Zia™ Image Enhancement System is an image processing software that can be used for reducing noise in CT images. Enhanced images will be uploaded back to host/PACS systems and exist in conjunction to the original images. Zia™ is not intended for mammography applications. The device processing is not effective for lesion, mass, or abnormalities of sizes less than 2mm.

Device Description

Zia™ Image Enhancement System is an image processing software that can be used for reducing noise in CT images. Zia™ image enhancement software is based on a core noise reduction algorithm that reduces noise in flat regions via a regularization process while keeping the edges via data fidelity constrains. The software, which is installed on a remote computer, receives DICOM images from CT host computer (Zia DICOM node needs to be configured on the scanner), automatically processes the received images and uploads the post processed images back on to the host computer and/or other PACS systems. Enhanced images exist in conjunction to the original images.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study details for the Zia™ Image Enhancement System based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

Performance Metric	Acceptance Criteria	Reported Device Performance	Test Result
Noise Reduction	Reduces noise in processed images by at least 10%	Reduced noise in processed images by at least 10%	PASS
CT# (Signal) Accuracy	Keeps CT# (signal) accuracy within +/- 1.0 HU	Kept CT# (signal) accuracy within +/- 1.0 HU	PASS
High Contrast Resolution	Maintains (preserves) high contrast resolution	Maintained (preserved) high contrast resolution	PASS
Low Contrast Resolution	Maintains (preserves) low contrast resolution	Maintained (preserved) low contrast resolution	PASS

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

Sample Size: A total of 81 datasets were processed and analyzed.
Data Provenance: The data was generated using an ACR CT PHANTOM (Model 464) on three different CT scanners: GE BrightSpeed 4-Slice, Siemens Sensation 16-Slice, and Philips Brilliance 64-Slice. The images were acquired following specific protocols (Head 120KV, Head 80KV, and Body 120KV) with varying mAs (150-350mAs) and slice thicknesses (1.25-5mm). This indicates a controlled, simulated environment using a phantom, not retrospective or prospective patient data from a specific country of origin.

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

The document does not mention the use of human experts to establish ground truth for the test set. The ground truth appears to be based on physical measurements of the ACR CT phantom.

4. Adjudication Method for the Test Set:

Not applicable, as human experts were not used for establishing ground truth or evaluating the test set. The performance was measured quantitatively using the phantom.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The study focuses on the technical performance of the image processing software itself, not its impact on human reader performance.

6. Standalone Performance Study:

Yes, a standalone study was performed. The device's performance (noise reduction, CT# accuracy, contrast resolution) was evaluated directly by analyzing the processed images from the CT phantom, without human-in-the-loop.

7. Type of Ground Truth Used:

The ground truth used was based on the physical characteristics and known properties of the ACR CT PHANTOM (Model 464). Measurements of CT# and noise were obtained from specific regions of interest (ROIs) within the phantom, and resolution was assessed based on the phantom's design.

8. Sample Size for the Training Set:

The document does not specify a separate training set or its sample size. The description of the device's core algorithm as reducing noise in flat regions while keeping edges suggests it's a rule-based or model-based algorithm, rather than a machine learning algorithm requiring a separate, large training set with annotated data.

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

Not explicitly stated. Given the description of the algorithm, it likely relies on mathematical principles and image processing techniques. If there was any "training" in a general sense, it would have involved developing and refining these algorithms based on general image characteristics rather than a labeled training dataset with a specific ground truth.

Summary

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

December 15, 2016

Zetta Medical Technologies, LLC. % Mr. Main Ghazal President 1313 Ensell Road LAKE ZURICH IL 60047

Re: K160852 Trade/Device Name: Zia™ Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: November 4, 2016 Received: November 4, 2016

Dear Mr. Ghazal:

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 O'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

510(k) Number (if known) K160852

Device Name Zia™м

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary of Safety and Effectiveness

This 510(k) summary of safety and effectiveness is being submitted in accordance with the requirement of Titles 21 CFR §807.87 and 807.92.

1. Applicant & Submitted By:

Zetta Medical Technologies, LLC. 1313 Ensell Road, Lake Zurich, IL 60047 Phone: (847) 550-9990 Fax: (847) 550-9994 Contact Person: Main M. Ghazal, President Date Prepared: November 2nd 2016

2. Identification of the Device:

Trade Name: Zia™ Common Name: Image Enhancement System Classification Name: Image Processing System, Radiological (21 CFR, 892.2050, LLZ) Regulatory Description: Picture Archiving and Communications System

3. Predicate Device:

Context Vision Sharp View Image Enhancement System, K024028

4. Indications for Use:

5. Device Description:

6. Substantial Equivalence Table

The subject device Zia™ is substantially equivalent to the predicate device, Sharp View Image Enhancement System, which is also used for image enhancement. The main difference is that Sharp View Image Enhancement System is multimodality image transfer/storage/enhancement system where as Zia (as of 10/27/2016) is strictly a CT

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image enhancement system. Detailed differences between Zia and Sharp view systems are listed in Table-1.

Characteristics	Zia™	Sharp View Image Enhancement System
Indications for Use	Zia™ Image EnhancementSystem is an imageprocessing software thatcan be used for reducingnoise in CT images.Enhanced images will beuploaded back tohost/PACS systems andexist in conjunction to theoriginal images. Zia™ isnot intended formammographyapplications. The deviceprocessing is not effectivefor lesion, mass, orabnormalities of sizes lessthan 2mm.	The Image EnhancementSystem is intended for use by aqualified/trained technologistfor transfer, storage,enhancement and viewing ofmulti-modality images.
ComputerOperating System	PC or PC CompatibleWindows 7	PC compatibleWindows 98, NT 4.0, 2000 andXP
Storage	Is not a primary imagestorage system. However,processed images areachieved on local harddrive	Hard disk or any compatible PCmethod: Optical, CDROM, Tape
Image ProcessingHardware	CUDA supported graphicscard or Equivalent	Javelin (PCI-bus) or Similar
Software core	Zia™ Image EnhancementSoftware(Zetta's own trademark)	GOP® Enhancement software(The GOP trademark is theproperty of Context Vision)
Image Input	DICOM	DICOM
Image output	DICOM	DICOM

Table -1: Zia vs Sharp View Image Enhancement System

7. Performance Testing:

Zia™ has been designed, verified and validated in compliance with FDA 21 CFR Part 820 requirements. The device has been validated through the use of ACR CT PHANTOM (Model 464) on a GE BrightSpeed 4-Slice, Siemens Sensation 16-Slice and Philips Brilliance 64-Slice scanners. Original images were acquired using a Head 120KV, Head 80KV, and Body 120KV protocols respectively. For each protocol, three mAs were selected in the range of 150-350mAs (150mAs, 250mAs, 350mAs), and three slice thickness were

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selected in the range of 1.25-5mm (1.25mm, 2.5mm, 5mm). All original images were reconstructed using filtered back projection, standard kernel, and matrix size of 512x512. A total of 81 datasets were processed and analyzed including noise, CT# (signal), low contrast resolution and high contrast resolution. CT# was measured as an average of pixel values of each ROI encompassing the four inserts (Acrylic, Bone, Polyethylene and Air) in the CT# module. Noise was measured as standard deviation of pixel values of an ROI placed at the center of the noise module as well as the four ROIs encompassing the four inserts. The results demonstrated that the system meets all defined specifications. Table-2 below summarizes the performance test results. A noise reduction of at-least 10% while maintaining CT# accuracy within +/-1HU indicates that the device is able to increase signal to noise ratio in the processed images.

Protocol	Expected	Scanners used for	Observed	Test result
parameters	outcome	testing	outcome
120kV, Head,mAs in rangeof 150-350,slice thicknessin range of1.25-5mm	Reducesnoise in theprocessedimages by atleast 10%;keeps CT #(signal)accuracywithin +/-1.0HU andmaintains(preserves)high and lowcontrastresolutions.	GE BrightSpeed 4;Siemens Sensation16;Philips Brilliance 64	Reducednoise in theprocessedimages by atleast 10%;kept CT #(signal)accuracywithin +/-1.0HU andmaintained(preserved)high and lowcontrastresolutions.	PASS
80kV, Head,mAs in rangeof 150-350,slice thicknessin range of1.25-5mm	Reducesnoise in theprocessedimages by atleast 10%;keeps CT #(signal)accuracywithin +/-1.0HU andmaintains(preserves)high and lowcontrastresolutions.	GE BrightSpeed 4;Siemens Sensation16;Philips Brilliance 64	Reducednoise in theprocessedimages by atleast 10%;kept CT #(signal)accuracywithin +/-1.0HU andmaintained(preserved)high and lowcontrastresolutions.	PASS
120kV, Body,mAs in range	Reducesnoise in the	GE BrightSpeed 4;	Reducednoise in the	PASS

Table -2: Zia Performance Test Results Summary

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of 150-350,slice thicknessin range of1.25-5mm	processedimages by atleast 10%;keeps CT #(signal)accuracywithin +/-1.0HU andmaintains(preserves)high and lowcontrastresolutions.	Siemens Sensation 16;Philips Brilliance 64	processedimages by atleast 10%;kept CT #(signal)accuracywithin +/-1.0HU andmaintained(preserved)high and lowcontrastresolutions.
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8. Safety and Effectiveness:

Based on the software test results and the information supplied in this 510(k), we conclude that this device is safe, effective, and substantially equivalent to the predicate devices.

9. Conclusion:

Zia™ is an image enhancement software which has similar indications for use as predicate device. The main difference is that the predicate device is a multimodality image transfer/storage/enhancement system where as Zia (as of 10/27/2016) is strictly a CT image enhancement system. Performance testing, along with verification and validation activities demonstrate that Zia™ is as safe and effective as 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).