The Microsoft® Amalga™ UIS Image Processing Module (IPM) is used in conjunction with Microsoft® Amalga™ UIS and Microsoft® Amalga™ UIS Medical Imaging Module to receive medical images from acquisition devices and imaging systems adhering to DICOM protocol. Medical images received from volumetric or planar imaging modalities are processed to derive certain information. The information thus derived is transmitted using the DICOM or HTTP protocol to other devices supporting these standard protocols.

The IPM enables physicians and other healthcare providers to rapidly navigate across images by selecting tagged organs and review them through multi-planar reconstruction (MPR). IPM is not intended to be used for primary diagnosis.

This device is not intended to be used for mammography.

Device Description

The Microsoft® Amalga™ UIS Image Processing Module (IPM) is used in conjunction with Microsoft® Amalga™ UIS and Microsoft® Amalga™ UIS Medical Imaging Module (MIM). These two software products (Amalga™ UIS and Amalga™ MIM) are Class 1 devices that perform consolidation of disparate health information (Amalga™ UIS) and medical image communication (Amalga™ MIM). Amalga™ IPM enables healthcare providers to rapidly navigate across images by selecting tagged organs and to review these images using multi-planar reconstruction (MPR).

Amalga™ IPM delivers a basic MPR rendering platform that constructs a three-dimensional view from a set of CT, MR, or PET images. Amalga™ IPM also enables organ label based navigation through DICOM CT scans both in 2D image display and MPR viewing mode.

AI/ML Overview

Here’s a summary of the acceptance criteria and study details for the Microsoft® Amalga™ UIS Image Processing Module:

1. Table of Acceptance Criteria and Reported Device Performance

Feature/Metric	Acceptance Criteria	Reported Device Performance
Accuracy of image tagging algorithm	Exceeding threshold of 81%	Ranged between 84% and 99% for 21 organs
Multiplanar Reconstruction (MPR) function	Operates properly	Confirmed to operate properly
Navigation using semantic tagging of organs	Operates properly	Confirmed to operate properly

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

The exact sample size (number of images or patients) for the test set is not explicitly stated. The document mentions "human images from a variety of databases."

Data Provenance: The data came from "a variety of databases" comprising patients with "a wide variety of medical conditions and body shapes." Scans exhibited "large differences in image cropping, resolution, scanner type and use of contrast agents." The country of origin is not specified, and it is stated as retrospective data (from existing databases).

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

Number of Experts: The document refers to "physician identified" boundaries for comparison, implying multiple physicians were involved but the exact number is not specified.
Qualifications of Experts: The experts are referred to as "physicians." Their specific specialties (e.g., radiologists) or years of experience are not provided.

4. Adjudication Method for the Test Set

The adjudication method used to establish ground truth is not specified. It mentions "physician identified" boundaries as the basis for comparison with the software's performance, but the process for resolving discrepancies among physicians or establishing a consensus is not detailed.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or described. The study focused on the standalone performance of the algorithm for image tagging.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone study was conducted. The "image tagging algorithm" was validated for its accuracy, sensitivity, specificity, and precision in identifying organ boundaries. The reported performance metrics (accuracy, sensitivity, specificity, precision) were determined for the algorithm itself.

7. Type of Ground Truth Used

The type of ground truth used for the test set was expert consensus / expert identification. Specifically, "physician identified" boundaries were used as the reference against which the software's identified boundaries were compared.

8. Sample Size for the Training Set

The sample size for the training set is not explicitly stated. The document only mentions using "human images from a variety of databases" for validation. It doesn't differentiate between training and validation/test sets in terms of sample size.

9. How Ground Truth for the Training Set Was Established

The document does not explicitly state how the ground truth for the training set was established. It only refers to "physician identified" boundaries for the validation/test phase. It's implied that the training data would also have had some form of expert-derived ground truth, but the method is not detailed.

Summary

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K120734

Microsoft Corporation Traditional 510(k) Premarket Submissio Microsoft® Amalga™ UIS Image Processing Module

AUG 2 2012

Section 5 - 510(k) Summary for

Microsoft® Amalga™ UIS Image Processing Module

1. Submission Sponsor

Microsoft Corporation 1 Microsoft Way Redmond, WA 98052 USA Phone: 301.771.8624

Contact: Michael Willingham, VP, Quality Assurance & Regulatory Affairs

Submission Correspondent 2.

Emergo Group 611 West 5th Street, Third Floor Austin, TX 78701 Cell Phone: 262-290-0023 Office Phone: (512) 327.9997 Fax: (512) 327.9998 Contact: Adrienne Lenz, Senior Consultant, QA & RA Email: project.management@emergogroup.com

Date Prepared 3.

17 July 2012

Device Name 4.

Trade/Proprietary Name: Microsoft® Amalga™ UIS Image Processing Module Common/Usual Name: Picture Archiving and Communication System Classification Name: Picture archiving and communications system Classification Regulation: 892.2050 Classification Panel: Radiology Product Code: LLZ

Device Class: 2

FDA Establishment Registration #: 3007734659

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Microsoft Corporation Traditional 510(k) Premarket Submission Microsoft® Amalga™ UIS image Processing Module

5. Predicate Devices

K061214 AquariusAPS Server, TeraRecon, Inc. K011142 AquariusAPS Workstation, TeraRecon, Inc.

6. Device Description

Intended Use

The Microsoft® Amalga™ UIS Image Processing Module is used in conjunction with Microsoft® Amalga™ UIS and Microsoft® Amalga™ Medical Imaging Module to receive medical images from acquisition devices and imaging systems adhering to DICOM protocol. Medical images received from volumetric or planar imaging modalities are processed to derive certain information. The information thus derived is transmitted using the DICOM or HTTP protocol to other devices supporting these standard protocols.

This device is not intended to be used for mammography.

7. Technological Characteristics and Substantial Equivalence

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The following table compares the features of the Microsoft® Amalga™ UIS Image Processing Module to the AquariusAPS Server and Workstation, providing the basis of substantial equivalence.

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Microsoft Corporation Traditional 510(k) Premarket Submission Microsoft® Amalga™ UIS Image Processing Module

Comparison Table

・

Trade Name	Amalga™ UIS IPM	AquariusAPS Server	AquariusAPSWorkstation
510(k) Number		K061214	K011142
Product Code	LLZ	LLZ	LLZ
Regulation Number	21 CFR 898.2050	21 CFR 898.2050	21 CFR 898.2050
Regulation Name	Picture archiving andcommunicationssystem	Picture archiving andcommunicationssystem	Picture archiving andcommunicationssystem
Platform	Amalga UIS 2009 R2SP3 and MedicalImaging Module	TeraRecon	TeraRecon
Intended for use in primarydiagnostic workflow	No	Yes	Yes
Receive images using DICOMprotocol	Yes	Yes	Yes
Send images using DICOMprotocol	Yes	Yes	Yes
MPR Visualization(Axial/Sagittal/Coronal)	Yes	No	Yes
MPR Visualization(oblique)	Yes	No	Yes
Modalities supported forMPR review	CT, MR, PET	CT, MR, PET	CT, MR, PET
Trade Name	Amalga™ UIS IPM	AquariusAPS Server	AquariusAPS
			Workstation
Identify locations of	Yes. The list of the	Yes. The list of	Yes (manual)
anatomical structures	structures are:	structures are:
	Abdomen,�Adrenal Gland●(Left/Right),Femoral Neckand head(Left/Right),Heart (Atriumand ventricle)(Left/Right),Kidney(Left/Right),Liver,Lung (Left/Right),Pelvis,●Spleen,Stomach,Thorax	Brain●HeartHeart vasculature●LiverLung
Modalities supported foridentification of anatomicalstructures	CT	СТ	ст
Manual review of identifiedanatomical structures andcorrection tools	Yes	Yes	Yes
Ability to navigate to animage displaying anidentified anatomicalstructure	Yes	Yes	Yes
Align and review two ormore sets of images side byside	Yes. Link by imagenumber for twoseries	Yes	Yes
Performing actions andimage set navigation basedon DICOM and other dataidentified from the DICOMimage set	Yes ·	Yes	No

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Microsoft Corporation Traditional 510(k) Premarket Submission Microsoft® Amalga™ UIS Image Processing Module

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Microsoft Corporation Traditional 510(k) Premarket Submission Microsoft® Amalga™ UIS Image Processing Module

8. Non-Clinical Testing

Support for the substantial equivalence of the Microsoft® Amalga™ UIS Image Processing Module was provided as a result of risk management and software validation, which confirmed all features of the Microsoft® Amalga™ UIS Image Processing Module were compliant with the software requirements: The Microsoft® Amalga™ UIS Image Processing Module operates properly for multiplanar reconstruction and navigation using semantic tagging of organs.

9. Clinical Testing

Validation of the image tagging algorithm was completed using human images from a variety of databases. These databases comprise patients with a wide variety of medical conditions and body shapes and the scans exhibit large differences in image cropping, resolution, scanner type and use of contrast agents. Comparison between physician identified and software identified boundaries confirmed suitable accuracy and efficiency of the image tagging algorithm. Sensitivity, specificity, accuracy and precision were determined for each of the 21 organs. Accuracy ranged between 84% and 99%, exceeding the predetermined threshold of 81%.

10. Conclusion

It has been shown in this 510(k) submission that the difference between the Microsoft® Amalga™ UIS Image Processing Module and the predicate device does not raise any questions regarding its safety and effectiveness. The conclusions drawn from the nonclinical tests demonstrate equivalent performance of the Microsoft® Amalga™ UIS Image Processing Module and the predicate devices. The Microsoft® Amalga™ Image Processing Module, as designed and manufactured is determined to be substantially equivalent to the referenced predicate devices.

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Image /page/5/Picture/0 description: The image shows a circular seal with the words "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" written around the perimeter. In the center of the seal is a stylized eagle emblem. The eagle is depicted with its wings spread, and its body is formed by three curved lines.

DEPARTMENT OF HEALTH & HUMAN SERVICES

Public Health Service

Food and Drug Administration 10903 New Hampshire Avenue Document Control Room - WO66-G609 Silver Spring. MD 20993-0002

Caradigm % Ms. Adrienne Lenz Senior Consultant, QA and RA Emergo Group 611 West 5th Street, Third Floor AUSTIN TX: 78701

Re: K120734

Trade/Device Name: Microsoft® Amalga™ UIS Image Processing Module Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: July 17, 2012 Received: July 18, 2012

Dear Ms. Lenz:

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 class II (Special Controls), it may be subject to such additional controls. Existing major regulations affecting your device can be found in Title 21, Code of Federal Regulations (CFR), Parts 800 to 895. In addition, FDA may publish further announcements concerning your device in the Federal Register.

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 Parts 801 and 809); medical device reporting (reporting of ^

AUG 2 2012

1 22-7

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medical device-related adverse events) (21 CFR 803); and good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820). 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 Parts 801 and 809), please contact the Office of In Vitro Diagnostic Device Evaluation and Safety at (301) 796-5450. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.

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 (301) 796-7100 or at its Internet address http://www.fda.gov/cdrh/industry/support/index.html.

Sincerely Yours,

Janine M. Morris

Acting Director Division of Radiological Devices Office of In Vitro Diagnostic Device Evaluation and Safety Center for Devices and Radiological Health

Enclosure

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Microsoft Corporation Traditional 510(k) Premarket Submission Microsoft® Amalga™ UIS Image Processing Module

Section 4 - Indications for Use Statement

510(k) Number (if known): Not Assigned

Device Name: Microsoft® Amalga™ UIS Image Processing Module

Indications for Use:

This device is not intended to be used for mammography.

Prescription Use X (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 In Vitro Diagnostic Devices (OIVD)

Office of In Vitro Diagnostic Device Evaluation and Safe

510(k) K120734

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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).