The AlgoMedica PixelShine System is intended for networking, communication, processing and enhancement of CT images in DICOM format. It is specifically indicated for assisting professional radiologists and specialists in reaching their own diagnosis. The device processing is not effective for lesion, mass or abnormalities of sizes less than 3.0 mm The AlgoMedica PixelShine is not intended for use with or for diagnostic interpretation of mammography images.

Device Description

PixelShine is a medical imaging application that can receive, transfer and perform noise reduction of CT DICOM images over a user network. Received images are processed by the PixelShine to reduce noise, thereby enhancing image quality.

AI/ML Overview

The provided text, a 510(k) summary for the AlgoMedica PixelShine, does not contain the specific details required to fully address all parts of your request regarding acceptance criteria and a detailed study proving device performance. The document focuses on regulatory clearance by demonstrating substantial equivalence to a predicate device, rather than providing the full technical report of a performance study with quantitative results and specific ground truth methodologies.

However, I can extract the available information and highlight what is missing based on your request.

Here's a breakdown of the information that is available and what is not:

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

Acceptance Criteria (Implicit/General): The document states that "The results of the performance testing demonstrate the safety and effectiveness of the PixelShine." It also mentions "The device processing is not effective for lesion, mass or abnormalities of sizes less than 3.0 mm," which can be interpreted as a functional limitation or an implicit performance boundary, rather than an acceptance criterion for the algorithm's performance on such abnormalities.
Reported Device Performance: The document does not provide quantitative performance metrics (e.g., sensitivity, specificity, AUC, noise reduction percentages, CR rates) from a study against specific acceptance criteria. It only states that "All of the testing was performed with the use of an approved testing protocol" and that "All of the testing was performed with satisfactory results."

Missing Information: Specific numerical acceptance criteria for metrics like noise reduction, contrast-to-noise ratio improvement, image quality scores, or diagnostic accuracy, and the corresponding quantitative results obtained by the device in a study.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Sample Size for Test Set: Not specified. The document mentions "the use of phantoms and the comparison of collected image data," but does not give a number of images, cases, or patients in the test set.
Data Provenance: Not specified (country of origin, retrospective/prospective). The mention of "phantoms" suggests synthetic data was used at least in part, but "collected image data" is vague.

Missing Information: Actual sample sizes for the test set (number of images/cases), and whether the data was clinical (retrospective/prospective) or entirely synthetic, and its geographical origin.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Missing Information: The document does not describe how ground truth was established for any performance testing, nor does it mention the involvement of experts for this purpose.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Missing Information: No information is provided regarding any adjudication method for ground truth establishment.

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

Missing Information: The document does not mention any MRMC study. Its primary claim is substantial equivalence to a predicate device, not an improvement in human reader performance with AI assistance. The intended use statement says it is "for assisting professional radiologists and specialists in reaching their own diagnosis," but no study is presented to quantify this assistance.

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

Standalone Performance: The document implies standalone performance testing was done, as it describes "PixelShine performance has been validated through the use of phantoms and the comparison of collected image data to ascertain image quality." However, the results are merely stated as "satisfactory" without quantitative details. It describes the device's function as "noise reduction processing."

Missing Information: Quantitative results from the standalone performance testing.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Type of Ground Truth: The document mentions "use of phantoms" for validation, which suggests engineered ground truth (known noise levels, known structures). For "collected image data," the method of establishing ground truth is not described.

Missing Information: Explicit details on the type of ground truth used for "collected image data."

8. The sample size for the training set

The document describes performance testing and validation but does not discuss the machine learning model's training process or the sample size of a training set. This is typical for a 510(k) summary, which focuses on device function and safety/effectiveness for regulatory clearance.

Missing Information: No information about a training set or its sample size is provided.

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

Missing Information: As no training set information is provided, there is no discussion of how ground truth for a training set would have been established.

Summary of Available Information from the Document:

Device: AlgoMedica PixelShine (K161625)
Intended Use: Networking, communication, processing, and enhancement of CT images in DICOM format, specifically for assisting professional radiologists and specialists in reaching their own diagnosis. Not effective for lesions/abnormalities < 3.0 mm.
Function: Performs noise reduction of CT DICOM images, enhancing image quality. Based on a non-linear filter.
Performance Testing: "PixelShine performance has been validated through the use of phantoms and the comparison of collected image data to ascertain image quality." All testing yielded "satisfactory results."
Ground Truth (partially inferred): Phantoms were used, suggesting engineered ground truth. Method for "collected image data" ground truth is not specified.

This document is a regulatory submission for 510(k) clearance, which demonstrates substantial equivalence to a predicate device. It typically does not include the detailed technical reports or performance study results that would be found in a peer-reviewed publication or a full clinical study report.

Summary

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Image /page/0/Picture/1 description: The image shows the logo for the U.S. Department of Health & Human Services. The logo consists of a circular seal with the text "DEPARTMENT OF HEALTH & HUMAN SERVICES - USA" around the perimeter. Inside the circle is a stylized image of three human profiles facing to the right, stacked on top of each other.

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

September, 19, 2016

AlgoMedica % Christopher J. Devine, Ph.D. President Devine Guidance International, Inc. 4730 South Fort Apache Road, Suite 300 LAS VEGAS NV 89147

Re: K161625 Trade/Device Name: PixelShine Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: August 19, 2016 Received: August 24, 2016

Dear Dr. Devine:

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. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to 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.

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); medical device reporting (reporting of medical device-related adverse events) (21 CFR 803); 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.

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If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638 2041 or (301) 796-7100 or at its Internet address

http://www.fda.gov/MedicalDevices/Resourcesfor You/Industry/default.htm. 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 Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address

http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.

Sincerely yours.

Michael D.'Hara

For

Robert Ochs, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health

Enclosure

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Indications for Use

Form Approved: OMB No. 0910-0120 Expiration Date: January 31, 2017 See PRA Statement below.

510(k) Number (if known)

к161625

Device Name PixelShine

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
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2 Prescription Use (Part 21 CFR 801 Subpart D)

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

CONTINUE ON A SEPARATE PAGE IF NEEDED.

This section applies only to requirements of the Paperwork Reduction Act of 1995.

DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.

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Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov

"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."

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Section Five (5) - 510(k) Summary

510(k) SUMMARY

[As Required by 21 CFR 807.92(c)]

Submitter's Name & Address:	AlgoMedica2600 El Camino RealSuite 100Palo Alto, CA 94306
Contact Person:	Christopher J. Devine, Ph.D.Telephone (702) 939-5507Mobile (702) 917-0585chris.devine@devineguidanceinternational.com
Date Summary Prepared:	June 06, 2016
Device Name:	Trade/Proprietary Name – PixelShine
	Common/Usual Name - System, Image Processing,Radiological
	Classification Name – 892.2050 - Picture archiving andcommunications system
Classification:	Class II
Product Code:	LLZ
Regulation Number:	892.2050
Predicate Device:	Medic Vision Brain Technologies, LTD – SafeCT(K100372)

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Previous FDA Submissions & Clearances

AlgoMedica has no previous regulatory submissions with the FDA.

Device Description

Intended Use

The AlgoMedica PixelShine is intended for networking, communication, processing and enhancement of CT images in DICOM format. It is specifically indicated for assisting professional radiologists and specialists in reaching their own diagnosis. The device processing is not effective for lesion, mass or abnormalities of sizes less than 3 mm The AlgoMedica PixelShine is not intended for use with or for diagnostic interpretation of Mammography images.

Prescriptive Statement

Caution: Federal law restricts this device to sale by or on the order of a physician.

Safety & Effectiveness

The PixelShine has been designed, verified and validated in compliance with 21 CFR, Part 820.30 requirements. The device has been designed to meet the requirements associated with EN ISO 14971:2012 (risk management). The PixelShine performance has been validated through the use of phantoms and the comparison of collected image data to ascertain image quality. The results of the performance testing demonstrate the safety and effectiveness of the PixelShine.

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Technological Characteristics/Principles of Operation

PixelShine is a medical imaging application that runs on an AlgoMedica-specified, customer's Off-the-Shelf Personal Computer (PC) and performs noise reduction processing and transfer of CT DICOM images over a user network. Once installed by AlgoMedica trained personnel, PixelShine operates independently, without the need for I/O devices such as mouse and keyboard. It is indicated for assisting radiologists and other medical specialists in arriving at their own diagnosis. The technology for noise reduction is based on a non-linear filter, which reduces noise in the original image. Figure 5.1 depicts a typical deployment of the PixelShine at a customer site.

PixelShine Components and Hardware Requirements

The following components and hardware requirements are an integral part of the PixelShine:

PixelShine Version 1 Software Package; .
. Linux Operating System;
DICOM Server software installed on PixelShine provides all DICOM communications: . and
. AlgoMedica specified off-the-shelf PC Hardware (minimum Requirements) containing:
- -Intel CPU with 4 cores;
- -16GB RAM;
- -500GB hard drive; and
- Two 1 Gigabit Ethernet ports -

PixelShine Functional Capabilities

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The following functions are associated with performance of the PixelShine (reference

Figure 5.1):

Operates in a network server mode environment; .
Functions as a DICOM device on the user network; .
Capable of receiving CT images from different DICOM devices over the ● network:
Capable of receiving images from multiple DICOM devices; ●
Processes the CT images upon receiving them from a DICOM device; and ●
. Sends the processed CT image to one or more destination DICOM devices.

Figure 5.1 – Pixel Shine Functional Block Diagram (deployment scenario)

Image /page/6/Figure/9 description: The image shows a diagram of a CT scanning process. The CT scanner sends original CT images to PACS and technologists' workstations. The original CT images are also sent to the AlgoMedica PixelShine Server, which enhances the quality of the images. The enhanced quality images are then sent to PACS and diagnostic workstations.

Note: PixeShine receives original CT images, processes them and routes the enhanced quality images to a PACS system. As in current practice, the technologist is able to view both the processed images on his workstation and take appropriate action as necessary. Both the original and processed images can be stored on the PACS server.

Summary of Non-Clinical Performance and Safety Testing

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The following non-clinical performance testing was performed with satisfactory results. All of the testing was performed with the use of an approved testing protocol. Details of each test, including protocols and reports are located in Appendix E of this 510(k).

Unit Integration Testing Pass; .
PixelShine System-Level-Testing Pass; .
PixelShine Verification Testing Pass; and .
PixelShine Validation Testing Pass. .

Substantial Equivalence Discussion

Medic Vision Brain Technologies Ltd. – SafeCT (K100372)

The PixelShine is substantially equivalent to the devices previously cleared by FDA (reference 510(k) – K100372). AlgoMedica claims this equivalence because the proposed device has an equivalent intended use, theory of operation, operating principals, and operational specifications as compared to the predicate device. The similarities and differences between the proposed and predicate device have been delineated within a comparison chart which has been included in Section 12 of this 510(k) submission.

Conclusion Statement

The AlgoMedica PixelShine has the same intended use as the predicate device. Any technological changes to the device do not raise new questions of safety or effectiveness. Performance testing, along with verification and validation activities demonstrate that the AlgoMedica PixelShine is as safe and effective, and performs as well as the predicate device. Therefore, the AlgoMedica PixelShine can be considered substantially equivalent to the predicate device.

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).