The iQMR is intended for networking, communication, processing and enhancement of MRI images in DICOM format. The device processing is not effective for lesion, mass, or abnormalities of sizes less than 1.5mm. This device is indicated for use by qualified trained medical professionals.

Device Description

iQMR is a software package that is aimed to process MRI images. The iQMR processing enhances MRI images by reduction of the image noise. The software runs on a PC server, which is connected to the Local Area Network (LAN). The device receives MRI images from different work stations over the network in DICOM format, processes the images and transmits them in DICOM format, to selected work stations.

AI/ML Overview

The provided text describes the iQMR device and its FDA 510(k) submission. However, it does not contain the detailed information required to fully answer the request regarding acceptance criteria, a specific study proving it meets those criteria, expert details, or sample sizes for training and test sets in a clinical context.

The document states:

"Clinical tests were not conducted." [Page 4]
"However, MRI clinical images were processed in order to ensure that the iQMR conforms to defined user needs and intended uses under actual conditions." [Page 4]
It also references "predefined software test plan" and "MRI standard phantoms" for non-clinical verification. [Page 3]

Therefore, the response below will highlight the limitations of the provided text in addressing the specific questions, while extracting what information is available.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics from a formal clinical study. It mentions the device's intended use and the results of non-clinical tests.

Acceptance Criteria Category	Specific Criteria (as implied or stated)	Reported Device Performance (from non-clinical tests)
Intended Use Conformity	Device conforms to defined user needs and intended uses under actual conditions.	Clinical MRI images were processed to ensure conformity under actual conditions.
Software Functionality	Software meets its specified performance.	Verified by testing the software following predefined software test plan.
System Performance	System meets its specified performance (noise reduction, image enhancement).	Verified by testing using MRI standard phantoms.
Image Resolution Limit	Processing not effective for lesions, mass, or abnormalities of sizes less than 1.5mm.	(This is a limitation stated, not a performance metric achieved by the device in terms of detecting such objects). The document doesn't provide data to "prove" this performance, it's a declared limitation of the device's capability.
DICOM Compatibility	Receives and transmits MRI images in DICOM format.	Software handles DICOM input and output.
Safety and Effectiveness	Equivalent to predicate device in terms of safety and effectiveness.	Non-clinical tests demonstrate that differences in technological characteristics do not raise new questions of safety or effectiveness.
Risk Management	Risks managed and controlled following ISO 14971 standard.	Hazards identified, risk levels evaluated, mitigation measures taken. Benefits outweigh residual risks.

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

The document states: "Clinical tests were not conducted." [page 4].
It does mention that "MRI clinical images were processed" [page 4] but does not specify the sample size, number of images, or their provenance (e.g., country of origin, retrospective/prospective nature).

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

Since formal clinical tests were not conducted, and the document only mentions "processing MRI clinical images," there is no information provided about experts establishing ground truth for a test set.

4. Adjudication Method for the Test Set

As formal clinical tests with human interpretation and ground truth establishment were not conducted, no adjudication method is described.

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

No MRMC comparative effectiveness study was mentioned or conducted. The submission clarifies that "Clinical tests were not conducted." [page 4]. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided.

6. Standalone Performance

The device is described as "a software package that is aimed to process MRI images" [page 3] for "enhancement of MRI images by reduction of the image noise." [page 3]. While it performs its function without a human "in the loop" during image processing, there's no standalone clinical performance study results provided in the sense of diagnostic accuracy (e.g., sensitivity, specificity for disease detection) because its purpose is image enhancement and noise reduction, not primary diagnosis. The device's declared limitation ("not effective for lesion, mass, or abnormalities of sizes less than 1.5mm") further indicates it's an enhancement tool, not a diagnostic one.

7. Type of Ground Truth Used

For the "processing of MRI clinical images" to ensure conformity, the document does not specify the type of ground truth. Given the device's function (image enhancement/noise reduction) and the lack of clinical studies, it's highly likely that ground truth, if informally assessed, would relate to image quality metrics, noise levels, or visual assessments by qualified personnel familiar with MRI, rather than pathology or outcome data for diagnostic accuracy. For the non-clinical tests, ground truth would be based on "MRI standard phantoms."

8. Sample Size for the Training Set

The document does not specify a sample size for any training set. It details verification and validation using predefined software test plans, MRI standard phantoms, and processing clinical images, but does not distinguish these as "training" or "test" sets in the context of machine learning model development. The algorithm is described as "Medic Vision's Algorithms" without further detail on its development process involving training data.

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

Since no training set is mentioned, no information is provided on how its ground truth was established.

Summary

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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

Medic Vision - Imaging Solutions Ltd % Mr. Dan Laor Q&R Advisor 6 Sireni St. Haifa, 3297206 ISRAEL

Re: K173605

Trade/Device Name: iOMR Regulation Number: 21 CFR 892,2050 Regulation Name: Picture archiving and communications system Regulatory Class: II Product Code: LLZ Dated: February 19, 2018 Received: February 27, 2018

Dear Mr. Laor:

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 of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

March 8, 2018

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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.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice

(https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,
Robert Sauer

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) K173605

Device Name iQMR

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

Submitter details

Medic Vision Imaging Solutions Ltd. 3 Yozma St, Tirat Carmel 39032, Israel

Telephone +972.73.7262226

Submission Contact: Dan Laor Israel.

Details of the submitted Device

Proprietary Name:	iQMR
Regulation Number	892.2050
Product Code:	LLZ
Committee/Panel:	Radiology
Device Class:	2

6 Sireni St., Haifa, 3297206,

Type of 510(k) Submission:

Traditional

Identification of the Legally Marketed Predicate Device K993802 SharpView

Device Description

Intended use and indications for Use

Technological Characteristics

The iQMR software package is installed in an off-the-shelf PC server, which include off-the -shelf graphical boards. The Operating System is Linux Ubuntu. The iQMR software package consists of three software modules: The User Interface, Algorithm, and Interface module. Data inputs and output are MRI images in DICOM format.

Performance Tests

Non-Clincal tests

The device software has been verified by testing the software following predefined software test plan.

The iQMR system has been verified by testing that it meets its specified performance, using MRI standard phantoms.

The iQMR performance has been validated by testing it performing its intended and indications for use, in end-user environment.

Vol_003 002_510K Summary

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The above testing methods adhered to state-of-art standards and procedures. The tests results demonstrate that the device output meet the design input and the intended use.

Clinical tests:

Clinical tests were not conducted. However, MRI clinical images were processed in order to ensure that the iQMR conforms to defined user needs and intended uses under actual conditions.

Risk Management

The device risks were managed and controlled following the requirements of ISO 14971standard. The device hazards were identified, their risk levels were evaluated and mitigation measures were taken to reduce the risk levels. In Medic Vision opinion the benefits of providing the iQMR features, overweight the device residual risks.

Substantial Equivalence

Parameter	Predicate DeviceSharpView (K993802)	Subject DeviceiQMR
Intended use	Intended for use by qualifiedtrained medical professionals forenhancement of MRI images thatare transferred in the network inDICOM format.	The same
21CFR section	892.2050	The same
Product Code	LLZ	The same
TechnologicalCharacteristics
Device nature	SW package	The same
Operating System	Windows	Linux
Data input	MRI images in DICOM format	The same
Data output	MRI images in DICOM format	The same
ProcessingAlgorithms	GOP Enhancement Software	Medic Vision'sAlgorithms
User Interface	Included	The same

Comparison with the predicate device

Substantial Equivalence conclusion

The iQMR has the same intended use as the legally marketed SharpView predicate device. The two devices have similar technological characteristics. Results of tests, which were adhered to state-of-art standards and procedures, demonstrate that differences in the technological characteristics do not raise new questions of safety or effectiveness. Based on this discussion, it is Medic Vision's opinion that iQMR is substantially equivalent in terms of safety and effectiveness to the SharpView (K993802) 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).