Ezra Flash

Ezra AI, Inc. • Radiology • 01/02/2025

510(k)IEC 62304 Class B

Device Purpose

Ezra Flash is an image processing software engineered to enhance the diagnostic quality of MR images by reducing noise in scans from 1.5-Tesla and 3-Tesla Siemens and GE scanners. This device specifically processes images within the head, abdomen, and pelvis regions across various sequences, utilizing its proprietary algorithm to achieve improved clarity and substantial equivalence for marketing.

Summary

Ezra AI, Inc. has received a determination allowing the marketing of its device, Ezra Flash, an image processing software. This software is designed to enhance MR images by reducing noise in scans acquired from 1.5-Tesla and 3-Tesla Siemens and GE scanners. It is specifically intended for use on patients over 18 years of age, processing images within the head, abdomen, and pelvis regions for various sequences, including Sagittal T1, Axial T2, Axial Flair, and Coronal T2. The review concluded that the device is substantially equivalent to currently marketed devices for its stated indications for use. The marketing of Ezra Flash is subject to ongoing compliance with general controls, including requirements for annual registration, device listing, good manufacturing practices, and truthful labeling. Depending on its classification, the device may also be subject to additional special controls. The manufacturer must adhere to all applicable regulations, such as the Quality System (QS) regulation and the Unique Device Identification (UDI) System rule. Guidance is provided for determining when changes to the device may necessitate a new review, and various resources are available for regulatory assistance and reporting adverse events.

AI Regulatory Concerns

Jev reads the full FDA letter and returns calibrated concern probabilities per regulatory category. These are AI estimates, not regulatory advice.

Keywords

Ezra FlashImage processing softwareMR imagesNoise reduction1.5-Tesla3-TeslaHeadabdomenpelvisRegulatory approvalMedical deviceSubstantial equivalence

Device Metadata

Submission Number

K242334

Company

Ezra AI, Inc.

Panel

Radiology

Product Code

N/A

Data Type

N/A

Clinical Function

N/A

AI Function

N/A

AI Subclass

N/A

Relevant Clinical Questions

Q1. What is the quantitative impact of Ezra Flash on image quality metrics (e.g., SNR, CNR) compared to unprocessed images or images processed by predicate devices?; How does Ezra Flash's noise reduction algorithm specifically operate to enhance MR images across different sequences and anatomical regions?; Are there any specific types of artifacts or pathologies for which Ezra Flash's performance is limited or potentially detrimental to diagnostic accuracy?; What clinical studies or data support the diagnostic utility and safety of using Ezra Flash-processed images for patient management decisions?; Does Ezra Flash offer benefits in terms of scan time reduction or lower magnetic field strength requirements while maintaining diagnostic quality?

Risk Classification

ESL Analysis

IEC 62304 ClassB

FDA Device ClassII

FDA Class II via 510(k) pathway; IEC 62304 Class B (software safety classification); Post-§524B but no clear network capability detected

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Cybersecurity Evidence

Based on AI-generated device summaries, not the full FDA submission. Items not detected here may still be present in the complete submission package.

Cyber Score5/100

SBOM Evidence⚠ Not in summary - likely in full submission per §524B

Cyber Risk Assessment⚠ Not in summary - likely in full submission per §524B

Postmarket Plan⚠ Not in summary - likely in full submission per §524B

§524B ApplicableYes

Supply Chain BOM Evidence

Based on the CycloneDX / OWASP ECMA-424 xBOM ecosystem. Detection is from the AI-generated summary.

SBOMSoftware Bill of Materials

- Not detected

ML-BOMMachine Learning Bill of Materials(algorithm, labeling)

✓ Detected

SaaSBOMSoftware-as-a-Service Bill of Materials

- Not detected

HBOMHardware Bill of Materials

- Not detected

CBOMCryptography Bill of Materials

- Not detected

VDR/VEXVulnerability Disclosure Report / Vulnerability Exploitability eXchange

- Not detected

OBOMOperations Bill of Materials

- Not detected

Analysis:

• Analysis is based on the AI-generated device summary, not the full FDA submission package. Click "Analyze Full FDA PDF" below to scan the actual submission document.

• Evidence of ML-BOM detected in AI-generated device summary.

• SBOM not mentioned in AI-generated device summary. Under §524B (effective Oct 2023), cyber devices must provide a SBOM.

• Cybersecurity risk assessment not referenced in AI-generated device summary. FDA cybersecurity guidance (2023) expects this for cyber devices.

• Postmarket cybersecurity monitoring plan not clearly documented in AI-generated device summary.

• Not detected in AI-generated device summary: SBOM, SaaSBOM, HBOM, CBOM, VDR/VEX, OBOM. These may be present in the full FDA submission.

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