overview

The provided text describes a Picture Archiving and Communications System (PACS) called xViewNet. However, it does not contain detailed information about specific acceptance criteria, a comprehensive study proving device performance against those criteria, or a comparative effectiveness study with human readers.

Here's an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document broadly states: "The xViewNet program complies with the voluntary standards as detailed in Section 9 of this submission." and "There are no substantial differences between the xViewNet defined in this 510(k) submission and the stated predicate devices. They are similar to the technologies that are currently used in other similar medical devices."

Without access to "Section 9 of this submission" or specific performance metrics from the predicate devices, it's impossible to create a table of acceptance criteria and reported device performance. The document focuses on showing substantial equivalence to predicate devices rather than proving specific performance against quantitative acceptance criteria for things like diagnostic accuracy, speed, or image quality as one might find in a study specifically designed for AI/algorithm performance.

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

The document does not specify a test set sample size or data provenance (e.g., country of origin of data, retrospective/prospective). It mentions "Testing on unit level (Module Verification)", "Integration testing (System Verification)", and "Final Acceptance Testing (Validation)", but these are general quality assurance steps, not detailed descriptions of a clinical or performance study with a defined test set.

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

This information is not provided. The document does not describe the establishment of a ground truth for a test set.

4. Adjudication Method for the Test Set:

This information is not provided as no specific test set or ground truth establishment is described.

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

No MRMC comparative effectiveness study is mentioned. The document focuses on the xViewNet PACS as a display and analysis tool, not as an AI-powered diagnostic aide that would augment human readers in a quantitative way requiring such a study for a 510(k) submission of this nature. The "AI" term wasn't as prevalent in this context at the time of this filing (2000/2008).

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study:

No standalone study is described. The device is intended as a "display and analysis tool for the interpretation of diagnostic images by trained healthcare professionals," clearly indicating a human-in-the-loop system.

7. Type of Ground Truth Used:

Not applicable, as no specific ground truth for a performance study is described. The document discusses system verification and validation regarding functionality and safety, not diagnostic accuracy against a ground truth.

8. Sample Size for the Training Set:

Not applicable. This device is a PACS, not an AI/machine learning algorithm requiring a "training set" in the modern sense. Its primary functions are image display, manipulation, storage, and communication.

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

Not applicable, for the same reasons as above.

Summary of Study Information Available in the Document:

The document outlines the following general testing and quality assurance measures applied during the development of xViewNet:

Risk Analysis
Requirements Reviews
Design Reviews
Testing on unit level (Module Verification)
Integration testing (System Verification)
Final Acceptance Testing (Validation)
Performance Testing
Safety Testing

The manufacturer certifies that the software was "designed, developed, tested and validated according to written procedures" and refers to "Section 16. Software, item 7. Verification & Validation Testing" for details, which are not included in the provided text.

Conclusion:

The provided 510(k) summary for xViewNet PACS focuses on establishing substantial equivalence to predicate devices (iSite Radiology and iPACS Prism) based on its intended use, technical characteristics, and quality assurance processes, rather than presenting a detailed clinical or performance study with specific acceptance criteria, ground truth, or statistical analysis of algorithmic performance. This approach is typical for PACS systems seeking 510(k) clearance, where the primary concern is safe and effective display, storage, and communication of medical images, and not necessarily the diagnostic accuracy of an embedded AI diagnostic algorithm.

Summary

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510(k) Summary (per 21 CFR 807.92)

FEB
22
2000

I. Applicant: American Radiologist Network, Inc. 2298 N.W. 60th Street Boca Raton, FL. 33496, U.S.A

Neil Iyer, President & CEO Contact Person: Tel: 805-906-1360 Fax: 805-520-0568 e-mail: neil@amradnet.com

II. Device Name

Proprietary Name: xViewNet Picture Archiving and Communications System Common/ Usual Name: Classification Name: System, Image Processing, Radiological Regulation Number: 892.2050 LLZ Product Code: 2 Classification:

III. Predicate Device

The xViewNet PACS is substantially equivalent to the following predicate devices:

iSite Radiology (K013630) from Stentor Inc. .
. iPACS Prism (K030751) from Real Time Image Inc.

IV. Intended Use of the Device

This device is not intended for mammography use

V. Description of the Device

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acceptance, transmission, printing, display, storage, editing and digital processing of medical images and associated data.

The xViewNet software includes advanced visualization such as 3-D multiplanar reconstruction of the 2-D images.

x ViewNet uses standard "off-the-shelf" PC hardware and communicates using the standard TCP/IP stack. The network hardware used to support the TCP/IP stack is superfluous to XViewNet.

VI. Technical Characteristics

Support for the DICOM 3.0 file specification, including all standard . classes and modalities (CR, CT, MR, NM, US, RF, SC, VL, etc.)
Overview of study or series with different filter possibilities t
Interactive scrolling through picture series .
Thumbnail view of different picture series .
Tools freely configurable to the different mouse buttons .
Interactive change of W/L or W/C .
Picture zoom with pixel interpolation ●
Magnifying glass .
Panning of pictures .
Shows modality-dependent DICOM header information in each picture .
Placing and show values of grey tones (numeric), distances and angles . (graphic and numeric), text annotations, ellipses, polygons, and arrows
Several picture series can be shown side by side .
Allocation of picture by free layout choice .
Turn picture, reflect picture and invert picture .
Fast Interactive 3D volume rendering .
Coronal, Axial and Sagittal views .
x ViewNet is able to read and display the HUGO dataset .
Fast continuous looping display of images in a series (cine-loop) at . various speeds: forwards, backwards, and bi-directional

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Linking and Unlinking of windows to coordinate actions (window/level, . panning, zooming, etc)

VII. Testing

The xViewNet program complies with the voluntary standards as detailed in Section 9 of this submission.

The following quality assurance measures were applied to the development of the MedViewNet program:

Risk Analysis .
Requirements Reviews .
Design Reviews .
Testing on unit level (Module Verification) .
Integration testing (System Verification) .
Final Acceptance Testing (Validation) .
Performance Testing .
Safety Testing .

American Radiologist Network certifies that the x ViewNet software is designed, developed, tested and validated according to written procedures. These procedures identify individuals within the organization responsible for developing and approving product specifications, coding and testing, validation testing and field maintenance.

For details please see Section 16. Software, item 7. Verification & Validation Testing.

VIII. Safety and Effectiveness

There are no substantial differences between the xViewNet defined in this 510(k) submission and the stated predicate devices. They are similar to the technologies that are currently used in other similar medical devices.

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Image /page/3/Picture/1 description: The image shows the logo for the U.S. Department of Health and Human Services. The logo consists of a stylized eagle or bird-like symbol with three curved lines representing its wings or body. The text "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" is arranged in a circular fashion around the symbol.

FEB 22 2008

Food and Drug Administration 9200 Corporate Blvd. Rockville MD 20850

American Radiologist Network, Incorporated % Mr. James W. Monroe Staff Engineer -- Medical Devices Intertek Testing Services NA, Incorporated 2307 East Aurora Road Unit B7 TWINSBURG OH 44087

Re: K080290

Trade/Device Name: xViewNet PACS Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: February 1, 2008 Received: February 4, 2008

Dear Mr. Monroe:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.

If your device is classified (see above) into either class II (Special Controls) or class III (Premarket Approval), it may be subject to such additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Image /page/3/Picture/10 description: The image is a circular logo with the letters "FDA" in large, bold font in the center. Above the letters, the numbers "1906-2006" are printed. Below the letters, the word "Centennial" is written in cursive. The logo is surrounded by a circular border with text and stars. The text is difficult to read due to the image quality.

Protecting and Promoting Public Health

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Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The FDA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.

If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Center for Devices and Radiological Health's (CDRH's) Office of Compliance at one of the following numbers, based on the regulation number at the top of this letter.

21 CFR 876.xxxx	(Gastroenterology/Renal/Urology)	240-276-0115
21 CFR 884.xxxx	(Obstetrics/Gynecology)	240-276-0115
21 CFR 892.xxxx	(Radiology)	240-276-0120
Other		240-276-0100

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding postmarket surveillance, please contact CDRH's Office of Surveillance and Biometric's (OSB's) Division of Postmarket Surveillance at 240-276-3474. For questions regarding the reporting of device adverse events (Medical Device Reporting (MDR)), please contact the Division of Surveillance Systems at 240-276-3464. You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (240) 276-3150 or at its Internet address http://www.fda.gov/cdrb/industry/support/index.html.

Sincerely vours.

Nancy C. Brogdon

Nancy C. Brogdon Director, Division of Reproductive. Abdominal, and Radiological Devices Office of Device Evaluation Center for Devices and Radiological Health

Enclosure

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Image /page/5/Picture/0 description: The image is a circular emblem or seal with text around the perimeter. The text reads "PUNJAB RAJYA BIJLI BOARD AMRADHET". In the center of the emblem is a stylized design that includes geometric shapes, possibly representing electrical components or a power grid. The design is symmetrical and appears to be a logo for an organization related to electricity or power in the Punjab region.

510(k) Number (if known):

K080290

Device Name: xViewNet

Indications for Use:

xViewNet is a secured imaging software system that receives medical images and data from various imaging sources. Images and data can be stored, communicated, processed and displayed within the system and or across computer networks at distributed locations.

This device is not intended for mammography use

Prescription Use (Part 21 CFR 801 Subpart D) AND/OR

Over-The-Counter Use (21 CFR 801 Subpart C)

(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)

Concurrence of CDRH, Office of Device Evaluation (ODE)

Agni De Whas

(Division Sign-Off Division of Reproductive, Abdomina and Radiological Devic 510(k) Number

Page 1 of

Page 4-1

Regulation Number and Section

§ 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).