InferRead CT Lung

Infervision

InferRead CT Lung is a processing solution for lung cancer screening. It recognizes the core features of lung cancer, determine the characteristics of suspected lung nodules in different image sequences and aims to aid early-stage diagnosis. This solution provides information on nodules, including position, size, density, malignancy rate and evolution.

Product specifications

Information source: Vendor
Last updated: March 31, 2020

General
Product name	InferRead CT Lung
Company	Infervision
Subspeciality	Chest
Modality	CT
Disease targeted	Lung cancer
Key-features	Lung nodule detection, report generation, multi-timepoint analysis
Suggested use	During: interactive decision support (shows abnormalities/results only on demand), report suggestion After: diagnosis verification
Data characteristics
Population
Input	CT thorax
Input format	DICOM
Output	Type of lesions (solid, calcified, GGN nodules, semi-solid, etc.), location of each lesion (layer and anatomical location), density of the lesion, volume of the lesion, degree of malignancy of the lesion, draft report
Output format	DICOM overlay, pdf file (draft report), DICOM GSPS, webviewer (description of lesion features)
Technology
Integration	Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration CIS (Clinical Information System), Stand-alone third party application, Stand-alone webbased
Deployment	Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis	Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time	1 - 10 minutes
Certification
CE	Certified, Class IIa , MDD
FDA	510(k) cleared, Class II
Market presence
On market since	01-2020
Distribution channels
Countries present (clinical, non-research use)	7
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model	Subscription
Based on	Number of installations
Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers