K223623 · Subtle Medical, Inc. · LLZ · May 11, 2023 · Radiology
Device Facts
Record ID
K223623
Device Name
SubtleMR (2.3.x)
Applicant
Subtle Medical, Inc.
Product Code
LLZ · Radiology
Decision Date
May 11, 2023
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K223623 · May 11, 2023
SubtleMR (2.3.x)
Subtle Medical, Inc.
Retrospective clinical MRI images
Retrospective clinical MRI data was used to validate the performance of the SubtleMR software for noise reduction and sharpness enhancement. Performance was measured by SNR improvement and a Likert reader study assessing the visibility of small structures.
Signal-to-noise ratio (SNR) improvement; visibility of small structures (Likert reader study); thickness of anatomic structure and sharpness of structure boundaries
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
MRI image noise reduction
PGDnet neural network
SNR improvement >= 5% and Likert reader study non-inferiority
Passed
—
—
Retrospective clinical data study
>1 (readers)
MRI image sharpness enhancement
EDSR neural network
Thickness of anatomic structure and sharpness of structure boundaries improved in >= 90% of test datasets
Passed
—
—
Retrospective clinical data study
—
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.
Device Story
SubtleMR is a SaMD that enhances MRI images acquired on 1.2T, 1.5T, or 3T scanners. It processes standard-of-care MRI images as input, applying convolutional neural network-based algorithms to reduce noise or increase sharpness. The device operates as a fixed nonlinear filter; users select the enhancement type via DICOM metadata, command line, or environment variables. It is intended for use by radiologists in hospitals, clinics, or imaging centers. The software outputs enhanced images, which are used by clinicians to improve diagnostic image quality. The device supports processing via DICOM files or ISMRM Raw Data Format (ISMRMRD).
Clinical Evidence
Bench testing and retrospective clinical data study. Noise reduction performance: SNR improved by ≥5% in ROIs; Likert reader study confirmed non-inferiority of small structure visibility. Sharpness enhancement performance: ≥90% of test datasets showed improved anatomic structure thickness and boundary sharpness. All acceptance criteria met.
Technological Characteristics
SaMD; convolutional neural network-based image processing. Denoising (DNE) uses PGDnet architecture; sharpness enhancement (SRE) uses EDSR architecture. Built using PyTorch framework. Loss functions include composite L1, SSIM, perceptual, and high-frequency loss with weighting for pixel-level misalignment. Supports DICOM and ISMRMRD input formats. Operates as a fixed nonlinear filter.
Indications for Use
Indicated for image enhancement in MRI images, specifically noise reduction for head, spine, neck, abdomen, pelvis, prostate, breast, and musculoskeletal MRI, and sharpness enhancement for head MRI.
Regulatory Classification
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.
Special Controls
*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).
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May 11, 2023
Subtle Medical Inc. % Jared Seehafer Regulatory Consultant Enzyme Corporation 611 Gateway Blvd #120 SOUTH SAN FRANCISCO CA 94080
Re: K223623
Trade/Device Name: SubtleMR (2.3.x) Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: November 22, 2022 Received: April 13, 2023
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
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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 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 medical devices and radiation-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,
FDA
Daniel M. Krainak, Ph.D. Assistant Director Magnetic Resonance and Nuclear Medicine Team DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Ouality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2023 See PRA Statement below.
Submission Number (if known)
Device Name
SubtleMR (2.3.x)
Indications for Use (Describe)
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.
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
| Date Summary Prepared: | 2023-05-08 |
|---------------------------------------|--------------------------------------------------------------------------------------------------------|
| Contact Details | |
| Applicant Name: | Subtle Medical, Inc. |
| Applicant Address: | 883 Santa Cruz Ave, Suite 205<br>Menlo Park, CA 94025 United States |
| Applicant Contact: | Mr. Ajit Shankaranarayanan |
| Applicant Contact Telephone: | (650) 397-8709 |
| Applicant Contact Email: | ajit@subtlemedical.com |
| Correspondent Name: | Enzyme Corporation |
| Correspondent Address: | 611 Gateway Blvd. Ste 120<br>South San Francisco, CA 94080 United States |
| Correspondent Contact: | Mr. Jared Seehafer |
| Correspondent Contact<br>Telephone: | (415) 638-9554 |
| Correspondent Contact<br>Email: | jared@enzyme.com |
| Device Name | |
| Device Trade Name: | SubtleMR (2.3.x) |
| Common Name: | Medical image management and processing system |
| Classification Name: | System, Image Processing, Radiological |
| Regulation Number: | 21 CFR 892.2050 |
| Product Code: | LLZ |
| Device Class: | Class II |
| Legally Marketed Predicate<br>Device: | Predicate #: K203182<br>Predicate Trade Name: SubtleMR<br>Predicate Manufacturer: Subtle Medical, Inc. |
# Table 1. Contact Details & Device Name
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## Device Description Summary
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 inputs are standard of care MRI images. The outputs are images with enhanced image quality.
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.
# Intended Use / 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.
### Intended Use / Indications for Use Comparison
The intended use and indications for use of the subject device are identical to those of the predicate device.
# Technological Comparison
The technological characteristics of the subject device are identical to those of the predicate device with two exceptions.
With respect to workflow, in the predicate device, the software operates on DICOM files on the file system, enhances the images, and stores the enhanced images on the file system. The subject device maintains this functionality, and in addition is capable of processing images communicated over ISMRM Raw Data Format (ISMRMRD).
With respect to the design of the device's neural networks, the properties of the predicate and subject device were as follows:
Predicate: The application consists of two models: sharpness enhancement (SRE) and denoising (DNE). Subject: Same
Predicate: The SRE model is an EDSR neural network model. The DNE model is an EDSR neural network model.
Subject: The SRE model is an EDSR neural network model. The DNE model is an PGDnet neural network model.
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Predicate: Model was built using the Tensorflow/Keras machine learning framework. Subject: Model was built using the PyTorch machine learning framework.
Predicate: Uses composite L1 and SSIM loss function.
Subject: Uses composite L1, SSIM, perceptual, and high frequency loss function. Also, a weighting is used in the loss function to mitigate the pixel-level mis-alignment issue between the training data pairs.
The subject device was validated with test methods identical to those used to test the predicate device, and changes in technological characteristics do not present new questions of safety and effectiveness.
## Non-Clinical and/or Clinical Tests Summary & Conclusions
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.
Test methods were identical to those of the predicate device.
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 the visibility of small structures in the test datasets after SubtleMR was rated on average non-inferior to that before SubtleMR based on a Likert reader study. 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.
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