(72 days)
Not Found
Yes
The device description explicitly states that the software uses a "convolutional neural network-based algorithm" to improve image quality. Convolutional neural networks are a type of artificial neural network commonly used in deep learning, which is a subset of machine learning.
No.
The device is an image processing software that enhances MR images by reducing noise; it does not directly treat or diagnose a disease or condition.
No
Explanation: The device is described as image processing software used for image enhancement and noise reduction in MR images. It does not perform diagnosis; rather, it improves the quality of images that radiologists then use for diagnosis.
Yes
The device is explicitly described as "Software as a Medical Device (SaMD)" and its function is solely image processing, receiving and outputting DICOM images without mentioning any associated hardware components included as part of the device itself.
Based on the provided information, Ezra Flash is not an In Vitro Diagnostic (IVD) device.
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices used to perform tests on samples taken from the human body (like blood, urine, tissue) to provide information about a person's health. They are used outside of the body ("in vitro").
- Ezra Flash's Function: Ezra Flash is an image processing software that enhances existing medical images (MRI scans) taken from the body. It does not analyze biological samples or perform tests on bodily fluids or tissues. Its function is to improve the quality of images that have already been acquired.
Therefore, Ezra Flash falls under the category of medical imaging software, not In Vitro Diagnostics.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The relevant text section indicates "Not Found" for "Control Plan Authorized (PCCP) and relevant text."
Intended Use / Indications for Use
Ezra Flash is an image processing software used for image enhancement of MR images. It can be used to reduce image noise in images acquired as part of non-contrast MRI exams on 3-Tesla Siemens and GE scanners for Sagittal T1, Axial T2 and Axial Flair sequences within the head region for patients > 18 years of age.
Product codes
LLZ
Device Description
Ezra Flash is a Software as a Medical Device (SaMD) consisting of a software algorithm that enhances images of the head region taken by MRI scanners. As it only processes images for the end user, the device has no 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 3-Tesla Siemens and GE scanners.
The outputs are images with enhanced image quality. Both the original non-enhanced studies and the Ezra Flash-enhanced studies are available to the end user.
Ezra Flash receives DICOM-compliant non-contrast MR image inputs acquired on 3-Tesla scanners for Sagittal T1, Axial T2 and Axial Flair sequences within the head region. The software uses a convolutional neural network-based algorithm to improve image quality by reducing noise. The device outputs a DICOM-compliant copy of the images with improved image quality.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Ezra Flash software implements an image enhancement algorithm using a convolutional neural network-based filtering. Original images are enhanced by running through a cascade of filter banks, where thresholding and scaling operations are applied. These filters result in a single machine learning model that reduces noise. The parameters of the filters were obtained through an image-guided optimization process.
Input Imaging Modality
MR images
Anatomical Site
head region
Indicated Patient Age Range
18 years of age
Intended User / Care Setting
radiologists in an imaging center, clinic, or hospital.
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
The Ezra Flash has been developed in a manner consistent with accepted standards for software development and evaluated in accordance with design specifications and applicable performance standards through software verification, validation, and usability testing.
Ezra performed the following main performance testing for Ezra Flash:
-
- Signal-to-Noise Ratio (SNR)
- SNR of a selected region of interest (ROI) in each test dataset is on average improved by > 5% after Ezra Flash enhancement compared to original MR-acquired images (raw).
-
- Contrast-to-Noise Ratio (CNR)
- CNR of a selected region of interest (ROI) in each test dataset is on average improved by > 0% after Ezra Flash enhancement compared to the MR-acquired raw images.
-
- Image Quality Perceived Noise
- The mean Likert results for the Ezra Flash-enhanced images compared to the original MR-acquired images (raw) is greater than or equal to 0.5 Likert scale points.
The test results demonstrated that the Ezra Flash performs to its intended use, is deemed acceptable for clinical use, and does not introduce new questions of safety or efficacy. The testing was conducted in accordance to the software validation/verification plans and protocols. A full description of the software functionality, device hazard analysis, software requirements, verification, validation and usability study is provided in this submission.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
- Signal-to-Noise Ratio (SNR) improved by > 5%
- Contrast-to-Noise Ratio (CNR) improved by > 0%
- Image Quality Perceived Noise: mean Likert results >= 0.5 Likert scale points
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 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).
0
Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo features the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG ADMINISTRATION" in blue text.
April 13, 2023
Ezra AI, Inc. % David Girard VP of Operations, Quality and Regulatory 419 Park Ave S, Suite 600 New York, NY 10016
Re: K230264
Trade/Device Name: Ezra Flash Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: LLZ Dated: April 6, 2023 Received: April 6, 2023
Dear David Girard:
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
1
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,
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 Quality Center for Devices and Radiological Health
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Indications for Use
510(k) Number (if known) K230264
Device Name Ezra Flash
Indications for Use (Describe)
Ezra Flash is an image processing software used for image enhancement of MR images. It can be used to reduce image noise in images acquired as part of non-contrast MRI exams on 3-Tesla Siemens for Sagittal T1, Axial T2 and Axial Flair sequences within the head region for patients > 18 years of age.
| 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 1
This 510(k) Summary is in accordance with the requirements of the Safe Medical Device Act (SMDA) of 1990. The content of this 510(k) summary is provided in conformance with 21 CFR Part 807.92.
Submitter Information 1.1
| Submitter's Name | Ezra Al, Inc. |
|---|---|
| Address | 419 Park Ave S, Suite 600, New York, NY 10016 USA |
| Telephone | +1 (646) 402-5751 |
| Contact Person | David Girard |
| Date of Summary Preparation | January 31st, 2023 |
Subject Device Information 1.2
| Device Name | Ezra Flash |
|---|---|
| Model Number | FLHAI00PL00IF00IT00LB00 |
| Common Name | Ezra Flash |
| Classification | II |
| Review Panel | Radiology |
| Product Code | LLZ |
| Regulations | 21 CFR 892.2050- System, Image Processing, Radiological |
Predicate Device Information 1.3
Device Name SubtleMR 510(k) Number K203182
4
Device Description 2
Ezra Flash is a Software as a Medical Device (SaMD) consisting of a software algorithm that enhances images of the head region taken by MRI scanners. As it only processes images for the end user, the device has no 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 3-Tesla Siemens and GE scanners.
The outputs are images with enhanced image quality. Both the original non-enhanced studies and the Ezra Flash-enhanced studies are available to the end user.
Ezra Flash receives DICOM-compliant non-contrast MR image inputs acquired on 3-Tesla scanners for Sagittal T1, Axial T2 and Axial Flair sequences within the head region. The software uses a convolutional neural network-based algorithm to improve image quality by reducing noise. The device outputs a DICOM-compliant copy of the images with improved image quality.
3 Indications for Use
Ezra Flash is an image processing software used for image enhancement of MR images. It can be used to reduce image noise in images acquired as part of non-contrast MRI exams on 3-Tesla Siemens and GE scanners for Sagittal T1, Axial T2 and Axial Flair sequences within the head region for patients > 18 years of age.
5
Summary of Technological 4 Characteristics Comparison
Table 1 shows that Ezra Flash and the Predicate Device (K203182) are equivalent in technological characteristics.
| Feature | Subject Device | Predicate Device (K203182) |
|---|---|---|
| Regulation Number | CFR 892.2050 | Same |
| Product Code | LLZ | Same |
| Indications for Use | Ezra Flash is an image processing soft- | |
| ware used for image enhancement of | ||
| MR images. It can be used to reduce | ||
| image noise for non-contrast 3T head | ||
| MRI scans. | SubtleMR is an image processing soft- | |
| ware that can be used for image en- | ||
| hancement 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. | ||
| Physical Character- | ||
| istics | Software package that operates on off- | |
| the-shelf hardware | Same | |
| Computer | Linux Compatible | Same |
| DICOM | ||
| Standard | ||
| Compliance | The software processes DICOM com- | |
| pliant image data | Same | |
| Operating System | Linux | Same |
| Modalities | MRI | Same |
| User Interface | None - enhanced images are viewed | |
| on existing PACS workstations | Same |
Table 1: Subject and Predicate Device Comparison.
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| Image Enhancement
Algorithm Description | Ezra Flash software implements an im-
age enhancement algorithm using a
convolutional neural network-based fil-
tering. Original images are enhanced
by running through a cascade of filter
banks, where thresholding and scal-
ing operations are applied. These fil-
ters result in a single machine learn-
ing model that reduces noise. The pa-
rameters of the filters were obtained
through an image-guided optimization
process. | SubtleMR software implements an im-
age enhancement algorithm using con-
volutional neural network based filter-
ing. Original images are enhanced
by running through a cascade of filter
banks, where thresholding and scaling
operations are applied. Separate neu-
ral network based filters are obtained
for noise reduction and sharpness in-
crease. The parameters of the fil-
ters were obtained through an image-
guided optimization process. |
|--------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Workflow | The software operates on DICOM files
on the file system, enhances the im-
ages, and stores the enhanced images
on the file system. The receipt of orig-
inal DICOM image files and delivery of
enhanced images as DICOM files de-
pends on other software systems. En-
hanced images co-exist with the origi-
nal images. | Same |
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5 Performance Testing
The Ezra Flash has been developed in a manner consistent with accepted standards for software development and evaluated in accordance with design specifications and applicable performance standards through software verification, validation, and usability testing.
Ezra performed the following main performance testing for Ezra Flash:
-
- Signal-to-Noise Ratio (SNR)
- SNR of a selected region of interest (ROI) in each test dataset is on average improved by > 5% after Ezra Flash enhancement compared to original MR-acquired images (raw).
-
- Contrast-to-Noise Ratio (CNR)
- CNR of a selected region of interest (ROI) in each test dataset is on average improved by > 0% after Ezra Flash enhancement compared to the MR-acquired raw images.
-
- Image Quality Perceived Noise
- The mean Likert results for the Ezra Flash-enhanced images compared to the original MR-acquired images (raw) is greater than or equal to 0.5 Likert scale points.
The test results demonstrated that the Ezra Flash performs to its intended use, is deemed acceptable for clinical use, and does not introduce new questions of safety or efficacy. The testing was conducted in accordance to the software validation/verification plans and protocols. A full description of the software functionality, device hazard analysis, software requirements, verification, validation and usability study is provided in this submission.
8
Conformance Standards б
There are no applicable FDA mandated performance standards for this device. However, voluntary standards have been utilized in the production of the software. The device was designed and developed in accordance to the following conformance standards:
- · ISO 14971:2019 Medical Devices Application of risk management to medical devices
- · IEC 62304 Edition 1.1: 2015 Medical device software Software life cycle processes
- NEMA PS 3.1-3.20 (2021e) Digital Imaging and Communications in Medicine (DICOM) set
Substantial Equivalence Conclusion 7
The Ezra Flash has the same intended use and similar technological characteristics as the predicate SubtleMR (K203182) device. As demonstrated in this submission, the subject and predicate device are identical in indications for use and intended use for the reduction of image noise in 3T head MRI scans. The subject Ezra Flash is substantially equivalent to the predicate SubtleMR (K203182) device, and the minor differences in the technological characteristics of the subject and predicate device do not raise any new or different questions of safety and effectiveness.