InferRead Lung CT.AI

Infervision Medical Technology Co., Ltd. • Radiology • 05/16/2025

510(k)IEC 62304 Class B

Device Purpose

The InferRead Lung CT.AI device is an AI-powered post-processing application designed to assist radiologists in the detection and analysis of pulmonary nodules 4mm or greater from chest CT examinations of asymptomatic individuals. Its methodology leverages artificial intelligence for image processing, segmentation, measurement, and temporal comparison of nodules, with its safety and effectiveness confirmed through non-clinical testing to meet intended use and specifications.

Summary

On May 16, 2025, a determination was made regarding Infervision Medical Technology Co., Ltd.'s device, InferRead Lung CT.AI. This device, categorized as a Class II medical image management and processing system, was found to be substantially equivalent to legally marketed devices. Consequently, the manufacturer is permitted to market the device, provided they adhere to general controls, including provisions for annual registration, device listing, good manufacturing practice, and accurate labeling. Additional regulations, such as Quality System requirements and the Unique Device Identification System, are also applicable. The InferRead Lung CT.AI is an AI-powered post-processing application designed to assist radiologists in the detection, segmentation, measurement, and localization of pulmonary nodules 4mm or greater during chest CT examinations of asymptomatic individuals aged 55 and above. It also offers enhanced features for temporal comparison of nodules and comprehensive lung analysis. Extensive non-clinical testing, encompassing performance evaluations for its new functions like nodule registration and lobe localization, verified the device's adherence to its intended use and specifications, thereby confirming its safety and effectiveness in line with recognized industry standards.

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

InferRead Lung CT.AIAI-poweredPulmonary nodulesChest CTNodule detectionMedical image processingClass II medical deviceAsymptomatic individualsTemporal comparisonSubstantial equivalence

Device Metadata

Submission Number

K240554

Company

Infervision Medical Technology Co., Ltd.

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 specific sensitivity and specificity of InferRead Lung CT.AI for detecting pulmonary nodules across different size ranges, particularly those closer to the 4mm threshold?; How does the AI algorithm for nodule temporal comparison account for variations in CT acquisition parameters or patient positioning across longitudinal scans?; Are there any known limitations or specific patient populations where the device's performance might be compromised, such as in cases of extensive lung pathology or artifacts?; What clinical evidence or real-world data supports the device's effectiveness beyond non-clinical testing, especially regarding its impact on radiologist efficiency or diagnostic accuracy?; How seamlessly does InferRead Lung CT.AI integrate with existing Picture Archiving and Communication Systems (PACS) or Radiology Information Systems (RIS), and what are the practical workflow implications for radiologists?

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 Score20/100

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✓ Detected in Summary

§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.

• 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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