SubtleMR is an image processing software that can be used for image enhancement in MRI images. It can be used to reduce image noise for head, spine, nelvis, prostate, breast and musculosketal MRI, or increase image sharpness for head MRI.

Device Description

SubtleMR is Software as a Medical Device (SaMD) consisting of a software algorithm that enhances images taken by MRI scanners. As it only processes images for the end user, the device has no user interface. It is intended to be used by radiologists in an imaging center, clinic, or hospital. The software can be used with MR images acquired as part of MRI exams on 1.2 Tesla. 1.5 Tesla or 3 Tesla scanners. The device's inouts are standard of care MRI images. The outputs are images with enhanced image quality.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Performance Test	Acceptance Criteria	Reported Device Performance
Noise Reduction	(i) Signal-to-noise ratio (SNR) of a selected region of interest (ROI) in each test dataset is on average improved by greater than or equal to 5% after SubtleMR enhancement compared to the original images.(ii) The visibility of small structures in the test datasets before and after SubtleMR is on average less than or equal to 0.5 Likert scale points (implying minimal visual difference in small structures).	This test passed.
Sharpness Enhancement	The thickness of anatomic structure and the sharpness of structure boundaries are improved after SubtleMR enhancement in at least 90% of the test datasets.	This test passed.

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

The document states that the study "utilized retrospective clinical data." However, it does not explicitly state the sample size for the test set (number of images or patients) or the country of origin of the data.

3. Number of Experts Used and Qualifications of Experts

The document does not explicitly state the number of experts used or their specific qualifications (e.g., "radiologist with 10 years of experience"). It mentions "visibility of small structures" and "thickness of anatomic structure and the sharpness of structure boundaries" were evaluated, implying expert review, but the details are missing.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for establishing the ground truth or evaluating the image quality metrics. It simply states that the tests "passed."

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

The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study involving human readers with and without AI assistance. The performance tests described focus on objective metrics (SNR) and subjective evaluation of image quality changes by the device, not on reader performance improvement.

6. Standalone (Algorithm Only) Performance

Yes, the performance data presented appears to be a standalone (algorithm only) performance evaluation. The metrics (SNR improvement, visibility of small structures, sharpness of structure boundaries) are directly related to the algorithm's output on images rather than evaluating human reader performance with or without the algorithm.

7. Type of Ground Truth Used

The ground truth used appears to be a combination:

Objective Measurement: For noise reduction, the "signal-to-noise ratio (SNR) of a selected region of interest (ROI)" was objectively measured.
Expert Consensus/Subjective Evaluation: For "visibility of small structures" and "thickness of anatomic structure and the sharpness of structure boundaries," a subjective evaluation was conducted using a Likert scale for noise reduction, and a percentage of datasets showing improvement for sharpness enhancement. While not explicitly stated as "expert consensus," these evaluations would typically require trained medical professionals (e.g., radiologists) to perform.

8. Sample Size for the Training Set

The document does not provide the sample size for the training set. It mentions the algorithm uses a "convolutional network-based algorithm" and that "parameters of the filters were obtained through an image-guided optimization process," implying a training phase, but the size is not specified.

9. How the 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 mentions "image-guided optimization process" to obtain the parameters of the filters, which implies that the training data had some form of "ground truth" to guide the optimization, but the nature of this ground truth (e.g., perfectly noise-free images, perfectly sharp images) and how it was derived is not detailed.

Summary

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February 26, 2021

Image /page/0/Picture/1 description: The image contains two logos. The logo on the left is the Department of Health & Human Services - USA logo. The logo on the right is the FDA U.S. Food & Drug Administration logo. The FDA logo is in blue.

Subtle Medical, Inc. % Jared Seehafer Regulatory Consultant Enzyme Corporation 611 Gateway Blvd #120 SOUTH SAN FRANCISCO CA 94080

Re: K203182

Trade/Device Name: SubtleMR Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: November 28, 2020 Received: December 1, 2020

Dear Jared Seehafer:

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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. 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) for

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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

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 https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). 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 (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely.

Michael D. O'Hara For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K203182

Device Name SubtleMR

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
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| X Prescription Use (Part 21 CFR 801 Subpart D)

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

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510(k) Summary

K203182

Submitter's Name:	Subtle Medical, Inc.
Address:	883 Santa Cruz Ave, Suite 205Menlo Park, CA 94025
Contact Person:	Jared Seehafer
Title:	Regulatory Consultant
Telephone Number:	415-857-9554
Fax Number:	415-367-1279
Email:	jared@enzyme.com
Date Summary Prepared:	18-FEB-2021
Device Proprietary Name:	SubtleMR
Model Number:	V 2.0.0
Common Name:	SubtleMR
Regulation Number:	21 CFR 892.2050
Regulation Name:	System, Image Processing, Radiological
Product Code:	LLZ
Device Class:	Class II
Predicate Device	Trade name: SubtleMRManufacturer: Subtle Medical, Inc.Regulation Number: 21 CFR 892.2050Regulation Name: System, Image Processing,RadiologicalDevice Class: Class IIProduct Code: LLZ510(k) Number: K191688510(k) Clearance Date: September 16, 2019

Table 1. Subject Device Overview.

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1 Device Description

The software uses a convolutional network-based algorithm to improve image quality by reducing noise or enhancing the image sharpness. The algorithm's specific parameters vary depending on the choice of image enhancement: noise reduction or sharpness enhancement, while the network designs are similar. For each choice, there is a fixed set of parameters and the algorithm is working as a fixed nonlinear filter. The choice of image enhancement is made by the end user via the DICOM Series Description, command line argument, or environment variable.

2 Indications for Use

SubtleMR is an image processing software that can be used for image enhancement in MRI images. It can be used to reduce image noise for head, spine, neck, abdomen, pelvis, prostate, breast and musculoskeletal MRI, or increase image sharpness for head MRI.

3 Purpose of Submission

The purpose of this 510(k) is to provide premarket notification for an expansion in the indications for use of SubtleMR to include: a) additional anatomical locations for which SubtleMR can reduce image and b) that SubtleMR can increase image sharpness in both contrast-enhanced and non-contrast-enhanced head MRI.

Summary of Technological Characteristics Comparison 4

Table 2 shows the similarities and differences between the technological characteristics of the two products.

Topic	Predicate Device	Subject Device
PhysicalCharacteristics	Software package that operates onoff-the-shelf hardware	Same
Computer	Linux Compatible	Same
DICOMStandardCompliance	The software processes DICOMcompliant image data	Same
Topic	Predicate Device	Subject Device
OperatingSystem	Linux	Same
Modalities	MRI	Same
User Interface	None	Same
ImageEnhancementAlgorithmDescription	SubtleMR software implementsan image enhancement algorithmusing convolutional neuralnetwork based filtering. Originalimages are enhanced by runningthrough a cascade of filter banks,where thresholding and scalingoperations are applied. Separateneural network based filters areobtained for noise reduction andsharpness enhancement. Theparameters of the filters wereobtained through an image-guidedoptimization process.	Same
Workflow	The software operates on DICOMfiles on the file system, enhancesthe images, and stores theenhanced images on the filesystem. The receipt of originalDICOM image files and deliveryof enhanced images as DICOMfiles depends on other softwaresystems. Enhanced images co-exist with the original images.	Same
TargetAnatomicalLocations	Head, spine, neck, and knee MRI	Head, spine, neck, abdomen,pelvis, prostate, breast andmusculoskeletal MRI

Table 2. Summary of Technological Characteristics Comparison.

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Performance Data 5

Subtle Medical conducted the following performance testing:

Software verification and validation testing .
. Study that utilized retrospective clinical data to demonstrate the software enhanced image quality in MR images via a reduction of noise or sharpness enhancement.

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The main performance study, utilizing retrospective clinical data, was divided into two tests.

For the noise reduction performance test, acceptance criteria were that signal-to-noise ratio (SNR) of a selected region of interest (ROI) in each test dataset is on average improved by greater than or equal to 5% after SubtleMR enhancement compared to the original images, and (ii) the visibility of small structures in the test datasets before and after SubtleMR is on average less than or equal to 0.5 Likert scale points. This test passed.

For the sharpness enhancement performance test, acceptance criteria were that the thickness of anatomic structure and the sharpness of structure boundaries are improved after SubtleMR enhancement in at least 90% of the test datasets. This test passed.

Based upon the results of this testing, the SubtleMR performance was determined to be substantially equivalent to the predicate device.

Substantial Equivalence Conclusion 6

The predicate for the subject device is its legally marketed prior revision (K191688). The two devices have the same intended use and similar indications for use. The two devices have nearly identical technological characteristics, the lone exception being the subject device's expanded target anatomical locations relative to the predicate device. The subject device was verified and validated using the same test methods and acceptance criteria as the predicate device and does not introduce any additional risk relative to its predicate. Therefore, this difference in technological characteristics does not raise different questions of safety and effectiveness. Consequently, SubtleMR is 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).